2. Training and Detection.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "QUANWN3rpfC9"
   },
   "source": [
    "# 0. Setup Paths"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "146BB11JpfDA"
   },
   "outputs": [],
   "source": [
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "42hJEdo_pfDB"
   },
   "outputs": [],
   "source": [
    "CUSTOM_MODEL_NAME = 'my_ssd_mobnet' \n",
    "PRETRAINED_MODEL_NAME = 'ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8'\n",
    "PRETRAINED_MODEL_URL = 'http://download.tensorflow.org/models/object_detection/tf2/20200711/ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8.tar.gz'\n",
    "TF_RECORD_SCRIPT_NAME = 'generate_tfrecord.py'\n",
    "LABEL_MAP_NAME = 'label_map.pbtxt'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "id": "hbPhYVy_pfDB"
   },
   "outputs": [],
   "source": [
    "paths = {\n",
    "    'WORKSPACE_PATH': os.path.join('Tensorflow', 'workspace'),\n",
    "    'SCRIPTS_PATH': os.path.join('Tensorflow','scripts'),\n",
    "    'APIMODEL_PATH': os.path.join('Tensorflow','models'),\n",
    "    'ANNOTATION_PATH': os.path.join('Tensorflow', 'workspace','annotations'),\n",
    "    'IMAGE_PATH': os.path.join('Tensorflow', 'workspace','images'),\n",
    "    'MODEL_PATH': os.path.join('Tensorflow', 'workspace','models'),\n",
    "    'PRETRAINED_MODEL_PATH': os.path.join('Tensorflow', 'workspace','pre-trained-models'),\n",
    "    'CHECKPOINT_PATH': os.path.join('Tensorflow', 'workspace','models',CUSTOM_MODEL_NAME), \n",
    "    'OUTPUT_PATH': os.path.join('Tensorflow', 'workspace','models',CUSTOM_MODEL_NAME, 'export'), \n",
    "    'TFJS_PATH':os.path.join('Tensorflow', 'workspace','models',CUSTOM_MODEL_NAME, 'tfjsexport'), \n",
    "    'TFLITE_PATH':os.path.join('Tensorflow', 'workspace','models',CUSTOM_MODEL_NAME, 'tfliteexport'), \n",
    "    'PROTOC_PATH':os.path.join('Tensorflow','protoc')\n",
    " }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "LwhWZMI0pfDC"
   },
   "outputs": [],
   "source": [
    "files = {\n",
    "    'PIPELINE_CONFIG':os.path.join('Tensorflow', 'workspace','models', CUSTOM_MODEL_NAME, 'pipeline.config'),\n",
    "    'TF_RECORD_SCRIPT': os.path.join(paths['SCRIPTS_PATH'], TF_RECORD_SCRIPT_NAME), \n",
    "    'LABELMAP': os.path.join(paths['ANNOTATION_PATH'], LABEL_MAP_NAME)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "HR-TfDGrpfDC"
   },
   "outputs": [],
   "source": [
    "for path in paths.values():\n",
    "    if not os.path.exists(path):\n",
    "        if os.name == 'posix':\n",
    "            !mkdir -p {path}\n",
    "        if os.name == 'nt':\n",
    "            !mkdir {path}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "OLU-rs_ipfDE"
   },
   "source": [
    "# 1. Download TF Models Pretrained Models from Tensorflow Model Zoo and Install TFOD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://www.tensorflow.org/install/source_windows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "id": "K-Cmz2edpfDE",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: wget in c:\\users\\manas\\anaconda3\\lib\\site-packages (3.2)\n"
     ]
    }
   ],
   "source": [
    "if os.name=='nt':\n",
    "    !pip install wget\n",
    "    import wget"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "id": "iA1DIq5OpfDE"
   },
   "outputs": [],
   "source": [
    "if not os.path.exists(os.path.join(paths['APIMODEL_PATH'], 'research', 'object_detection')):\n",
    "    !git clone https://github.com/tensorflow/models {paths['APIMODEL_PATH']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "id": "rJjMHbnDs3Tv"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "100% [..........................................................................] 1468733 / 1468733        1 file(s) moved.\n",
      "        1 file(s) copied.\n",
      "running build\n",
      "running build_py\n",
      "copying object_detection\\protos\\anchor_generator_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\argmax_matcher_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\bipartite_matcher_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\box_coder_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\box_predictor_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\calibration_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\center_net_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\eval_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\faster_rcnn_box_coder_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\faster_rcnn_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\flexible_grid_anchor_generator_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\fpn_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\graph_rewriter_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\grid_anchor_generator_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\hyperparams_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\image_resizer_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\input_reader_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\keypoint_box_coder_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\losses_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\matcher_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\mean_stddev_box_coder_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\model_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\multiscale_anchor_generator_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\optimizer_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\pipeline_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\post_processing_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\preprocessor_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\region_similarity_calculator_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\square_box_coder_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\ssd_anchor_generator_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\ssd_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\string_int_label_map_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\target_assigner_pb2.py -> build\\lib\\object_detection\\protos\n",
      "copying object_detection\\protos\\train_pb2.py -> build\\lib\\object_detection\\protos\n",
      "running egg_info\n",
      "writing object_detection.egg-info\\PKG-INFO\n",
      "writing dependency_links to object_detection.egg-info\\dependency_links.txt\n",
      "writing requirements to object_detection.egg-info\\requires.txt\n",
      "writing top-level names to object_detection.egg-info\\top_level.txt\n",
      "reading manifest file 'object_detection.egg-info\\SOURCES.txt'\n",
      "writing manifest file 'object_detection.egg-info\\SOURCES.txt'\n",
      "running install\n",
      "running bdist_egg\n",
      "running egg_info\n",
      "writing object_detection.egg-info\\PKG-INFO\n",
      "writing dependency_links to object_detection.egg-info\\dependency_links.txt\n",
      "writing requirements to object_detection.egg-info\\requires.txt\n",
      "writing top-level names to object_detection.egg-info\\top_level.txt\n",
      "reading manifest file 'object_detection.egg-info\\SOURCES.txt'\n",
      "writing manifest file 'object_detection.egg-info\\SOURCES.txt'\n",
      "installing library code to build\\bdist.win-amd64\\egg\n",
      "running install_lib\n",
      "running build_py\n",
      "creating build\\bdist.win-amd64\\egg\n",
      "creating build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\build_imagenet_data.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\cifar10.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\dataset_factory.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\dataset_utils.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\download_and_convert_cifar10.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\download_and_convert_flowers.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\download_and_convert_mnist.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\download_and_convert_visualwakewords.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\download_and_convert_visualwakewords_lib.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\flowers.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\imagenet.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\mnist.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\preprocess_imagenet_validation_data.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\process_bounding_boxes.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\visualwakewords.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "copying build\\lib\\datasets\\__init__.py -> build\\bdist.win-amd64\\egg\\datasets\n",
      "creating build\\bdist.win-amd64\\egg\\deployment\n",
      "copying build\\lib\\deployment\\model_deploy.py -> build\\bdist.win-amd64\\egg\\deployment\n",
      "copying build\\lib\\deployment\\model_deploy_test.py -> build\\bdist.win-amd64\\egg\\deployment\n",
      "copying build\\lib\\deployment\\__init__.py -> build\\bdist.win-amd64\\egg\\deployment\n",
      "creating build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\alexnet.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\alexnet_test.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\cifarnet.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\cyclegan.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\cyclegan_test.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\dcgan.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\dcgan_test.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\i3d.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\i3d_test.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\i3d_utils.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\inception.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\inception_resnet_v2.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\inception_resnet_v2_test.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\inception_utils.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\inception_v1.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\inception_v1_test.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\inception_v2.py -> build\\bdist.win-amd64\\egg\\nets\n",
      "copying build\\lib\\nets\\inception_v2_test.py -> build\\bdist.win-amd64\\egg\\nets\n",
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      "creating build\\bdist.win-amd64\\egg\\EGG-INFO\n",
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      "object-detection 0.1 is already the active version in easy-install.pth\n",
      "\n",
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      "\n",
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      "\n",
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      "Processing avro-python3-1.10.2.tar.gz\n",
      "Writing C:\\Users\\Manas\\AppData\\Local\\Temp\\easy_install-_of7banf\\avro-python3-1.10.2\\setup.cfg\n",
      "Running avro-python3-1.10.2\\setup.py -q bdist_egg --dist-dir C:\\Users\\Manas\\AppData\\Local\\Temp\\easy_install-_of7banf\\avro-python3-1.10.2\\egg-dist-tmp-v2l84vdb\n",
      "Copying avro_python3-1.10.2-py3.9.egg to c:\\users\\manas\\anaconda3\\lib\\site-packages\n",
      "Adding avro-python3 1.10.2 to easy-install.pth file\n",
      "Installing avro script to C:\\Users\\Manas\\anaconda3\\Scripts\n",
      "\n",
      "Installed c:\\users\\manas\\anaconda3\\lib\\site-packages\\avro_python3-1.10.2-py3.9.egg\n",
      "Searching for portalocker\n",
      "Reading https://pypi.org/simple/portalocker/\n",
      "Downloading https://files.pythonhosted.org/packages/8c/df/d4f711d168524f5aebd7fb30969eaa31e3048cf8979688cde3b08f6e5eb8/portalocker-2.7.0-py2.py3-none-any.whl#sha256=a07c5b4f3985c3cf4798369631fb7011adb498e2a46d8440efc75a8f29a0f983\n",
      "Best match: portalocker 2.7.0\n",
      "Processing portalocker-2.7.0-py2.py3-none-any.whl\n",
      "Installing portalocker-2.7.0-py2.py3-none-any.whl to c:\\users\\manas\\anaconda3\\lib\\site-packages\n",
      "Adding portalocker 2.7.0 to easy-install.pth file\n",
      "\n",
      "Installed c:\\users\\manas\\anaconda3\\lib\\site-packages\\portalocker-2.7.0-py3.9.egg\n",
      "Searching for tensorflow-text~=2.11.0\n",
      "Reading https://pypi.org/simple/tensorflow-text/\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\setuptools\\command\\install.py:34: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\setuptools\\command\\easy_install.py:144: EasyInstallDeprecationWarning: easy_install command is deprecated. Use build and pip and other standards-based tools.\n",
      "  warnings.warn(\n",
      "zip_safe flag not set; analyzing archive contents...\n",
      "object_detection.core.__pycache__.densepose_ops.cpython-39: module references __file__\n",
      "object_detection.core.__pycache__.preprocessor.cpython-39: module MAY be using inspect.stack\n",
      "object_detection.utils.__pycache__.autoaugment_utils.cpython-39: module MAY be using inspect.stack\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning:  is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-0.6.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.0.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.1.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.1.1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.2.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.3.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.4.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.5.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.6.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.7.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.8.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.9.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.10.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.11.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.12.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.13.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.14.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.15.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.16.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.17.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.18.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.19.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.20.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.21.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.22.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.23.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.24.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.25.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.26.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.27.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.28.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.29.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.29.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.30.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.30.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.31.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.31.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.32.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.32.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.33.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.33.0rc2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.33.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.34.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.34.0rc2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.34.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.35.0rc2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.35.0rc3 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.35.0rc5 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.35.0rc6 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.35.0rc8 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.35.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.36.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.36.0rc2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.36.0rc3 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.36.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.37.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.37.0rc2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.37.0rc3 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.37.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.38.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.38.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.39.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.39.0rc2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.39.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.40.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.40.0rc2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.40.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.41.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.41.0rc2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.41.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.42.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.42.0rc2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.42.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.43.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.43.0rc2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.43.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.44.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.44.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: beam-2.45.0rc1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: python3-1.7.6 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: python3-1.7.7 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: python3-1.8.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: python3-1.8.1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: python3-1.8.2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: python3-1.9.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: python3-1.9.1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: python3-1.9.2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: python3-1.9.2.1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: python3-1.10.0 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: python3-1.10.1 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning: python3-1.10.2 is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\setuptools\\command\\install.py:34: SetuptoolsDeprecationWarning: setup.py install is deprecated. Use build and pip and other standards-based tools.\n",
      "  warnings.warn(\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\pkg_resources\\__init__.py:123: PkgResourcesDeprecationWarning:  is an invalid version and will not be supported in a future release\n",
      "  warnings.warn(\n",
      "No local packages or working download links found for tensorflow-text~=2.11.0\n",
      "error: Could not find suitable distribution for Requirement.parse('tensorflow-text~=2.11.0')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Obtaining file:///C:/Users/Manas/OneDrive/Documents/HackNotts/Hackathon/tfod/TFODCourse/Tensorflow/models/research/slim\n",
      "  Preparing metadata (setup.py): started\n",
      "  Preparing metadata (setup.py): finished with status 'done'\n",
      "Requirement already satisfied: six in c:\\users\\manas\\anaconda3\\lib\\site-packages (from slim==0.1) (1.16.0)\n",
      "Requirement already satisfied: tf-slim>=1.1 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from slim==0.1) (1.1.0)\n",
      "Requirement already satisfied: absl-py>=0.2.2 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tf-slim>=1.1->slim==0.1) (1.4.0)\n",
      "Installing collected packages: slim\n",
      "  Attempting uninstall: slim\n",
      "    Found existing installation: slim 0.1\n",
      "    Uninstalling slim-0.1:\n",
      "      Successfully uninstalled slim-0.1\n",
      "  Running setup.py develop for slim\n",
      "Successfully installed slim-0.1\n"
     ]
    }
   ],
   "source": [
    "# Install Tensorflow Object Detection \n",
    "if os.name=='posix':  \n",
    "    !apt-get install protobuf-compiler\n",
    "    !cd Tensorflow/models/research && protoc object_detection/protos/*.proto --python_out=. && cp object_detection/packages/tf2/setup.py . && python -m pip install . \n",
    "    \n",
    "if os.name=='nt':\n",
    "    url=\"https://github.com/protocolbuffers/protobuf/releases/download/v3.15.6/protoc-3.15.6-win64.zip\"\n",
    "    wget.download(url)\n",
    "    !move protoc-3.15.6-win64.zip {paths['PROTOC_PATH']}\n",
    "    !cd {paths['PROTOC_PATH']} && tar -xf protoc-3.15.6-win64.zip\n",
    "    os.environ['PATH'] += os.pathsep + os.path.abspath(os.path.join(paths['PROTOC_PATH'], 'bin'))   \n",
    "    !cd Tensorflow/models/research && protoc object_detection/protos/*.proto --python_out=. && copy object_detection\\\\packages\\\\tf2\\\\setup.py setup.py && python setup.py build && python setup.py install\n",
    "    !cd Tensorflow/models/research/slim && pip install -e . "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\models\\ssd_efficientnet_bifpn_feature_extractor.py\", line 36, in <module>\n",
      "    from official.legacy.image_classification.efficientnet import efficientnet_model\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tf_models_official-2.11.3-py3.9.egg\\official\\legacy\\image_classification\\efficientnet\\efficientnet_model.py\", line 33, in <module>\n",
      "    from official.modeling import tf_utils\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tf_models_official-2.11.3-py3.9.egg\\official\\modeling\\tf_utils.py\", line 22, in <module>\n",
      "    from official.modeling import activations\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tf_models_official-2.11.3-py3.9.egg\\official\\modeling\\activations\\__init__.py\", line 17, in <module>\n",
      "    from official.modeling.activations.mish import mish\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tf_models_official-2.11.3-py3.9.egg\\official\\modeling\\activations\\mish.py\", line 19, in <module>\n",
      "    from tensorflow_addons.utils import types\n",
      "ModuleNotFoundError: No module named 'tensorflow_addons'\n",
      "\n",
      "During handling of the above exception, another exception occurred:\n",
      "\n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\TFODCourse\\Tensorflow\\models\\research\\object_detection\\builders\\model_builder_tf2_test.py\", line 24, in <module>\n",
      "    from object_detection.builders import model_builder\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\model_builder.py\", line 70, in <module>\n",
      "    from object_detection.models import ssd_efficientnet_bifpn_feature_extractor as ssd_efficientnet_bifpn\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\models\\ssd_efficientnet_bifpn_feature_extractor.py\", line 38, in <module>\n",
      "    from official.vision.image_classification.efficientnet import efficientnet_model\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tf_models_official-2.11.3-py3.9.egg\\official\\vision\\__init__.py\", line 17, in <module>\n",
      "    from official.vision import configs\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tf_models_official-2.11.3-py3.9.egg\\official\\vision\\configs\\__init__.py\", line 19, in <module>\n",
      "    from official.vision.configs import common\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tf_models_official-2.11.3-py3.9.egg\\official\\vision\\configs\\common.py\", line 22, in <module>\n",
      "    from official.core import config_definitions as cfg\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tf_models_official-2.11.3-py3.9.egg\\official\\core\\__init__.py\", line 17, in <module>\n",
      "    from official.core import actions\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tf_models_official-2.11.3-py3.9.egg\\official\\core\\actions.py\", line 21, in <module>\n",
      "    import gin\n",
      "ModuleNotFoundError: No module named 'gin'\n"
     ]
    }
   ],
   "source": [
    "VERIFICATION_SCRIPT = os.path.join(paths['APIMODEL_PATH'], 'research', 'object_detection', 'builders', 'model_builder_tf2_test.py')\n",
    "# Verify Installation\n",
    "!python {VERIFICATION_SCRIPT}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: tensorflow in c:\\users\\manas\\anaconda3\\lib\\site-packages (2.11.0)\n",
      "Requirement already satisfied: tensorflow-intel==2.11.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow) (2.11.0)\n",
      "Requirement already satisfied: astunparse>=1.6.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (1.6.3)\n",
      "Requirement already satisfied: termcolor>=1.1.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (2.2.0)\n",
      "Requirement already satisfied: packaging in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (23.0)\n",
      "Requirement already satisfied: libclang>=13.0.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (15.0.6.1)\n",
      "Requirement already satisfied: google-pasta>=0.1.1 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (0.2.0)\n",
      "Requirement already satisfied: flatbuffers>=2.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (23.1.21)\n",
      "Requirement already satisfied: numpy>=1.20 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (1.24.2)\n",
      "Requirement already satisfied: keras<2.12,>=2.11.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (2.11.0)\n",
      "Requirement already satisfied: tensorflow-io-gcs-filesystem>=0.23.1 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (0.30.0)\n",
      "Requirement already satisfied: six>=1.12.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (1.16.0)\n",
      "Requirement already satisfied: opt-einsum>=2.3.2 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (3.3.0)\n",
      "Requirement already satisfied: typing-extensions>=3.6.6 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (4.3.0)\n",
      "Requirement already satisfied: protobuf<3.20,>=3.9.2 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (3.19.6)\n",
      "Requirement already satisfied: grpcio<2.0,>=1.24.3 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (1.51.1)\n",
      "Requirement already satisfied: absl-py>=1.0.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (1.4.0)\n",
      "Requirement already satisfied: tensorboard<2.12,>=2.11 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (2.11.2)\n",
      "Requirement already satisfied: tensorflow-estimator<2.12,>=2.11.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (2.11.0)\n",
      "Requirement already satisfied: setuptools in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (63.4.1)\n",
      "Requirement already satisfied: h5py>=2.9.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (3.7.0)\n",
      "Requirement already satisfied: gast<=0.4.0,>=0.2.1 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (0.4.0)\n",
      "Requirement already satisfied: wrapt>=1.11.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorflow-intel==2.11.0->tensorflow) (1.14.1)\n",
      "Requirement already satisfied: wheel<1.0,>=0.23.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from astunparse>=1.6.0->tensorflow-intel==2.11.0->tensorflow) (0.38.4)\n",
      "Requirement already satisfied: tensorboard-data-server<0.7.0,>=0.6.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (0.6.1)\n",
      "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (0.4.6)\n",
      "Requirement already satisfied: requests<3,>=2.21.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.28.1)\n",
      "Requirement already satisfied: werkzeug>=1.0.1 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.0.3)\n",
      "Requirement already satisfied: google-auth<3,>=1.6.3 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.16.0)\n",
      "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (1.8.1)\n",
      "Requirement already satisfied: markdown>=2.6.8 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (3.3.4)\n",
      "Requirement already satisfied: pyasn1-modules>=0.2.1 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from google-auth<3,>=1.6.3->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (0.2.8)\n",
      "Requirement already satisfied: rsa<5,>=3.1.4 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from google-auth<3,>=1.6.3->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (4.9)\n",
      "Requirement already satisfied: cachetools<6.0,>=2.0.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from google-auth<3,>=1.6.3->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (5.3.0)\n",
      "Requirement already satisfied: requests-oauthlib>=0.7.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (1.3.1)\n",
      "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (3.3)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2022.9.14)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (1.26.11)\n",
      "Requirement already satisfied: charset-normalizer<3,>=2 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (2.0.4)\n",
      "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (0.4.8)\n",
      "Requirement already satisfied: oauthlib>=3.0.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard<2.12,>=2.11->tensorflow-intel==2.11.0->tensorflow) (3.2.2)\n"
     ]
    }
   ],
   "source": [
    "!pip install tensorflow --upgrade"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: Skipping protobuf as it is not installed.\n",
      "WARNING: Skipping matplotlib as it is not installed.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting protobuf\n",
      "  Using cached protobuf-4.21.12-cp39-cp39-win_amd64.whl (527 kB)\n",
      "Collecting matplotlib\n",
      "  Using cached matplotlib-3.6.3-cp39-cp39-win_amd64.whl (7.2 MB)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from matplotlib) (0.11.0)\n",
      "Requirement already satisfied: packaging>=20.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from matplotlib) (23.0)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from matplotlib) (1.0.7)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from matplotlib) (4.25.0)\n",
      "Requirement already satisfied: numpy>=1.19 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from matplotlib) (1.24.2)\n",
      "Requirement already satisfied: pillow>=6.2.0 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from matplotlib) (9.2.0)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from matplotlib) (1.4.2)\n",
      "Requirement already satisfied: pyparsing>=2.2.1 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from matplotlib) (3.0.9)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from matplotlib) (2.8.2)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\manas\\anaconda3\\lib\\site-packages (from python-dateutil>=2.7->matplotlib) (1.16.0)\n",
      "Installing collected packages: protobuf, matplotlib\n",
      "Successfully installed matplotlib-3.6.3 protobuf-4.21.12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
      "tf-models-official 2.11.3 requires google-api-python-client>=1.6.7, which is not installed.\n",
      "tf-models-official 2.11.3 requires immutabledict, which is not installed.\n",
      "tf-models-official 2.11.3 requires kaggle>=1.3.9, which is not installed.\n",
      "tf-models-official 2.11.3 requires oauth2client, which is not installed.\n",
      "tf-models-official 2.11.3 requires opencv-python-headless, which is not installed.\n",
      "tf-models-official 2.11.3 requires py-cpuinfo>=3.3.0, which is not installed.\n",
      "tf-models-official 2.11.3 requires sentencepiece, which is not installed.\n",
      "tf-models-official 2.11.3 requires seqeval, which is not installed.\n",
      "tf-models-official 2.11.3 requires tensorflow-datasets, which is not installed.\n",
      "tf-models-official 2.11.3 requires tensorflow-hub>=0.6.0, which is not installed.\n",
      "tf-models-official 2.11.3 requires tensorflow-model-optimization>=0.4.1, which is not installed.\n",
      "tf-models-official 2.11.3 requires tensorflow-text~=2.11.0, which is not installed.\n",
      "apache-beam 2.45.0rc1 requires crcmod<2.0,>=1.7, which is not installed.\n",
      "apache-beam 2.45.0rc1 requires fastavro<2,>=0.23.6, which is not installed.\n",
      "apache-beam 2.45.0rc1 requires fasteners<1.0,>=0.3, which is not installed.\n",
      "apache-beam 2.45.0rc1 requires hdfs<3.0.0,>=2.1.0, which is not installed.\n",
      "apache-beam 2.45.0rc1 requires httplib2<0.21.0,>=0.8, which is not installed.\n",
      "apache-beam 2.45.0rc1 requires objsize<0.7.0,>=0.6.1, which is not installed.\n",
      "apache-beam 2.45.0rc1 requires orjson<4.0, which is not installed.\n",
      "apache-beam 2.45.0rc1 requires proto-plus<2,>=1.7.1, which is not installed.\n",
      "apache-beam 2.45.0rc1 requires pyarrow<10.0.0,>=0.15.1, which is not installed.\n",
      "apache-beam 2.45.0rc1 requires pydot<2,>=1.2.0, which is not installed.\n",
      "apache-beam 2.45.0rc1 requires pymongo<4.0.0,>=3.8.0, which is not installed.\n",
      "apache-beam 2.45.0rc1 requires zstandard<1,>=0.18.0, which is not installed.\n",
      "tensorflow-intel 2.11.0 requires protobuf<3.20,>=3.9.2, but you have protobuf 4.21.12 which is incompatible.\n",
      "tensorboard 2.11.2 requires protobuf<4,>=3.9.2, but you have protobuf 4.21.12 which is incompatible.\n",
      "object-detection 0.1 requires pyparsing==2.4.7, but you have pyparsing 3.0.9 which is incompatible.\n",
      "tf-models-official 2.11.3 requires pyyaml<6.0,>=5.1, but you have pyyaml 6.0 which is incompatible.\n",
      "apache-beam 2.45.0rc1 requires cloudpickle~=2.2.1, but you have cloudpickle 2.0.0 which is incompatible.\n",
      "apache-beam 2.45.0rc1 requires dill<0.3.2,>=0.3.1.1, but you have dill 0.3.4 which is incompatible.\n",
      "apache-beam 2.45.0rc1 requires numpy<1.23.0,>=1.14.3, but you have numpy 1.24.2 which is incompatible.\n",
      "apache-beam 2.45.0rc1 requires protobuf<4,>3.12.2, but you have protobuf 4.21.12 which is incompatible.\n"
     ]
    }
   ],
   "source": [
    "!pip uninstall protobuf matplotlib -y\n",
    "!pip install protobuf matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import object_detection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Package                       Version              Editable project location\n",
      "----------------------------- -------------------- -----------------------------------------------------------------------------------------------------\n",
      "absl-py                       1.4.0\n",
      "alabaster                     0.7.12\n",
      "anaconda-client               1.11.0\n",
      "anaconda-navigator            2.3.2\n",
      "anaconda-project              0.11.1\n",
      "anyio                         3.5.0\n",
      "apache-beam                   2.45.0rc1\n",
      "appdirs                       1.4.4\n",
      "argon2-cffi                   21.3.0\n",
      "argon2-cffi-bindings          21.2.0\n",
      "arrow                         1.2.2\n",
      "astroid                       2.11.7\n",
      "astropy                       5.1\n",
      "astunparse                    1.6.3\n",
      "atomicwrites                  1.4.0\n",
      "attrs                         21.4.0\n",
      "Automat                       20.2.0\n",
      "autopep8                      1.6.0\n",
      "avro-python3                  1.10.2\n",
      "Babel                         2.9.1\n",
      "backcall                      0.2.0\n",
      "backports.functools-lru-cache 1.6.4\n",
      "backports.tempfile            1.0\n",
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      "six                           1.16.0\n",
      "slim                          0.1                  c:\\users\\manas\\onedrive\\documents\\hacknotts\\hackathon\\tfod\\tfodcourse\\tensorflow\\models\\research\\slim\n",
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      "tf-models-official            2.11.3\n",
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      "tifffile                      2021.7.2\n",
      "tinycss                       0.4\n",
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      "toml                          0.10.2\n",
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      "tornado                       6.1\n",
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      "traitlets                     5.1.1\n",
      "Twisted                       22.2.0\n",
      "twisted-iocpsupport           1.0.2\n",
      "typing_extensions             4.3.0\n",
      "ujson                         5.4.0\n",
      "Unidecode                     1.2.0\n",
      "urllib3                       1.26.11\n",
      "w3lib                         1.21.0\n",
      "watchdog                      2.1.6\n",
      "wcwidth                       0.2.5\n",
      "webencodings                  0.5.1\n",
      "websocket-client              0.58.0\n",
      "Werkzeug                      2.0.3\n",
      "wget                          3.2\n",
      "wheel                         0.38.4\n",
      "widgetsnbextension            3.5.2\n",
      "win-inet-pton                 1.1.0\n",
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      "wincertstore                  0.2\n",
      "wrapt                         1.14.1\n",
      "xarray                        0.20.1\n",
      "xlrd                          2.0.1\n",
      "XlsxWriter                    3.0.3\n",
      "xlwings                       0.27.15\n",
      "yapf                          0.31.0\n",
      "zict                          2.1.0\n",
      "zipp                          3.8.0\n",
      "zope.interface                5.4.0\n"
     ]
    }
   ],
   "source": [
    "!pip list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "csofht2npfDE",
    "outputId": "ff5471b2-bed2-43f2-959c-327a706527b6"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        1 file(s) moved.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "x ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/\n",
      "x ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/checkpoint/\n",
      "x ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/checkpoint/ckpt-0.data-00000-of-00001\n",
      "x ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/checkpoint/checkpoint\n",
      "x ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/checkpoint/ckpt-0.index\n",
      "x ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/pipeline.config\n",
      "x ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/saved_model/\n",
      "x ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/saved_model/saved_model.pb\n",
      "x ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/saved_model/variables/\n",
      "x ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/saved_model/variables/variables.data-00000-of-00001\n",
      "x ssd_mobilenet_v2_fpnlite_320x320_coco17_tpu-8/saved_model/variables/variables.index\n"
     ]
    }
   ],
   "source": [
    "if os.name =='posix':\n",
    "    !wget {PRETRAINED_MODEL_URL}\n",
    "    !mv {PRETRAINED_MODEL_NAME+'.tar.gz'} {paths['PRETRAINED_MODEL_PATH']}\n",
    "    !cd {paths['PRETRAINED_MODEL_PATH']} && tar -zxvf {PRETRAINED_MODEL_NAME+'.tar.gz'}\n",
    "if os.name == 'nt':\n",
    "    wget.download(PRETRAINED_MODEL_URL)\n",
    "    !move {PRETRAINED_MODEL_NAME+'.tar.gz'} {paths['PRETRAINED_MODEL_PATH']}\n",
    "    !cd {paths['PRETRAINED_MODEL_PATH']} && tar -zxvf {PRETRAINED_MODEL_NAME+'.tar.gz'}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "M5KJTnkfpfDC"
   },
   "source": [
    "# 2. Create Label Map"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "p1BVDWo7pfDC"
   },
   "outputs": [],
   "source": [
    "labels = [{'name':'egg', 'id':1}, {'name':'chicken', 'id':2}, {'name':'milk', 'id':3}, {'name':'wheat', 'id':4}]\n",
    "\n",
    "with open(files['LABELMAP'], 'w') as f:\n",
    "    for label in labels:\n",
    "        f.write('item { \\n')\n",
    "        f.write('\\tname:\\'{}\\'\\n'.format(label['name']))\n",
    "        f.write('\\tid:{}\\n'.format(label['id']))\n",
    "        f.write('}\\n')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "C88zyVELpfDC"
   },
   "source": [
    "# 3. Create TF records"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "kvf5WccwrFGq",
    "outputId": "49902aeb-0bd7-4298-e1a0-5b4a64eb2064"
   },
   "outputs": [],
   "source": [
    "# OPTIONAL IF RUNNING ON COLAB\n",
    "ARCHIVE_FILES = os.path.join(paths['IMAGE_PATH'], 'archive.tar.gz')\n",
    "if os.path.exists(ARCHIVE_FILES):\n",
    "  !tar -zxvf {ARCHIVE_FILES}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "KWpb_BVUpfDD",
    "outputId": "56ce2a3f-3933-4ee6-8a9d-d5ec65f7d73c"
   },
   "outputs": [],
   "source": [
    "if not os.path.exists(files['TF_RECORD_SCRIPT']):\n",
    "    !git clone https://github.com/nicknochnack/GenerateTFRecord {paths['SCRIPTS_PATH']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "UPFToGZqpfDD",
    "outputId": "0ebb456f-aadc-4a1f-96e6-fbfec1923e1c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Successfully created the TFRecord file: Tensorflow\\workspace\\annotations\\train.record\n",
      "Successfully created the TFRecord file: Tensorflow\\workspace\\annotations\\test.record\n"
     ]
    }
   ],
   "source": [
    "!python {files['TF_RECORD_SCRIPT']} -x {os.path.join(paths['IMAGE_PATH'], 'train')} -l {files['LABELMAP']} -o {os.path.join(paths['ANNOTATION_PATH'], 'train.record')} \n",
    "!python {files['TF_RECORD_SCRIPT']} -x {os.path.join(paths['IMAGE_PATH'], 'test')} -l {files['LABELMAP']} -o {os.path.join(paths['ANNOTATION_PATH'], 'test.record')} "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "qT4QU7pLpfDE"
   },
   "source": [
    "# 4. Copy Model Config to Training Folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "cOjuTFbwpfDF"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        1 file(s) copied.\n"
     ]
    }
   ],
   "source": [
    "if os.name =='posix':\n",
    "    !cp {os.path.join(paths['PRETRAINED_MODEL_PATH'], PRETRAINED_MODEL_NAME, 'pipeline.config')} {os.path.join(paths['CHECKPOINT_PATH'])}\n",
    "if os.name == 'nt':\n",
    "    !copy {os.path.join(paths['PRETRAINED_MODEL_PATH'], PRETRAINED_MODEL_NAME, 'pipeline.config')} {os.path.join(paths['CHECKPOINT_PATH'])}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Ga8gpNslpfDF"
   },
   "source": [
    "# 5. Update Config For Transfer Learning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "id": "Z9hRrO_ppfDF"
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from object_detection.utils import config_util\n",
    "from object_detection.protos import pipeline_pb2\n",
    "from google.protobuf import text_format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "id": "c2A0mn4ipfDF"
   },
   "outputs": [],
   "source": [
    "config = config_util.get_configs_from_pipeline_file(files['PIPELINE_CONFIG'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "uQA13-afpfDF",
    "outputId": "907496a4-a39d-4b13-8c2c-e5978ecb1f10"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'model': ssd {\n",
       "   num_classes: 90\n",
       "   image_resizer {\n",
       "     fixed_shape_resizer {\n",
       "       height: 320\n",
       "       width: 320\n",
       "     }\n",
       "   }\n",
       "   feature_extractor {\n",
       "     type: \"ssd_mobilenet_v2_fpn_keras\"\n",
       "     depth_multiplier: 1.0\n",
       "     min_depth: 16\n",
       "     conv_hyperparams {\n",
       "       regularizer {\n",
       "         l2_regularizer {\n",
       "           weight: 3.9999998989515007e-05\n",
       "         }\n",
       "       }\n",
       "       initializer {\n",
       "         random_normal_initializer {\n",
       "           mean: 0.0\n",
       "           stddev: 0.009999999776482582\n",
       "         }\n",
       "       }\n",
       "       activation: RELU_6\n",
       "       batch_norm {\n",
       "         decay: 0.996999979019165\n",
       "         scale: true\n",
       "         epsilon: 0.0010000000474974513\n",
       "       }\n",
       "     }\n",
       "     use_depthwise: true\n",
       "     override_base_feature_extractor_hyperparams: true\n",
       "     fpn {\n",
       "       min_level: 3\n",
       "       max_level: 7\n",
       "       additional_layer_depth: 128\n",
       "     }\n",
       "   }\n",
       "   box_coder {\n",
       "     faster_rcnn_box_coder {\n",
       "       y_scale: 10.0\n",
       "       x_scale: 10.0\n",
       "       height_scale: 5.0\n",
       "       width_scale: 5.0\n",
       "     }\n",
       "   }\n",
       "   matcher {\n",
       "     argmax_matcher {\n",
       "       matched_threshold: 0.5\n",
       "       unmatched_threshold: 0.5\n",
       "       ignore_thresholds: false\n",
       "       negatives_lower_than_unmatched: true\n",
       "       force_match_for_each_row: true\n",
       "       use_matmul_gather: true\n",
       "     }\n",
       "   }\n",
       "   similarity_calculator {\n",
       "     iou_similarity {\n",
       "     }\n",
       "   }\n",
       "   box_predictor {\n",
       "     weight_shared_convolutional_box_predictor {\n",
       "       conv_hyperparams {\n",
       "         regularizer {\n",
       "           l2_regularizer {\n",
       "             weight: 3.9999998989515007e-05\n",
       "           }\n",
       "         }\n",
       "         initializer {\n",
       "           random_normal_initializer {\n",
       "             mean: 0.0\n",
       "             stddev: 0.009999999776482582\n",
       "           }\n",
       "         }\n",
       "         activation: RELU_6\n",
       "         batch_norm {\n",
       "           decay: 0.996999979019165\n",
       "           scale: true\n",
       "           epsilon: 0.0010000000474974513\n",
       "         }\n",
       "       }\n",
       "       depth: 128\n",
       "       num_layers_before_predictor: 4\n",
       "       kernel_size: 3\n",
       "       class_prediction_bias_init: -4.599999904632568\n",
       "       share_prediction_tower: true\n",
       "       use_depthwise: true\n",
       "     }\n",
       "   }\n",
       "   anchor_generator {\n",
       "     multiscale_anchor_generator {\n",
       "       min_level: 3\n",
       "       max_level: 7\n",
       "       anchor_scale: 4.0\n",
       "       aspect_ratios: 1.0\n",
       "       aspect_ratios: 2.0\n",
       "       aspect_ratios: 0.5\n",
       "       scales_per_octave: 2\n",
       "     }\n",
       "   }\n",
       "   post_processing {\n",
       "     batch_non_max_suppression {\n",
       "       score_threshold: 9.99999993922529e-09\n",
       "       iou_threshold: 0.6000000238418579\n",
       "       max_detections_per_class: 100\n",
       "       max_total_detections: 100\n",
       "       use_static_shapes: false\n",
       "     }\n",
       "     score_converter: SIGMOID\n",
       "   }\n",
       "   normalize_loss_by_num_matches: true\n",
       "   loss {\n",
       "     localization_loss {\n",
       "       weighted_smooth_l1 {\n",
       "       }\n",
       "     }\n",
       "     classification_loss {\n",
       "       weighted_sigmoid_focal {\n",
       "         gamma: 2.0\n",
       "         alpha: 0.25\n",
       "       }\n",
       "     }\n",
       "     classification_weight: 1.0\n",
       "     localization_weight: 1.0\n",
       "   }\n",
       "   encode_background_as_zeros: true\n",
       "   normalize_loc_loss_by_codesize: true\n",
       "   inplace_batchnorm_update: true\n",
       "   freeze_batchnorm: false\n",
       " },\n",
       " 'train_config': batch_size: 128\n",
       " data_augmentation_options {\n",
       "   random_horizontal_flip {\n",
       "   }\n",
       " }\n",
       " data_augmentation_options {\n",
       "   random_crop_image {\n",
       "     min_object_covered: 0.0\n",
       "     min_aspect_ratio: 0.75\n",
       "     max_aspect_ratio: 3.0\n",
       "     min_area: 0.75\n",
       "     max_area: 1.0\n",
       "     overlap_thresh: 0.0\n",
       "   }\n",
       " }\n",
       " sync_replicas: true\n",
       " optimizer {\n",
       "   momentum_optimizer {\n",
       "     learning_rate {\n",
       "       cosine_decay_learning_rate {\n",
       "         learning_rate_base: 0.07999999821186066\n",
       "         total_steps: 50000\n",
       "         warmup_learning_rate: 0.026666000485420227\n",
       "         warmup_steps: 1000\n",
       "       }\n",
       "     }\n",
       "     momentum_optimizer_value: 0.8999999761581421\n",
       "   }\n",
       "   use_moving_average: false\n",
       " }\n",
       " fine_tune_checkpoint: \"PATH_TO_BE_CONFIGURED\"\n",
       " num_steps: 50000\n",
       " startup_delay_steps: 0.0\n",
       " replicas_to_aggregate: 8\n",
       " max_number_of_boxes: 100\n",
       " unpad_groundtruth_tensors: false\n",
       " fine_tune_checkpoint_type: \"classification\"\n",
       " fine_tune_checkpoint_version: V2,\n",
       " 'train_input_config': label_map_path: \"PATH_TO_BE_CONFIGURED\"\n",
       " tf_record_input_reader {\n",
       "   input_path: \"PATH_TO_BE_CONFIGURED\"\n",
       " },\n",
       " 'eval_config': metrics_set: \"coco_detection_metrics\"\n",
       " use_moving_averages: false,\n",
       " 'eval_input_configs': [label_map_path: \"PATH_TO_BE_CONFIGURED\"\n",
       " shuffle: false\n",
       " num_epochs: 1\n",
       " tf_record_input_reader {\n",
       "   input_path: \"PATH_TO_BE_CONFIGURED\"\n",
       " }\n",
       " ],\n",
       " 'eval_input_config': label_map_path: \"PATH_TO_BE_CONFIGURED\"\n",
       " shuffle: false\n",
       " num_epochs: 1\n",
       " tf_record_input_reader {\n",
       "   input_path: \"PATH_TO_BE_CONFIGURED\"\n",
       " }}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "id": "9vK5lotDpfDF"
   },
   "outputs": [],
   "source": [
    "pipeline_config = pipeline_pb2.TrainEvalPipelineConfig()\n",
    "with tf.io.gfile.GFile(files['PIPELINE_CONFIG'], \"r\") as f:                                                                                                                                                                                                                     \n",
    "    proto_str = f.read()                                                                                                                                                                                                                                          \n",
    "    text_format.Merge(proto_str, pipeline_config)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "id": "rP43Ph0JpfDG"
   },
   "outputs": [],
   "source": [
    "pipeline_config.model.ssd.num_classes = len(labels)\n",
    "pipeline_config.train_config.batch_size = 4\n",
    "pipeline_config.train_config.fine_tune_checkpoint = os.path.join(paths['PRETRAINED_MODEL_PATH'], PRETRAINED_MODEL_NAME, 'checkpoint', 'ckpt-0')\n",
    "pipeline_config.train_config.fine_tune_checkpoint_type = \"detection\"\n",
    "pipeline_config.train_input_reader.label_map_path= files['LABELMAP']\n",
    "pipeline_config.train_input_reader.tf_record_input_reader.input_path[:] = [os.path.join(paths['ANNOTATION_PATH'], 'train.record')]\n",
    "pipeline_config.eval_input_reader[0].label_map_path = files['LABELMAP']\n",
    "pipeline_config.eval_input_reader[0].tf_record_input_reader.input_path[:] = [os.path.join(paths['ANNOTATION_PATH'], 'test.record')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "id": "oJvfgwWqpfDG"
   },
   "outputs": [],
   "source": [
    "config_text = text_format.MessageToString(pipeline_config)                                                                                                                                                                                                        \n",
    "with tf.io.gfile.GFile(files['PIPELINE_CONFIG'], \"wb\") as f:                                                                                                                                                                                                                     \n",
    "    f.write(config_text)   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "Zr3ON7xMpfDG"
   },
   "source": [
    "# 6. Train the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "id": "B-Y2UQmQpfDG"
   },
   "outputs": [],
   "source": [
    "TRAINING_SCRIPT = os.path.join(paths['APIMODEL_PATH'], 'research', 'object_detection', 'model_main_tf2.py')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "id": "jMP2XDfQpfDH"
   },
   "outputs": [],
   "source": [
    "command = \"python {} --model_dir={} --pipeline_config_path={} --num_train_steps=2000\".format(TRAINING_SCRIPT, paths['CHECKPOINT_PATH'],files['PIPELINE_CONFIG'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "A4OXXi-ApfDH",
    "outputId": "117a0e83-012b-466e-b7a6-ccaa349ac5ab"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "python Tensorflow\\models\\research\\object_detection\\model_main_tf2.py --model_dir=Tensorflow\\workspace\\models\\my_ssd_mobnet --pipeline_config_path=Tensorflow\\workspace\\models\\my_ssd_mobnet\\pipeline.config --num_train_steps=2000\n"
     ]
    }
   ],
   "source": [
    "print(command)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "i3ZsJR-qpfDH",
    "outputId": "cabec5e1-45e6-4f2f-d9cf-297d9c1d0225"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "^C\n"
     ]
    }
   ],
   "source": [
    "!{command}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4_YRZu7npfDH"
   },
   "source": [
    "# 7. Evaluate the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "id": "80L7-fdPpfDH"
   },
   "outputs": [],
   "source": [
    "command = \"python {} --model_dir={} --pipeline_config_path={} --checkpoint_dir={}\".format(TRAINING_SCRIPT, paths['CHECKPOINT_PATH'],files['PIPELINE_CONFIG'], paths['CHECKPOINT_PATH'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "lYsgEPx9pfDH",
    "outputId": "8632d48b-91d2-45d9-bcb8-c1b172bf6eed"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "python Tensorflow\\models\\research\\object_detection\\model_main_tf2.py --model_dir=Tensorflow\\workspace\\models\\my_ssd_mobnet --pipeline_config_path=Tensorflow\\workspace\\models\\my_ssd_mobnet\\pipeline.config --checkpoint_dir=Tensorflow\\workspace\\models\\my_ssd_mobnet\n"
     ]
    }
   ],
   "source": [
    "print(command)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "id": "lqTV2jGBpfDH"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-02-12 10:27:46.325167: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX AVX2\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "WARNING:tensorflow:There are non-GPU devices in `tf.distribute.Strategy`, not using nccl allreduce.\n",
      "W0212 10:27:46.327489 11208 cross_device_ops.py:1387] There are non-GPU devices in `tf.distribute.Strategy`, not using nccl allreduce.\n",
      "INFO:tensorflow:Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:CPU:0',)\n",
      "I0212 10:27:46.377713 11208 mirrored_strategy.py:374] Using MirroredStrategy with devices ('/job:localhost/replica:0/task:0/device:CPU:0',)\n",
      "INFO:tensorflow:Maybe overwriting train_steps: 2000\n",
      "I0212 10:27:46.386711 11208 config_util.py:552] Maybe overwriting train_steps: 2000\n",
      "INFO:tensorflow:Maybe overwriting use_bfloat16: False\n",
      "I0212 10:27:46.386711 11208 config_util.py:552] Maybe overwriting use_bfloat16: False\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\model_lib_v2.py:563: StrategyBase.experimental_distribute_datasets_from_function (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "rename to distribute_datasets_from_function\n",
      "W0212 10:27:46.462898 11208 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\model_lib_v2.py:563: StrategyBase.experimental_distribute_datasets_from_function (from tensorflow.python.distribute.distribute_lib) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "rename to distribute_datasets_from_function\n",
      "INFO:tensorflow:Reading unweighted datasets: ['Tensorflow\\\\workspace\\\\annotations\\\\train.record']\n",
      "I0212 10:27:46.488902 11208 dataset_builder.py:162] Reading unweighted datasets: ['Tensorflow\\\\workspace\\\\annotations\\\\train.record']\n",
      "INFO:tensorflow:Reading record datasets for input file: ['Tensorflow\\\\workspace\\\\annotations\\\\train.record']\n",
      "I0212 10:27:46.490215 11208 dataset_builder.py:79] Reading record datasets for input file: ['Tensorflow\\\\workspace\\\\annotations\\\\train.record']\n",
      "INFO:tensorflow:Number of filenames to read: 1\n",
      "I0212 10:27:46.490215 11208 dataset_builder.py:80] Number of filenames to read: 1\n",
      "WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.\n",
      "W0212 10:27:46.490215 11208 dataset_builder.py:86] num_readers has been reduced to 1 to match input file shards.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:100: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`.\n",
      "W0212 10:27:46.505578 11208 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:100: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:235: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.map()\n",
      "W0212 10:27:46.563251 11208 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:235: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.map()\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\pyct\\static_analysis\\liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.\n",
      "Instructions for updating:\n",
      "Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089\n",
      "W0212 10:27:47.922299 11208 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\pyct\\static_analysis\\liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.\n",
      "Instructions for updating:\n",
      "Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.\n",
      "W0212 10:28:04.413556 11208 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "`seed2` arg is deprecated.Use sample_distorted_bounding_box_v2 instead.\n",
      "W0212 10:28:12.590415 11208 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: sample_distorted_bounding_box (from tensorflow.python.ops.image_ops_impl) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "`seed2` arg is deprecated.Use sample_distorted_bounding_box_v2 instead.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "W0212 10:28:17.374338 11208 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "2023-02-12 10:28:24.673349: W tensorflow/core/framework/dataset.cc:769] Input of GeneratorDatasetOp::Dataset will not be optimized because the dataset does not implement the AsGraphDefInternal() method needed to apply optimizations.\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\keras\\backend.py:451: UserWarning: `tf.keras.backend.set_learning_phase` is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the `training` argument of the `__call__` method of your layer or model.\n",
      "  warnings.warn(\n",
      "2023-02-12 10:29:32.265497: W tensorflow/core/framework/dataset.cc:769] Input of GeneratorDatasetOp::Dataset will not be optimized because the dataset does not implement the AsGraphDefInternal() method needed to apply optimizations.\n",
      "WARNING:tensorflow:Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.\n",
      "W0212 10:29:32.710034 11208 checkpoint.py:205] Detecting that an object or model or tf.train.Checkpoint is being deleted with unrestored values. See the following logs for the specific values in question. To silence these warnings, use `status.expect_partial()`. See https://www.tensorflow.org/api_docs/python/tf/train/Checkpoint#restorefor details about the status object returned by the restore function.\n",
      "WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer.iter\n",
      "W0212 10:29:32.710034 11208 checkpoint.py:214] Value in checkpoint could not be found in the restored object: (root).optimizer.iter\n",
      "WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer.decay\n",
      "W0212 10:29:32.710034 11208 checkpoint.py:214] Value in checkpoint could not be found in the restored object: (root).optimizer.decay\n",
      "WARNING:tensorflow:Value in checkpoint could not be found in the restored object: (root).optimizer.momentum\n",
      "W0212 10:29:32.710034 11208 checkpoint.py:214] Value in checkpoint could not be found in the restored object: (root).optimizer.momentum\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Forced number of epochs for all eval validations to be 1.\n",
      "W0212 10:27:59.342094 11588 model_lib_v2.py:1089] Forced number of epochs for all eval validations to be 1.\n",
      "INFO:tensorflow:Maybe overwriting sample_1_of_n_eval_examples: None\n",
      "I0212 10:27:59.342094 11588 config_util.py:552] Maybe overwriting sample_1_of_n_eval_examples: None\n",
      "INFO:tensorflow:Maybe overwriting use_bfloat16: False\n",
      "I0212 10:27:59.342094 11588 config_util.py:552] Maybe overwriting use_bfloat16: False\n",
      "INFO:tensorflow:Maybe overwriting eval_num_epochs: 1\n",
      "I0212 10:27:59.342094 11588 config_util.py:552] Maybe overwriting eval_num_epochs: 1\n",
      "WARNING:tensorflow:Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1.\n",
      "W0212 10:27:59.342094 11588 model_lib_v2.py:1106] Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1.\n",
      "2023-02-12 10:27:59.354622: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX AVX2\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "INFO:tensorflow:Reading unweighted datasets: ['Tensorflow\\\\workspace\\\\annotations\\\\test.record']\n",
      "I0212 10:27:59.451467 11588 dataset_builder.py:162] Reading unweighted datasets: ['Tensorflow\\\\workspace\\\\annotations\\\\test.record']\n",
      "INFO:tensorflow:Reading record datasets for input file: ['Tensorflow\\\\workspace\\\\annotations\\\\test.record']\n",
      "I0212 10:27:59.451467 11588 dataset_builder.py:79] Reading record datasets for input file: ['Tensorflow\\\\workspace\\\\annotations\\\\test.record']\n",
      "INFO:tensorflow:Number of filenames to read: 1\n",
      "I0212 10:27:59.451467 11588 dataset_builder.py:80] Number of filenames to read: 1\n",
      "WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.\n",
      "W0212 10:27:59.451467 11588 dataset_builder.py:86] num_readers has been reduced to 1 to match input file shards.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:100: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`.\n",
      "W0212 10:27:59.467095 11588 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:100: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:235: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.map()\n",
      "W0212 10:27:59.513970 11588 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:235: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.map()\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\pyct\\static_analysis\\liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.\n",
      "Instructions for updating:\n",
      "Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089\n",
      "W0212 10:28:01.187666 11588 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\pyct\\static_analysis\\liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.\n",
      "Instructions for updating:\n",
      "Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.\n",
      "W0212 10:28:11.011431 11588 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "W0212 10:28:13.982747 11588 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "INFO:tensorflow:Waiting for new checkpoint at Tensorflow\\workspace\\models\\my_ssd_mobnet\n",
      "I0212 10:28:21.096643 11588 checkpoint_utils.py:140] Waiting for new checkpoint at Tensorflow\\workspace\\models\\my_ssd_mobnet\n",
      "INFO:tensorflow:Found new checkpoint at Tensorflow\\workspace\\models\\my_ssd_mobnet\\ckpt-5\n",
      "I0212 10:28:21.096643 11588 checkpoint_utils.py:149] Found new checkpoint at Tensorflow\\workspace\\models\\my_ssd_mobnet\\ckpt-5\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\keras\\backend.py:451: UserWarning: `tf.keras.backend.set_learning_phase` is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the `training` argument of the `__call__` method of your layer or model.\n",
      "  warnings.warn(\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_int64 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "W0212 10:29:35.878172 11588 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_int64 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "INFO:tensorflow:Finished eval step 0\n",
      "I0212 10:29:35.940672 11588 model_lib_v2.py:966] Finished eval step 0\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\impl\\api.py:459: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "tf.py_func is deprecated in TF V2. Instead, there are two\n",
      "    options available in V2.\n",
      "    - tf.py_function takes a python function which manipulates tf eager\n",
      "    tensors instead of numpy arrays. It's easy to convert a tf eager tensor to\n",
      "    an ndarray (just call tensor.numpy()) but having access to eager tensors\n",
      "    means `tf.py_function`s can use accelerators such as GPUs as well as\n",
      "    being differentiable using a gradient tape.\n",
      "    - tf.numpy_function maintains the semantics of the deprecated tf.py_func\n",
      "    (it is not differentiable, and manipulates numpy arrays). It drops the\n",
      "    stateful argument making all functions stateful.\n",
      "    \n",
      "W0212 10:29:36.362543 11588 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\impl\\api.py:459: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "tf.py_func is deprecated in TF V2. Instead, there are two\n",
      "    options available in V2.\n",
      "    - tf.py_function takes a python function which manipulates tf eager\n",
      "    tensors instead of numpy arrays. It's easy to convert a tf eager tensor to\n",
      "    an ndarray (just call tensor.numpy()) but having access to eager tensors\n",
      "    means `tf.py_function`s can use accelerators such as GPUs as well as\n",
      "    being differentiable using a gradient tape.\n",
      "    - tf.numpy_function maintains the semantics of the deprecated tf.py_func\n",
      "    (it is not differentiable, and manipulates numpy arrays). It drops the\n",
      "    stateful argument making all functions stateful.\n",
      "    \n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\TFODCourse\\Tensorflow\\models\\research\\object_detection\\model_main_tf2.py\", line 114, in <module>\n",
      "    tf.compat.v1.app.run()\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\platform\\app.py\", line 36, in run\n",
      "    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\absl\\app.py\", line 308, in run\n",
      "    _run_main(main, args)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\absl\\app.py\", line 254, in _run_main\n",
      "    sys.exit(main(argv))\n",
      "  File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\TFODCourse\\Tensorflow\\models\\research\\object_detection\\model_main_tf2.py\", line 81, in main\n",
      "    model_lib_v2.eval_continuously(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\model_lib_v2.py\", line 1158, in eval_continuously\n",
      "    eager_eval_loop(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\model_lib_v2.py\", line 970, in eager_eval_loop\n",
      "    sbys_image_list = vutils.draw_side_by_side_evaluation_image(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 735, in draw_side_by_side_evaluation_image\n",
      "    images_with_groundtruth = draw_bounding_boxes_on_image_tensors(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 621, in draw_bounding_boxes_on_image_tensors\n",
      "    images = tf.map_fn(draw_boxes, elems, dtype=tf.uint8, back_prop=False)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\deprecation.py\", line 561, in new_func\n",
      "    return func(*args, **kwargs)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\map_fn.py\", line 498, in map_fn\n",
      "    _, r_a = control_flow_ops.while_loop(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 2765, in while_loop\n",
      "    loop_vars = body(*loop_vars)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 2756, in <lambda>\n",
      "    body = lambda i, lv: (i + 1, orig_body(*lv))\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\map_fn.py\", line 488, in compute\n",
      "    result_value = autographed_fn(elems_value)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\impl\\api.py\", line 692, in wrapper\n",
      "    raise e.ag_error_metadata.to_exception(e)\n",
      "tensorflow.python.autograph.impl.api.StagingError: in user code:\n",
      "\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 617, in draw_boxes  *\n",
      "        image_with_boxes = tf.py_func(visualize_boxes_fn, image_and_detections[2:],\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 397, in visualization_py_func_fn\n",
      "        return visualize_boxes_and_labels_on_image_array(\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 1250, in visualize_boxes_and_labels_on_image_array\n",
      "        draw_bounding_box_on_image_array(\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 160, in draw_bounding_box_on_image_array\n",
      "        draw_bounding_box_on_image(image_pil, ymin, xmin, ymax, xmax, color,\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 212, in draw_bounding_box_on_image\n",
      "        font = ImageFont.truetype('arial.ttf', 24)\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\", line 959, in truetype\n",
      "        return freetype(font)\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\", line 956, in freetype\n",
      "        return FreeTypeFont(font, size, index, encoding, layout_engine)\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\", line 219, in __init__\n",
      "        if core.HAVE_RAQM:\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\", line 58, in __getattr__\n",
      "        raise ImportError(\"The _imagingft C module is not installed\")\n",
      "\n",
      "    ImportError: The _imagingft C module is not installed\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Forced number of epochs for all eval validations to be 1.\n",
      "W0212 10:28:01.294160  9868 model_lib_v2.py:1089] Forced number of epochs for all eval validations to be 1.\n",
      "INFO:tensorflow:Maybe overwriting sample_1_of_n_eval_examples: None\n",
      "I0212 10:28:01.295161  9868 config_util.py:552] Maybe overwriting sample_1_of_n_eval_examples: None\n",
      "INFO:tensorflow:Maybe overwriting use_bfloat16: False\n",
      "I0212 10:28:01.295161  9868 config_util.py:552] Maybe overwriting use_bfloat16: False\n",
      "INFO:tensorflow:Maybe overwriting eval_num_epochs: 1\n",
      "I0212 10:28:01.295161  9868 config_util.py:552] Maybe overwriting eval_num_epochs: 1\n",
      "WARNING:tensorflow:Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1.\n",
      "W0212 10:28:01.295161  9868 model_lib_v2.py:1106] Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1.\n",
      "2023-02-12 10:28:01.306511: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX AVX2\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "INFO:tensorflow:Reading unweighted datasets: ['Tensorflow\\\\workspace\\\\annotations\\\\test.record']\n",
      "I0212 10:28:01.427879  9868 dataset_builder.py:162] Reading unweighted datasets: ['Tensorflow\\\\workspace\\\\annotations\\\\test.record']\n",
      "INFO:tensorflow:Reading record datasets for input file: ['Tensorflow\\\\workspace\\\\annotations\\\\test.record']\n",
      "I0212 10:28:01.427879  9868 dataset_builder.py:79] Reading record datasets for input file: ['Tensorflow\\\\workspace\\\\annotations\\\\test.record']\n",
      "INFO:tensorflow:Number of filenames to read: 1\n",
      "I0212 10:28:01.428876  9868 dataset_builder.py:80] Number of filenames to read: 1\n",
      "WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.\n",
      "W0212 10:28:01.428876  9868 dataset_builder.py:86] num_readers has been reduced to 1 to match input file shards.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:100: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`.\n",
      "W0212 10:28:01.438878  9868 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:100: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:235: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.map()\n",
      "W0212 10:28:01.489877  9868 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:235: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.map()\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\pyct\\static_analysis\\liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.\n",
      "Instructions for updating:\n",
      "Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089\n",
      "W0212 10:28:03.253951  9868 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\pyct\\static_analysis\\liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.\n",
      "Instructions for updating:\n",
      "Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.\n",
      "W0212 10:28:12.809163  9868 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "W0212 10:28:15.639825  9868 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "INFO:tensorflow:Waiting for new checkpoint at Tensorflow\\workspace\\models\\my_ssd_mobnet\n",
      "I0212 10:28:22.910591  9868 checkpoint_utils.py:140] Waiting for new checkpoint at Tensorflow\\workspace\\models\\my_ssd_mobnet\n",
      "INFO:tensorflow:Found new checkpoint at Tensorflow\\workspace\\models\\my_ssd_mobnet\\ckpt-5\n",
      "I0212 10:28:22.926218  9868 checkpoint_utils.py:149] Found new checkpoint at Tensorflow\\workspace\\models\\my_ssd_mobnet\\ckpt-5\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\keras\\backend.py:451: UserWarning: `tf.keras.backend.set_learning_phase` is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the `training` argument of the `__call__` method of your layer or model.\n",
      "  warnings.warn(\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_int64 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "W0212 10:29:37.854366  9868 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_int64 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "INFO:tensorflow:Finished eval step 0\n",
      "I0212 10:29:37.928322  9868 model_lib_v2.py:966] Finished eval step 0\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\impl\\api.py:459: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "tf.py_func is deprecated in TF V2. Instead, there are two\n",
      "    options available in V2.\n",
      "    - tf.py_function takes a python function which manipulates tf eager\n",
      "    tensors instead of numpy arrays. It's easy to convert a tf eager tensor to\n",
      "    an ndarray (just call tensor.numpy()) but having access to eager tensors\n",
      "    means `tf.py_function`s can use accelerators such as GPUs as well as\n",
      "    being differentiable using a gradient tape.\n",
      "    - tf.numpy_function maintains the semantics of the deprecated tf.py_func\n",
      "    (it is not differentiable, and manipulates numpy arrays). It drops the\n",
      "    stateful argument making all functions stateful.\n",
      "    \n",
      "W0212 10:29:38.382421  9868 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\impl\\api.py:459: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "tf.py_func is deprecated in TF V2. Instead, there are two\n",
      "    options available in V2.\n",
      "    - tf.py_function takes a python function which manipulates tf eager\n",
      "    tensors instead of numpy arrays. It's easy to convert a tf eager tensor to\n",
      "    an ndarray (just call tensor.numpy()) but having access to eager tensors\n",
      "    means `tf.py_function`s can use accelerators such as GPUs as well as\n",
      "    being differentiable using a gradient tape.\n",
      "    - tf.numpy_function maintains the semantics of the deprecated tf.py_func\n",
      "    (it is not differentiable, and manipulates numpy arrays). It drops the\n",
      "    stateful argument making all functions stateful.\n",
      "    \n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\TFODCourse\\Tensorflow\\models\\research\\object_detection\\model_main_tf2.py\", line 114, in <module>\n",
      "    tf.compat.v1.app.run()\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\platform\\app.py\", line 36, in run\n",
      "    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\absl\\app.py\", line 308, in run\n",
      "    _run_main(main, args)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\absl\\app.py\", line 254, in _run_main\n",
      "    sys.exit(main(argv))\n",
      "  File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\TFODCourse\\Tensorflow\\models\\research\\object_detection\\model_main_tf2.py\", line 81, in main\n",
      "    model_lib_v2.eval_continuously(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\model_lib_v2.py\", line 1158, in eval_continuously\n",
      "    eager_eval_loop(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\model_lib_v2.py\", line 970, in eager_eval_loop\n",
      "    sbys_image_list = vutils.draw_side_by_side_evaluation_image(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 735, in draw_side_by_side_evaluation_image\n",
      "    images_with_groundtruth = draw_bounding_boxes_on_image_tensors(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 621, in draw_bounding_boxes_on_image_tensors\n",
      "    images = tf.map_fn(draw_boxes, elems, dtype=tf.uint8, back_prop=False)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\deprecation.py\", line 561, in new_func\n",
      "    return func(*args, **kwargs)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\map_fn.py\", line 498, in map_fn\n",
      "    _, r_a = control_flow_ops.while_loop(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 2765, in while_loop\n",
      "    loop_vars = body(*loop_vars)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 2756, in <lambda>\n",
      "    body = lambda i, lv: (i + 1, orig_body(*lv))\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\map_fn.py\", line 488, in compute\n",
      "    result_value = autographed_fn(elems_value)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\impl\\api.py\", line 692, in wrapper\n",
      "    raise e.ag_error_metadata.to_exception(e)\n",
      "tensorflow.python.autograph.impl.api.StagingError: in user code:\n",
      "\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 617, in draw_boxes  *\n",
      "        image_with_boxes = tf.py_func(visualize_boxes_fn, image_and_detections[2:],\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 397, in visualization_py_func_fn\n",
      "        return visualize_boxes_and_labels_on_image_array(\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 1250, in visualize_boxes_and_labels_on_image_array\n",
      "        draw_bounding_box_on_image_array(\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 160, in draw_bounding_box_on_image_array\n",
      "        draw_bounding_box_on_image(image_pil, ymin, xmin, ymax, xmax, color,\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 212, in draw_bounding_box_on_image\n",
      "        font = ImageFont.truetype('arial.ttf', 24)\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\", line 959, in truetype\n",
      "        return freetype(font)\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\", line 956, in freetype\n",
      "        return FreeTypeFont(font, size, index, encoding, layout_engine)\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\", line 219, in __init__\n",
      "        if core.HAVE_RAQM:\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\", line 58, in __getattr__\n",
      "        raise ImportError(\"The _imagingft C module is not installed\")\n",
      "\n",
      "    ImportError: The _imagingft C module is not installed\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:Forced number of epochs for all eval validations to be 1.\n",
      "W0212 10:28:07.948508 11468 model_lib_v2.py:1089] Forced number of epochs for all eval validations to be 1.\n",
      "INFO:tensorflow:Maybe overwriting sample_1_of_n_eval_examples: None\n",
      "I0212 10:28:07.948508 11468 config_util.py:552] Maybe overwriting sample_1_of_n_eval_examples: None\n",
      "INFO:tensorflow:Maybe overwriting use_bfloat16: False\n",
      "I0212 10:28:07.948508 11468 config_util.py:552] Maybe overwriting use_bfloat16: False\n",
      "INFO:tensorflow:Maybe overwriting eval_num_epochs: 1\n",
      "I0212 10:28:07.948508 11468 config_util.py:552] Maybe overwriting eval_num_epochs: 1\n",
      "WARNING:tensorflow:Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1.\n",
      "W0212 10:28:07.948508 11468 model_lib_v2.py:1106] Expected number of evaluation epochs is 1, but instead encountered `eval_on_train_input_config.num_epochs` = 0. Overwriting `num_epochs` to 1.\n",
      "2023-02-12 10:28:07.969508: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX AVX2\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "INFO:tensorflow:Reading unweighted datasets: ['Tensorflow\\\\workspace\\\\annotations\\\\test.record']\n",
      "I0212 10:28:08.088047 11468 dataset_builder.py:162] Reading unweighted datasets: ['Tensorflow\\\\workspace\\\\annotations\\\\test.record']\n",
      "INFO:tensorflow:Reading record datasets for input file: ['Tensorflow\\\\workspace\\\\annotations\\\\test.record']\n",
      "I0212 10:28:08.088047 11468 dataset_builder.py:79] Reading record datasets for input file: ['Tensorflow\\\\workspace\\\\annotations\\\\test.record']\n",
      "INFO:tensorflow:Number of filenames to read: 1\n",
      "I0212 10:28:08.088047 11468 dataset_builder.py:80] Number of filenames to read: 1\n",
      "WARNING:tensorflow:num_readers has been reduced to 1 to match input file shards.\n",
      "W0212 10:28:08.088047 11468 dataset_builder.py:86] num_readers has been reduced to 1 to match input file shards.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:100: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`.\n",
      "W0212 10:28:08.088047 11468 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:100: parallel_interleave (from tensorflow.python.data.experimental.ops.interleave_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.interleave(map_func, cycle_length, block_length, num_parallel_calls=tf.data.AUTOTUNE)` instead. If sloppy execution is desired, use `tf.data.Options.deterministic`.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:235: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.map()\n",
      "W0212 10:28:08.134918 11468 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\builders\\dataset_builder.py:235: DatasetV1.map_with_legacy_function (from tensorflow.python.data.ops.dataset_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.data.Dataset.map()\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\pyct\\static_analysis\\liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.\n",
      "Instructions for updating:\n",
      "Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089\n",
      "W0212 10:28:09.744718 11468 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\pyct\\static_analysis\\liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.\n",
      "Instructions for updating:\n",
      "Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.\n",
      "W0212 10:28:19.282519 11468 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: sparse_to_dense (from tensorflow.python.ops.sparse_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Create a `tf.sparse.SparseTensor` and use `tf.sparse.to_dense` instead.\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "W0212 10:28:22.175354 11468 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_float (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "INFO:tensorflow:Waiting for new checkpoint at Tensorflow\\workspace\\models\\my_ssd_mobnet\n",
      "I0212 10:28:30.719933 11468 checkpoint_utils.py:140] Waiting for new checkpoint at Tensorflow\\workspace\\models\\my_ssd_mobnet\n",
      "INFO:tensorflow:Found new checkpoint at Tensorflow\\workspace\\models\\my_ssd_mobnet\\ckpt-5\n",
      "I0212 10:28:30.719933 11468 checkpoint_utils.py:149] Found new checkpoint at Tensorflow\\workspace\\models\\my_ssd_mobnet\\ckpt-5\n",
      "C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\keras\\backend.py:451: UserWarning: `tf.keras.backend.set_learning_phase` is deprecated and will be removed after 2020-10-11. To update it, simply pass a True/False value to the `training` argument of the `__call__` method of your layer or model.\n",
      "  warnings.warn(\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_int64 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "W0212 10:29:45.028767 11468 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\dispatch.py:1176: to_int64 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use `tf.cast` instead.\n",
      "INFO:tensorflow:Finished eval step 0\n",
      "I0212 10:29:45.091264 11468 model_lib_v2.py:966] Finished eval step 0\n",
      "WARNING:tensorflow:From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\impl\\api.py:459: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "tf.py_func is deprecated in TF V2. Instead, there are two\n",
      "    options available in V2.\n",
      "    - tf.py_function takes a python function which manipulates tf eager\n",
      "    tensors instead of numpy arrays. It's easy to convert a tf eager tensor to\n",
      "    an ndarray (just call tensor.numpy()) but having access to eager tensors\n",
      "    means `tf.py_function`s can use accelerators such as GPUs as well as\n",
      "    being differentiable using a gradient tape.\n",
      "    - tf.numpy_function maintains the semantics of the deprecated tf.py_func\n",
      "    (it is not differentiable, and manipulates numpy arrays). It drops the\n",
      "    stateful argument making all functions stateful.\n",
      "    \n",
      "W0212 10:29:45.443616 11468 deprecation.py:350] From C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\impl\\api.py:459: py_func (from tensorflow.python.ops.script_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "tf.py_func is deprecated in TF V2. Instead, there are two\n",
      "    options available in V2.\n",
      "    - tf.py_function takes a python function which manipulates tf eager\n",
      "    tensors instead of numpy arrays. It's easy to convert a tf eager tensor to\n",
      "    an ndarray (just call tensor.numpy()) but having access to eager tensors\n",
      "    means `tf.py_function`s can use accelerators such as GPUs as well as\n",
      "    being differentiable using a gradient tape.\n",
      "    - tf.numpy_function maintains the semantics of the deprecated tf.py_func\n",
      "    (it is not differentiable, and manipulates numpy arrays). It drops the\n",
      "    stateful argument making all functions stateful.\n",
      "    \n",
      "Traceback (most recent call last):\n",
      "  File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\TFODCourse\\Tensorflow\\models\\research\\object_detection\\model_main_tf2.py\", line 114, in <module>\n",
      "    tf.compat.v1.app.run()\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\platform\\app.py\", line 36, in run\n",
      "    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\absl\\app.py\", line 308, in run\n",
      "    _run_main(main, args)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\absl\\app.py\", line 254, in _run_main\n",
      "    sys.exit(main(argv))\n",
      "  File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\TFODCourse\\Tensorflow\\models\\research\\object_detection\\model_main_tf2.py\", line 81, in main\n",
      "    model_lib_v2.eval_continuously(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\model_lib_v2.py\", line 1158, in eval_continuously\n",
      "    eager_eval_loop(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\model_lib_v2.py\", line 970, in eager_eval_loop\n",
      "    sbys_image_list = vutils.draw_side_by_side_evaluation_image(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 735, in draw_side_by_side_evaluation_image\n",
      "    images_with_groundtruth = draw_bounding_boxes_on_image_tensors(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 621, in draw_bounding_boxes_on_image_tensors\n",
      "    images = tf.map_fn(draw_boxes, elems, dtype=tf.uint8, back_prop=False)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\util\\deprecation.py\", line 561, in new_func\n",
      "    return func(*args, **kwargs)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\map_fn.py\", line 498, in map_fn\n",
      "    _, r_a = control_flow_ops.while_loop(\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 2765, in while_loop\n",
      "    loop_vars = body(*loop_vars)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\control_flow_ops.py\", line 2756, in <lambda>\n",
      "    body = lambda i, lv: (i + 1, orig_body(*lv))\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\ops\\map_fn.py\", line 488, in compute\n",
      "    result_value = autographed_fn(elems_value)\n",
      "  File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\tensorflow\\python\\autograph\\impl\\api.py\", line 692, in wrapper\n",
      "    raise e.ag_error_metadata.to_exception(e)\n",
      "tensorflow.python.autograph.impl.api.StagingError: in user code:\n",
      "\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 617, in draw_boxes  *\n",
      "        image_with_boxes = tf.py_func(visualize_boxes_fn, image_and_detections[2:],\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 397, in visualization_py_func_fn\n",
      "        return visualize_boxes_and_labels_on_image_array(\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 1250, in visualize_boxes_and_labels_on_image_array\n",
      "        draw_bounding_box_on_image_array(\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 160, in draw_bounding_box_on_image_array\n",
      "        draw_bounding_box_on_image(image_pil, ymin, xmin, ymax, xmax, color,\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\visualization_utils.py\", line 212, in draw_bounding_box_on_image\n",
      "        font = ImageFont.truetype('arial.ttf', 24)\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\", line 959, in truetype\n",
      "        return freetype(font)\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\", line 956, in freetype\n",
      "        return FreeTypeFont(font, size, index, encoding, layout_engine)\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\", line 219, in __init__\n",
      "        if core.HAVE_RAQM:\n",
      "    File \"C:\\Users\\Manas\\anaconda3\\lib\\site-packages\\PIL\\ImageFont.py\", line 58, in __getattr__\n",
      "        raise ImportError(\"The _imagingft C module is not installed\")\n",
      "\n",
      "    ImportError: The _imagingft C module is not installed\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!{command}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "orvRk02UpfDI"
   },
   "source": [
    "# 8. Load Train Model From Checkpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "id": "8TYk4_oIpfDI"
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import os\n",
    "\n",
    "from object_detection.utils import label_map_util\n",
    "from object_detection.utils import config_util\n",
    "from object_detection.utils import visualization_utils as viz_utils\n",
    "from object_detection.builders import model_builder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {
    "id": "tDnQg-cYpfDI"
   },
   "outputs": [],
   "source": [
    "# Load pipeline config and build a detection model\n",
    "configs = config_util.get_configs_from_pipeline_file(files['PIPELINE_CONFIG'])\n",
    "detection_model = model_builder.build(model_config=configs['model'], is_training=False)\n",
    "\n",
    "# Restore checkpoint\n",
    "ckpt = tf.compat.v2.train.Checkpoint(model=detection_model)\n",
    "ckpt.restore(os.path.join(paths['CHECKPOINT_PATH'], 'ckpt-5')).expect_partial()\n",
    "\n",
    "@tf.function\n",
    "def detect_fn(image):\n",
    "    image, shapes = detection_model.preprocess(image)\n",
    "    prediction_dict = detection_model.predict(image, shapes)\n",
    "    detections = detection_model.postprocess(prediction_dict, shapes)\n",
    "    return detections"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "0EmsmbBZpfDI"
   },
   "source": [
    "# 9. Detect from an Image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "id": "Y_MKiuZ4pfDI"
   },
   "outputs": [],
   "source": [
    "import cv2 \n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "id": "cBDbIhNapfDI"
   },
   "outputs": [],
   "source": [
    "category_index = label_map_util.create_category_index_from_labelmap(files['LABELMAP'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "id": "Lx3crOhOzITB"
   },
   "outputs": [],
   "source": [
    "IMAGE_PATH = os.path.join(paths['IMAGE_PATH'], 'test', 'livelong.02533422-940e-11eb-9dbd-5cf3709bbcc6.jpg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 269
    },
    "id": "Tpzn1SMry1yK",
    "outputId": "c392a2c5-10fe-4fc4-9998-a1d4c7db2bd3"
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "in user code:\n\n    File \"C:\\Users\\Manas\\AppData\\Local\\Temp\\ipykernel_13064\\1654050223.py\", line 11, in detect_fn  *\n        image, shapes = detection_model.preprocess(image)\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\meta_architectures\\ssd_meta_arch.py\", line 484, in preprocess  *\n        normalized_inputs, self._image_resizer_fn)\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\shape_utils.py\", line 492, in resize_images_and_return_shapes  *\n        outputs = static_or_dynamic_map_fn(\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\shape_utils.py\", line 246, in static_or_dynamic_map_fn  *\n        outputs = [fn(arg) for arg in tf.unstack(elems)]\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\core\\preprocessor.py\", line 3330, in resize_image  *\n        new_image = tf.image.resize_images(\n\n    ValueError: 'images' must have either 3 or 4 dimensions.\n",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[125], line 5\u001b[0m\n\u001b[0;32m      2\u001b[0m image_np \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39marray(img)\n\u001b[0;32m      4\u001b[0m input_tensor \u001b[38;5;241m=\u001b[39m tf\u001b[38;5;241m.\u001b[39mconvert_to_tensor(np\u001b[38;5;241m.\u001b[39mexpand_dims(image_np, \u001b[38;5;241m0\u001b[39m), dtype\u001b[38;5;241m=\u001b[39mtf\u001b[38;5;241m.\u001b[39mfloat32)\n\u001b[1;32m----> 5\u001b[0m detections, predictions_dict, shapes \u001b[38;5;241m=\u001b[39m \u001b[43mdetect_fn\u001b[49m\u001b[43m(\u001b[49m\u001b[43minput_tensor\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m      7\u001b[0m num_detections \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mint\u001b[39m(detections\u001b[38;5;241m.\u001b[39mpop(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnum_detections\u001b[39m\u001b[38;5;124m'\u001b[39m))\n\u001b[0;32m      8\u001b[0m detections \u001b[38;5;241m=\u001b[39m {key: value[\u001b[38;5;241m0\u001b[39m, :num_detections]\u001b[38;5;241m.\u001b[39mnumpy()\n\u001b[0;32m      9\u001b[0m               \u001b[38;5;28;01mfor\u001b[39;00m key, value \u001b[38;5;129;01min\u001b[39;00m detections\u001b[38;5;241m.\u001b[39mitems()}\n",
      "File \u001b[1;32m~\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\tensorflow\\python\\util\\traceback_utils.py:153\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    151\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m    152\u001b[0m   filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n\u001b[1;32m--> 153\u001b[0m   \u001b[38;5;28;01mraise\u001b[39;00m e\u001b[38;5;241m.\u001b[39mwith_traceback(filtered_tb) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28mNone\u001b[39m\n\u001b[0;32m    154\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m    155\u001b[0m   \u001b[38;5;28;01mdel\u001b[39;00m filtered_tb\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_filesfg5k0sr.py:10\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__detect_fn\u001b[1;34m(image)\u001b[0m\n\u001b[0;32m      8\u001b[0m do_return \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[0;32m      9\u001b[0m retval_ \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mUndefinedReturnValue()\n\u001b[1;32m---> 10\u001b[0m (image, shapes) \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(detection_model)\u001b[38;5;241m.\u001b[39mpreprocess, (ag__\u001b[38;5;241m.\u001b[39mld(image),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)\n\u001b[0;32m     11\u001b[0m prediction_dict \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(detection_model)\u001b[38;5;241m.\u001b[39mpredict, (ag__\u001b[38;5;241m.\u001b[39mld(image), ag__\u001b[38;5;241m.\u001b[39mld(shapes)), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)\n\u001b[0;32m     12\u001b[0m detections \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(detection_model)\u001b[38;5;241m.\u001b[39mpostprocess, (ag__\u001b[38;5;241m.\u001b[39mld(prediction_dict), ag__\u001b[38;5;241m.\u001b[39mld(shapes)), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_fileck8tvdpj.py:35\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__preprocess\u001b[1;34m(self, inputs)\u001b[0m\n\u001b[0;32m     33\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m     34\u001b[0m     do_return \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m---> 35\u001b[0m     retval_ \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(shape_utils)\u001b[38;5;241m.\u001b[39mresize_images_and_return_shapes, (ag__\u001b[38;5;241m.\u001b[39mld(normalized_inputs), ag__\u001b[38;5;241m.\u001b[39mld(\u001b[38;5;28mself\u001b[39m)\u001b[38;5;241m.\u001b[39m_image_resizer_fn), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)\n\u001b[0;32m     36\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[0;32m     37\u001b[0m     do_return \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_fileclubxhy9.py:37\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__resize_images_and_return_shapes\u001b[1;34m(inputs, image_resizer_fn)\u001b[0m\n\u001b[0;32m     35\u001b[0m     \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[0;32m     36\u001b[0m ag__\u001b[38;5;241m.\u001b[39mif_stmt(ag__\u001b[38;5;241m.\u001b[39mld(inputs)\u001b[38;5;241m.\u001b[39mdtype \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39mfloat32, if_body, else_body, get_state, set_state, (), \u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m---> 37\u001b[0m outputs \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(static_or_dynamic_map_fn), (ag__\u001b[38;5;241m.\u001b[39mld(image_resizer_fn),), \u001b[38;5;28mdict\u001b[39m(elems\u001b[38;5;241m=\u001b[39mag__\u001b[38;5;241m.\u001b[39mld(inputs), dtype\u001b[38;5;241m=\u001b[39m[ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39mfloat32, ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39mint32]), fscope)\n\u001b[0;32m     38\u001b[0m resized_inputs \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mld(outputs)[\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m     39\u001b[0m true_image_shapes \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mld(outputs)[\u001b[38;5;241m1\u001b[39m]\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_filelwls6fqg.py:186\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__static_or_dynamic_map_fn\u001b[1;34m(fn, elems, dtype, parallel_iterations, back_prop)\u001b[0m\n\u001b[0;32m    184\u001b[0m elem_shape \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mUndefined(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124melem_shape\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m    185\u001b[0m outputs \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mUndefined(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124moutputs\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m--> 186\u001b[0m ag__\u001b[38;5;241m.\u001b[39mif_stmt(ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(\u001b[38;5;28misinstance\u001b[39m), (ag__\u001b[38;5;241m.\u001b[39mld(elems), ag__\u001b[38;5;241m.\u001b[39mld(\u001b[38;5;28mlist\u001b[39m)), \u001b[38;5;28;01mNone\u001b[39;00m, fscope), if_body_5, else_body_5, get_state_7, set_state_7, (\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdo_return\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124moutputs\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mretval_\u001b[39m\u001b[38;5;124m'\u001b[39m), \u001b[38;5;241m3\u001b[39m)\n\u001b[0;32m    188\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_state_12\u001b[39m():\n\u001b[0;32m    189\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m (do_return, retval_)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_filelwls6fqg.py:179\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__static_or_dynamic_map_fn.<locals>.else_body_5\u001b[1;34m()\u001b[0m\n\u001b[0;32m    177\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m [ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(fn), (ag__\u001b[38;5;241m.\u001b[39mld(arg),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope) \u001b[38;5;28;01mfor\u001b[39;00m arg \u001b[38;5;129;01min\u001b[39;00m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39munstack, (ag__\u001b[38;5;241m.\u001b[39mld(elems),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)]\n\u001b[0;32m    178\u001b[0m outputs \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mUndefined(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124moutputs\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m--> 179\u001b[0m \u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mif_stmt\u001b[49m\u001b[43m(\u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mor_\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnot_\u001b[49m\u001b[43m(\u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mld\u001b[49m\u001b[43m(\u001b[49m\u001b[43melems_shape\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnot_\u001b[49m\u001b[43m(\u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mld\u001b[49m\u001b[43m(\u001b[49m\u001b[43melems_shape\u001b[49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mif_body_4\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43melse_body_4\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mget_state_6\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mset_state_6\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mdo_return\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43moutputs\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mretval_\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m3\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_filelwls6fqg.py:177\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__static_or_dynamic_map_fn.<locals>.else_body_5.<locals>.else_body_4\u001b[1;34m()\u001b[0m\n\u001b[0;32m    175\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21melse_body_4\u001b[39m():\n\u001b[0;32m    176\u001b[0m     \u001b[38;5;28;01mnonlocal\u001b[39;00m do_return, retval_, outputs\n\u001b[1;32m--> 177\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m [ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(fn), (ag__\u001b[38;5;241m.\u001b[39mld(arg),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope) \u001b[38;5;28;01mfor\u001b[39;00m arg \u001b[38;5;129;01min\u001b[39;00m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39munstack, (ag__\u001b[38;5;241m.\u001b[39mld(elems),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)]\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_filelwls6fqg.py:177\u001b[0m, in \u001b[0;36m<listcomp>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m    175\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21melse_body_4\u001b[39m():\n\u001b[0;32m    176\u001b[0m     \u001b[38;5;28;01mnonlocal\u001b[39;00m do_return, retval_, outputs\n\u001b[1;32m--> 177\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m [\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconverted_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mld\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mld\u001b[49m\u001b[43m(\u001b[49m\u001b[43marg\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfscope\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m arg \u001b[38;5;129;01min\u001b[39;00m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39munstack, (ag__\u001b[38;5;241m.\u001b[39mld(elems),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)]\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_file57nmue0_.py:34\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__resize_image\u001b[1;34m(image, masks, new_height, new_width, method, align_corners)\u001b[0m\n\u001b[0;32m     32\u001b[0m retval_ \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mUndefinedReturnValue()\n\u001b[0;32m     33\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39mname_scope(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mResizeImage\u001b[39m\u001b[38;5;124m'\u001b[39m, values\u001b[38;5;241m=\u001b[39m[ag__\u001b[38;5;241m.\u001b[39mld(image), ag__\u001b[38;5;241m.\u001b[39mld(new_height), ag__\u001b[38;5;241m.\u001b[39mld(new_width), ag__\u001b[38;5;241m.\u001b[39mld(method), ag__\u001b[38;5;241m.\u001b[39mld(align_corners)]):\n\u001b[1;32m---> 34\u001b[0m     new_image \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39mimage\u001b[38;5;241m.\u001b[39mresize_images, (ag__\u001b[38;5;241m.\u001b[39mld(image), ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39mstack, ([ag__\u001b[38;5;241m.\u001b[39mld(new_height), ag__\u001b[38;5;241m.\u001b[39mld(new_width)],), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)), \u001b[38;5;28mdict\u001b[39m(method\u001b[38;5;241m=\u001b[39mag__\u001b[38;5;241m.\u001b[39mld(method), align_corners\u001b[38;5;241m=\u001b[39mag__\u001b[38;5;241m.\u001b[39mld(align_corners)), fscope)\n\u001b[0;32m     35\u001b[0m     image_shape \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(shape_utils)\u001b[38;5;241m.\u001b[39mcombined_static_and_dynamic_shape, (ag__\u001b[38;5;241m.\u001b[39mld(image),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)\n\u001b[0;32m     36\u001b[0m     result \u001b[38;5;241m=\u001b[39m [ag__\u001b[38;5;241m.\u001b[39mld(new_image)]\n",
      "\u001b[1;31mValueError\u001b[0m: in user code:\n\n    File \"C:\\Users\\Manas\\AppData\\Local\\Temp\\ipykernel_13064\\1654050223.py\", line 11, in detect_fn  *\n        image, shapes = detection_model.preprocess(image)\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\meta_architectures\\ssd_meta_arch.py\", line 484, in preprocess  *\n        normalized_inputs, self._image_resizer_fn)\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\shape_utils.py\", line 492, in resize_images_and_return_shapes  *\n        outputs = static_or_dynamic_map_fn(\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\shape_utils.py\", line 246, in static_or_dynamic_map_fn  *\n        outputs = [fn(arg) for arg in tf.unstack(elems)]\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\core\\preprocessor.py\", line 3330, in resize_image  *\n        new_image = tf.image.resize_images(\n\n    ValueError: 'images' must have either 3 or 4 dimensions.\n"
     ]
    }
   ],
   "source": [
    "img = cv2.imread(IMAGE_PATH)\n",
    "image_np = np.array(img)\n",
    "\n",
    "input_tensor = tf.convert_to_tensor(np.expand_dims(image_np, 0), dtype=tf.float32)\n",
    "detections, predictions_dict, shapes = detect_fn(input_tensor)\n",
    "\n",
    "num_detections = int(detections.pop('num_detections'))\n",
    "detections = {key: value[0, :num_detections].numpy()\n",
    "              for key, value in detections.items()}\n",
    "detections['num_detections'] = num_detections\n",
    "\n",
    "# detection_classes should be ints.\n",
    "detections['detection_classes'] = detections['detection_classes'].astype(np.int64)\n",
    "\n",
    "label_id_offset = 1\n",
    "image_np_with_detections = image_np.copy()\n",
    "\n",
    "viz_utils.visualize_boxes_and_labels_on_image_array(\n",
    "            image_np_with_detections,\n",
    "            detections['detection_boxes'],\n",
    "            detections['detection_classes']+label_id_offset,\n",
    "            detections['detection_scores'],\n",
    "            category_index,\n",
    "            use_normalized_coordinates=True,\n",
    "            max_boxes_to_draw=5,\n",
    "            min_score_thresh=.8,\n",
    "            agnostic_mode=False)\n",
    "\n",
    "plt.imshow(cv2.cvtColor(image_np_with_detections, cv2.COLOR_BGR2RGB))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "IsNAaYAo0WVL"
   },
   "source": [
    "# 10. Real Time Detections from your Webcam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING: Skipping opencv-python-headless as it is not installed.\n"
     ]
    }
   ],
   "source": [
    "!pip uninstall opencv-python-headless -y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {
    "id": "o_grs6OGpfDJ"
   },
   "outputs": [
    {
     "ename": "ValueError",
     "evalue": "in user code:\n\n    File \"C:\\Users\\Manas\\AppData\\Local\\Temp\\ipykernel_13064\\1654050223.py\", line 11, in detect_fn  *\n        image, shapes = detection_model.preprocess(image)\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\meta_architectures\\ssd_meta_arch.py\", line 484, in preprocess  *\n        normalized_inputs, self._image_resizer_fn)\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\shape_utils.py\", line 492, in resize_images_and_return_shapes  *\n        outputs = static_or_dynamic_map_fn(\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\shape_utils.py\", line 246, in static_or_dynamic_map_fn  *\n        outputs = [fn(arg) for arg in tf.unstack(elems)]\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\core\\preprocessor.py\", line 3330, in resize_image  *\n        new_image = tf.image.resize_images(\n\n    ValueError: 'images' must have either 3 or 4 dimensions.\n",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[132], line 24\u001b[0m\n\u001b[0;32m     15\u001b[0m \u001b[38;5;66;03m# Things to try:\u001b[39;00m\n\u001b[0;32m     16\u001b[0m \u001b[38;5;66;03m# Flip horizontally\u001b[39;00m\n\u001b[0;32m     17\u001b[0m \u001b[38;5;66;03m# image_np = np.fliplr(image_np).copy()\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     20\u001b[0m \u001b[38;5;66;03m# image_np = np.tile(\u001b[39;00m\n\u001b[0;32m     21\u001b[0m \u001b[38;5;66;03m#     np.mean(image_np, 2, keepdims=True), (1, 1, 3)).astype(np.uint8)\u001b[39;00m\n\u001b[0;32m     23\u001b[0m input_tensor \u001b[38;5;241m=\u001b[39m  tf\u001b[38;5;241m.\u001b[39mconvert_to_tensor(np\u001b[38;5;241m.\u001b[39mexpand_dims(image_np, \u001b[38;5;241m0\u001b[39m), dtype\u001b[38;5;241m=\u001b[39mtf\u001b[38;5;241m.\u001b[39mfloat32)\n\u001b[1;32m---> 24\u001b[0m detections \u001b[38;5;241m=\u001b[39m \u001b[43mdetect_fn\u001b[49m\u001b[43m(\u001b[49m\u001b[43minput_tensor\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     26\u001b[0m label_id_offset \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m     27\u001b[0m image_np_with_detections \u001b[38;5;241m=\u001b[39m image_np\u001b[38;5;241m.\u001b[39mcopy()\n",
      "File \u001b[1;32m~\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\tensorflow\\python\\util\\traceback_utils.py:153\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    151\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m    152\u001b[0m   filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n\u001b[1;32m--> 153\u001b[0m   \u001b[38;5;28;01mraise\u001b[39;00m e\u001b[38;5;241m.\u001b[39mwith_traceback(filtered_tb) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28mNone\u001b[39m\n\u001b[0;32m    154\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m    155\u001b[0m   \u001b[38;5;28;01mdel\u001b[39;00m filtered_tb\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_filesfg5k0sr.py:10\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__detect_fn\u001b[1;34m(image)\u001b[0m\n\u001b[0;32m      8\u001b[0m do_return \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[0;32m      9\u001b[0m retval_ \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mUndefinedReturnValue()\n\u001b[1;32m---> 10\u001b[0m (image, shapes) \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(detection_model)\u001b[38;5;241m.\u001b[39mpreprocess, (ag__\u001b[38;5;241m.\u001b[39mld(image),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)\n\u001b[0;32m     11\u001b[0m prediction_dict \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(detection_model)\u001b[38;5;241m.\u001b[39mpredict, (ag__\u001b[38;5;241m.\u001b[39mld(image), ag__\u001b[38;5;241m.\u001b[39mld(shapes)), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)\n\u001b[0;32m     12\u001b[0m detections \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(detection_model)\u001b[38;5;241m.\u001b[39mpostprocess, (ag__\u001b[38;5;241m.\u001b[39mld(prediction_dict), ag__\u001b[38;5;241m.\u001b[39mld(shapes)), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_fileck8tvdpj.py:35\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__preprocess\u001b[1;34m(self, inputs)\u001b[0m\n\u001b[0;32m     33\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m     34\u001b[0m     do_return \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m---> 35\u001b[0m     retval_ \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(shape_utils)\u001b[38;5;241m.\u001b[39mresize_images_and_return_shapes, (ag__\u001b[38;5;241m.\u001b[39mld(normalized_inputs), ag__\u001b[38;5;241m.\u001b[39mld(\u001b[38;5;28mself\u001b[39m)\u001b[38;5;241m.\u001b[39m_image_resizer_fn), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)\n\u001b[0;32m     36\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[0;32m     37\u001b[0m     do_return \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_fileclubxhy9.py:37\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__resize_images_and_return_shapes\u001b[1;34m(inputs, image_resizer_fn)\u001b[0m\n\u001b[0;32m     35\u001b[0m     \u001b[38;5;28;01mpass\u001b[39;00m\n\u001b[0;32m     36\u001b[0m ag__\u001b[38;5;241m.\u001b[39mif_stmt(ag__\u001b[38;5;241m.\u001b[39mld(inputs)\u001b[38;5;241m.\u001b[39mdtype \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39mfloat32, if_body, else_body, get_state, set_state, (), \u001b[38;5;241m0\u001b[39m)\n\u001b[1;32m---> 37\u001b[0m outputs \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(static_or_dynamic_map_fn), (ag__\u001b[38;5;241m.\u001b[39mld(image_resizer_fn),), \u001b[38;5;28mdict\u001b[39m(elems\u001b[38;5;241m=\u001b[39mag__\u001b[38;5;241m.\u001b[39mld(inputs), dtype\u001b[38;5;241m=\u001b[39m[ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39mfloat32, ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39mint32]), fscope)\n\u001b[0;32m     38\u001b[0m resized_inputs \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mld(outputs)[\u001b[38;5;241m0\u001b[39m]\n\u001b[0;32m     39\u001b[0m true_image_shapes \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mld(outputs)[\u001b[38;5;241m1\u001b[39m]\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_filelwls6fqg.py:186\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__static_or_dynamic_map_fn\u001b[1;34m(fn, elems, dtype, parallel_iterations, back_prop)\u001b[0m\n\u001b[0;32m    184\u001b[0m elem_shape \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mUndefined(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124melem_shape\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[0;32m    185\u001b[0m outputs \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mUndefined(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124moutputs\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m--> 186\u001b[0m ag__\u001b[38;5;241m.\u001b[39mif_stmt(ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(\u001b[38;5;28misinstance\u001b[39m), (ag__\u001b[38;5;241m.\u001b[39mld(elems), ag__\u001b[38;5;241m.\u001b[39mld(\u001b[38;5;28mlist\u001b[39m)), \u001b[38;5;28;01mNone\u001b[39;00m, fscope), if_body_5, else_body_5, get_state_7, set_state_7, (\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdo_return\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124moutputs\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mretval_\u001b[39m\u001b[38;5;124m'\u001b[39m), \u001b[38;5;241m3\u001b[39m)\n\u001b[0;32m    188\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mget_state_12\u001b[39m():\n\u001b[0;32m    189\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m (do_return, retval_)\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_filelwls6fqg.py:179\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__static_or_dynamic_map_fn.<locals>.else_body_5\u001b[1;34m()\u001b[0m\n\u001b[0;32m    177\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m [ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(fn), (ag__\u001b[38;5;241m.\u001b[39mld(arg),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope) \u001b[38;5;28;01mfor\u001b[39;00m arg \u001b[38;5;129;01min\u001b[39;00m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39munstack, (ag__\u001b[38;5;241m.\u001b[39mld(elems),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)]\n\u001b[0;32m    178\u001b[0m outputs \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mUndefined(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124moutputs\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m--> 179\u001b[0m \u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mif_stmt\u001b[49m\u001b[43m(\u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mor_\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnot_\u001b[49m\u001b[43m(\u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mld\u001b[49m\u001b[43m(\u001b[49m\u001b[43melems_shape\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mlambda\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mnot_\u001b[49m\u001b[43m(\u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mld\u001b[49m\u001b[43m(\u001b[49m\u001b[43melems_shape\u001b[49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mif_body_4\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43melse_body_4\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mget_state_6\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mset_state_6\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mdo_return\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43moutputs\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mretval_\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m3\u001b[39;49m\u001b[43m)\u001b[49m\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_filelwls6fqg.py:177\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__static_or_dynamic_map_fn.<locals>.else_body_5.<locals>.else_body_4\u001b[1;34m()\u001b[0m\n\u001b[0;32m    175\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21melse_body_4\u001b[39m():\n\u001b[0;32m    176\u001b[0m     \u001b[38;5;28;01mnonlocal\u001b[39;00m do_return, retval_, outputs\n\u001b[1;32m--> 177\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m [ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(fn), (ag__\u001b[38;5;241m.\u001b[39mld(arg),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope) \u001b[38;5;28;01mfor\u001b[39;00m arg \u001b[38;5;129;01min\u001b[39;00m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39munstack, (ag__\u001b[38;5;241m.\u001b[39mld(elems),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)]\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_filelwls6fqg.py:177\u001b[0m, in \u001b[0;36m<listcomp>\u001b[1;34m(.0)\u001b[0m\n\u001b[0;32m    175\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21melse_body_4\u001b[39m():\n\u001b[0;32m    176\u001b[0m     \u001b[38;5;28;01mnonlocal\u001b[39;00m do_return, retval_, outputs\n\u001b[1;32m--> 177\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m [\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconverted_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mld\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfn\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mag__\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mld\u001b[49m\u001b[43m(\u001b[49m\u001b[43marg\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mfscope\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m arg \u001b[38;5;129;01min\u001b[39;00m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39munstack, (ag__\u001b[38;5;241m.\u001b[39mld(elems),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)]\n",
      "File \u001b[1;32m~\\AppData\\Local\\Temp\\__autograph_generated_file57nmue0_.py:34\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__resize_image\u001b[1;34m(image, masks, new_height, new_width, method, align_corners)\u001b[0m\n\u001b[0;32m     32\u001b[0m retval_ \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mUndefinedReturnValue()\n\u001b[0;32m     33\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39mname_scope(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mResizeImage\u001b[39m\u001b[38;5;124m'\u001b[39m, values\u001b[38;5;241m=\u001b[39m[ag__\u001b[38;5;241m.\u001b[39mld(image), ag__\u001b[38;5;241m.\u001b[39mld(new_height), ag__\u001b[38;5;241m.\u001b[39mld(new_width), ag__\u001b[38;5;241m.\u001b[39mld(method), ag__\u001b[38;5;241m.\u001b[39mld(align_corners)]):\n\u001b[1;32m---> 34\u001b[0m     new_image \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39mimage\u001b[38;5;241m.\u001b[39mresize_images, (ag__\u001b[38;5;241m.\u001b[39mld(image), ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(tf)\u001b[38;5;241m.\u001b[39mstack, ([ag__\u001b[38;5;241m.\u001b[39mld(new_height), ag__\u001b[38;5;241m.\u001b[39mld(new_width)],), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)), \u001b[38;5;28mdict\u001b[39m(method\u001b[38;5;241m=\u001b[39mag__\u001b[38;5;241m.\u001b[39mld(method), align_corners\u001b[38;5;241m=\u001b[39mag__\u001b[38;5;241m.\u001b[39mld(align_corners)), fscope)\n\u001b[0;32m     35\u001b[0m     image_shape \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(shape_utils)\u001b[38;5;241m.\u001b[39mcombined_static_and_dynamic_shape, (ag__\u001b[38;5;241m.\u001b[39mld(image),), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)\n\u001b[0;32m     36\u001b[0m     result \u001b[38;5;241m=\u001b[39m [ag__\u001b[38;5;241m.\u001b[39mld(new_image)]\n",
      "\u001b[1;31mValueError\u001b[0m: in user code:\n\n    File \"C:\\Users\\Manas\\AppData\\Local\\Temp\\ipykernel_13064\\1654050223.py\", line 11, in detect_fn  *\n        image, shapes = detection_model.preprocess(image)\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\meta_architectures\\ssd_meta_arch.py\", line 484, in preprocess  *\n        normalized_inputs, self._image_resizer_fn)\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\shape_utils.py\", line 492, in resize_images_and_return_shapes  *\n        outputs = static_or_dynamic_map_fn(\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\utils\\shape_utils.py\", line 246, in static_or_dynamic_map_fn  *\n        outputs = [fn(arg) for arg in tf.unstack(elems)]\n    File \"C:\\Users\\Manas\\OneDrive\\Documents\\HackNotts\\Hackathon\\tfod\\tfod\\lib\\site-packages\\object_detection-0.1-py3.9.egg\\object_detection\\core\\preprocessor.py\", line 3330, in resize_image  *\n        new_image = tf.image.resize_images(\n\n    ValueError: 'images' must have either 3 or 4 dimensions.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "\n",
    "import cv2\n",
    "\n",
    "cap = cv2.VideoCapture(0)\n",
    "\n",
    "while True:\n",
    "    # Read frame from camera\n",
    "    ret, image_np = cap.read()\n",
    "\n",
    "    # Expand dimensions since the model expects images to have shape: [1, None, None, 3]\n",
    "    image_np_expanded = np.expand_dims(image_np, axis=0)\n",
    "\n",
    "    # Things to try:\n",
    "    # Flip horizontally\n",
    "    # image_np = np.fliplr(image_np).copy()\n",
    "\n",
    "    # Convert image to grayscale\n",
    "    # image_np = np.tile(\n",
    "    #     np.mean(image_np, 2, keepdims=True), (1, 1, 3)).astype(np.uint8)\n",
    "\n",
    "    input_tensor =  tf.convert_to_tensor(np.expand_dims(image_np, 0), dtype=tf.float32)\n",
    "    detections = detect_fn(input_tensor)\n",
    "\n",
    "    label_id_offset = 1\n",
    "    image_np_with_detections = image_np.copy()\n",
    "\n",
    "    viz_utils.visualize_boxes_and_labels_on_image_array(\n",
    "          image_np_with_detections,\n",
    "          detections['detection_boxes'][0].numpy(),\n",
    "          (detections['detection_classes'][0].numpy() + label_id_offset).astype(int),\n",
    "          detections['detection_scores'][0].numpy(),\n",
    "          category_index,\n",
    "          use_normalized_coordinates=True,\n",
    "          max_boxes_to_draw=200,\n",
    "          min_score_thresh=.30,\n",
    "          agnostic_mode=False)\n",
    "\n",
    "    # Display output\n",
    "    cv2.imshow('object detection', cv2.resize(image_np_with_detections, (800, 600)))\n",
    "\n",
    "    if cv2.waitKey(25) & 0xFF == ord('q'):\n",
    "        break\n",
    "\n",
    "cap.release()\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rzlM4jt0pfDJ"
   },
   "source": [
    "# 10. Freezing the Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "id": "n4olHB2npfDJ"
   },
   "outputs": [],
   "source": [
    "FREEZE_SCRIPT = os.path.join(paths['APIMODEL_PATH'], 'research', 'object_detection', 'exporter_main_v2.py ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "id": "0AjO93QDpfDJ"
   },
   "outputs": [],
   "source": [
    "command = \"python {} --input_type=image_tensor --pipeline_config_path={} --trained_checkpoint_dir={} --output_directory={}\".format(FREEZE_SCRIPT ,files['PIPELINE_CONFIG'], paths['CHECKPOINT_PATH'], paths['OUTPUT_PATH'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "F6Lsp3tCpfDJ",
    "outputId": "c3828529-bf06-4df5-d7f3-145890ec3edd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "python Tensorflow\\models\\research\\object_detection\\exporter_main_v2.py  --input_type=image_tensor --pipeline_config_path=Tensorflow\\workspace\\models\\my_ssd_mobnet\\pipeline.config --trained_checkpoint_dir=Tensorflow\\workspace\\models\\my_ssd_mobnet --output_directory=Tensorflow\\workspace\\models\\my_ssd_mobnet\\export\n"
     ]
    }
   ],
   "source": [
    "print(command)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "1Sw1ULgHpfDJ",
    "outputId": "6fd441e1-9fc9-4889-d072-3395c21e40b6"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-04-03 11:51:42.281339: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:51:44.712115: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2021-04-03 11:51:44.712813: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll\n",
      "2021-04-03 11:51:44.734951: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:51:44.734976: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:51:44.738520: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:51:44.738545: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:51:44.740713: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:51:44.741572: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:51:44.745641: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:51:44.747323: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:51:44.747849: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:51:44.747917: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:51:44.748158: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2021-04-03 11:51:44.748975: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:51:44.749003: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:51:44.749011: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:51:44.749017: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:51:44.749025: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:51:44.749031: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:51:44.749036: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:51:44.749042: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:51:44.749046: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:51:44.749072: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:51:45.185363: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
      "2021-04-03 11:51:45.185385: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n",
      "2021-04-03 11:51:45.185389: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n",
      "2021-04-03 11:51:45.185509: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6461 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2070 SUPER, pci bus id: 0000:2b:00.0, compute capability: 7.5)\n",
      "2021-04-03 11:51:45.185889: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "WARNING:tensorflow:From D:\\YouTube\\OD\\TFODCourse\\tfod\\lib\\site-packages\\object_detection-0.1-py3.7.egg\\object_detection\\exporter_lib_v2.py:106: calling map_fn_v2 (from tensorflow.python.ops.map_fn) with back_prop=False is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "back_prop=False is deprecated. Consider using tf.stop_gradient instead.\n",
      "Instead of:\n",
      "results = tf.map_fn(fn, elems, back_prop=False)\n",
      "Use:\n",
      "results = tf.nest.map_structure(tf.stop_gradient, tf.map_fn(fn, elems))\n",
      "W0403 11:51:46.585407 12508 deprecation.py:604] From D:\\YouTube\\OD\\TFODCourse\\tfod\\lib\\site-packages\\object_detection-0.1-py3.7.egg\\object_detection\\exporter_lib_v2.py:106: calling map_fn_v2 (from tensorflow.python.ops.map_fn) with back_prop=False is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "back_prop=False is deprecated. Consider using tf.stop_gradient instead.\n",
      "Instead of:\n",
      "results = tf.map_fn(fn, elems, back_prop=False)\n",
      "Use:\n",
      "results = tf.nest.map_structure(tf.stop_gradient, tf.map_fn(fn, elems))\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x0000022EAD5FA7F0>, because it is not built.\n",
      "W0403 11:51:57.182201 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x0000022EAD5FA7F0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x0000022EB41A6128>, because it is not built.\n",
      "W0403 11:51:57.735328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x0000022EB41A6128>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ECBB91940>, because it is not built.\n",
      "W0403 11:51:57.735328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ECBB91940>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022EC7E820F0>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022EC7E820F0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x0000022EBFE87F98>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x0000022EBFE87F98>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED451CDA0>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED451CDA0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED451CD30>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED451CD30>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x0000022ED451C390>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x0000022ED451C390>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED4510FD0>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED4510FD0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ECBB744A8>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ECBB744A8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x0000022ECBB74EB8>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x0000022ECBB74EB8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ECBBCD390>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ECBBCD390>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E8C5C0>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E8C5C0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ECBBA1CC0>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ECBBA1CC0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E8E0B8>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E8E0B8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E9F0F0>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E9F0F0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E9F358>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E9F358>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E9F208>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E9F208>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E9FA90>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E9FA90>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E9FC18>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E9FC18>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E9FDA0>, because it is not built.\n",
      "W0403 11:51:57.736328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E9FDA0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6EBAF98>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6EBAF98>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6EB6B00>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6EB6B00>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6EB6DA0>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6EB6DA0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E98B00>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E98B00>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E982E8>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E982E8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E98C50>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E98C50>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E984A8>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E984A8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E98B38>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E98B38>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E42470>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E42470>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED59E30F0>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED59E30F0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED59E3E10>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED59E3E10>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E233C8>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E233C8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E23198>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E23198>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED59CA2E8>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED59CA2E8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED59CA3C8>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED59CA3C8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E68278>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E68278>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED450C828>, because it is not built.\n",
      "W0403 11:51:57.737328 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED450C828>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E7B160>, because it is not built.\n",
      "W0403 11:51:57.738330 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E7B160>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E7B080>, because it is not built.\n",
      "W0403 11:51:57.738330 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E7B080>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E7B898>, because it is not built.\n",
      "W0403 11:51:57.738330 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED6E7B898>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E7B8D0>, because it is not built.\n",
      "W0403 11:51:57.738330 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED6E7B8D0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED58784E0>, because it is not built.\n",
      "W0403 11:51:57.738330 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED58784E0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED5878198>, because it is not built.\n",
      "W0403 11:51:57.738330 12508 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x0000022ED5878198>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED5878828>, because it is not built.\n",
      "W0403 11:51:57.738330 12508 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x0000022ED5878828>, because it is not built.\n",
      "2021-04-03 11:52:03.707161: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:52:09.159238 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:52:09.160238 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2358>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C25C0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:52:09.160238 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2358>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C25C0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B52E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:52:09.160238 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B52E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2358>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C25C0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:52:11.896544 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2358>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C25C0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B52E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:52:11.896544 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B52E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:52:11.896544 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:52:11.896544 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:52:11.896544 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:52:11.896544 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "W0403 11:52:14.030074 12508 save.py:241] Found untraced functions such as WeightSharedConvolutionalBoxPredictor_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxPredictor_layer_call_fn, WeightSharedConvolutionalBoxHead_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxHead_layer_call_fn, WeightSharedConvolutionalBoxPredictor_layer_call_fn while saving (showing 5 of 155). These functions will not be directly callable after loading.\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:52:14.174074 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:52:14.174074 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2358>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C25C0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:52:14.174074 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2358>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C25C0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B52E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:52:14.174074 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B52E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2358>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C25C0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:52:14.368074 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2358>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C25C0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B52E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:52:14.368074 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B52E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:52:14.368074 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:52:14.368074 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:52:14.368074 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:52:14.368074 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "W0403 11:52:14.738204 12508 save.py:241] Found untraced functions such as WeightSharedConvolutionalBoxPredictor_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxPredictor_layer_call_fn, WeightSharedConvolutionalBoxHead_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxHead_layer_call_fn, WeightSharedConvolutionalBoxPredictor_layer_call_fn while saving (showing 5 of 155). These functions will not be directly callable after loading.\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:52:17.735654 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C4A8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C7F0>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002309135C6A0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:52:17.735654 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923746D8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374828>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x0000023092374A90>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2358>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C25C0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:52:17.736654 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C2358>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923C25C0>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B52E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:52:17.736654 12508 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B52E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x00000230923B5550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Assets written to: Tensorflow\\workspace\\models\\my_ssd_mobnet\\export\\saved_model\\assets\n",
      "I0403 11:52:18.462644 12508 builder_impl.py:775] Assets written to: Tensorflow\\workspace\\models\\my_ssd_mobnet\\export\\saved_model\\assets\n",
      "INFO:tensorflow:Writing pipeline config file to Tensorflow\\workspace\\models\\my_ssd_mobnet\\export\\pipeline.config\n",
      "I0403 11:52:19.186990 12508 config_util.py:254] Writing pipeline config file to Tensorflow\\workspace\\models\\my_ssd_mobnet\\export\\pipeline.config\n"
     ]
    }
   ],
   "source": [
    "!{command}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "wTPmdqaXpfDK"
   },
   "source": [
    "# 11. Conversion to TFJS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "gZ6UzY_fpfDK",
    "outputId": "0c84722e-1c2b-4002-d857-80827ade828a",
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting tensorflowjs\n",
      "  Using cached tensorflowjs-3.3.0-py3-none-any.whl (63 kB)\n",
      "Requirement already satisfied: six<2,>=1.12.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflowjs) (1.15.0)\n",
      "Collecting tensorflow-hub<0.10,>=0.7.0\n",
      "  Using cached tensorflow_hub-0.9.0-py2.py3-none-any.whl (103 kB)\n",
      "Requirement already satisfied: h5py<3,>=2.8.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflowjs) (2.10.0)\n",
      "Requirement already satisfied: tensorflow<3,>=2.1.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflowjs) (2.4.0)\n",
      "Requirement already satisfied: numpy>=1.7 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from h5py<3,>=2.8.0->tensorflowjs) (1.19.5)\n",
      "Requirement already satisfied: flatbuffers~=1.12.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.12)\n",
      "Requirement already satisfied: gast==0.3.3 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (0.3.3)\n",
      "Requirement already satisfied: wrapt~=1.12.1 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.12.1)\n",
      "Requirement already satisfied: tensorboard~=2.4 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (2.4.1)\n",
      "Requirement already satisfied: termcolor~=1.1.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.1.0)\n",
      "Requirement already satisfied: protobuf>=3.9.2 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (3.15.7)\n",
      "Requirement already satisfied: wheel~=0.35 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (0.36.2)\n",
      "Requirement already satisfied: tensorflow-estimator<2.5.0,>=2.4.0rc0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (2.4.0)\n",
      "Requirement already satisfied: absl-py~=0.10 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (0.12.0)\n",
      "Requirement already satisfied: opt-einsum~=3.3.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (3.3.0)\n",
      "Requirement already satisfied: grpcio~=1.32.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.32.0)\n",
      "Requirement already satisfied: keras-preprocessing~=1.1.2 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.1.2)\n",
      "Requirement already satisfied: astunparse~=1.6.3 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.6.3)\n",
      "Requirement already satisfied: typing-extensions~=3.7.4 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages\\typing_extensions-3.7.4.3-py3.7.egg (from tensorflow<3,>=2.1.0->tensorflowjs) (3.7.4.3)\n",
      "Requirement already satisfied: google-pasta~=0.2 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (0.2.0)\n",
      "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (0.4.4)\n",
      "Requirement already satisfied: werkzeug>=0.11.15 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (1.0.1)\n",
      "Requirement already satisfied: requests<3,>=2.21.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages\\requests-2.25.1-py3.7.egg (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (2.25.1)\n",
      "Requirement already satisfied: google-auth<2,>=1.6.3 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (1.28.0)\n",
      "Requirement already satisfied: setuptools>=41.0.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (54.2.0)\n",
      "Requirement already satisfied: markdown>=2.6.8 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (3.3.4)\n",
      "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (1.8.0)\n",
      "Requirement already satisfied: rsa<5,>=3.1.4 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (4.7.2)\n",
      "Requirement already satisfied: pyasn1-modules>=0.2.1 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (0.2.8)\n",
      "Requirement already satisfied: cachetools<5.0,>=2.0.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (4.2.1)\n",
      "Requirement already satisfied: requests-oauthlib>=0.7.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (1.3.0)\n",
      "Requirement already satisfied: importlib-metadata in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from markdown>=2.6.8->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (3.10.0)\n",
      "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from pyasn1-modules>=0.2.1->google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (0.4.8)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (2020.12.5)\n",
      "Requirement already satisfied: chardet<5,>=3.0.2 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (4.0.0)\n",
      "Requirement already satisfied: idna<3,>=2.5 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (2.10)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (1.26.4)\n",
      "Requirement already satisfied: oauthlib>=3.0.0 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (3.1.0)\n",
      "Requirement already satisfied: zipp>=0.5 in d:\\youtube\\od\\tfodcourse\\tfod\\lib\\site-packages (from importlib-metadata->markdown>=2.6.8->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (3.4.1)\n",
      "Installing collected packages: tensorflow-hub, tensorflowjs\n",
      "  Attempting uninstall: tensorflow-hub\n",
      "    Found existing installation: tensorflow-hub 0.11.0\n",
      "    Uninstalling tensorflow-hub-0.11.0:\n",
      "      Successfully uninstalled tensorflow-hub-0.11.0\n",
      "Successfully installed tensorflow-hub-0.9.0 tensorflowjs-3.3.0\n"
     ]
    }
   ],
   "source": [
    "!pip install tensorflowjs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "0oxbVynHpfDK"
   },
   "outputs": [],
   "source": [
    "command = \"tensorflowjs_converter --input_format=tf_saved_model --output_node_names='detection_boxes,detection_classes,detection_features,detection_multiclass_scores,detection_scores,num_detections,raw_detection_boxes,raw_detection_scores' --output_format=tfjs_graph_model --signature_name=serving_default {} {}\".format(os.path.join(paths['OUTPUT_PATH'], 'saved_model'), paths['TFJS_PATH'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "DB2AGNmJpfDK",
    "outputId": "fbc9f747-f511-47e8-df8f-5ea65cef0374"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensorflowjs_converter --input_format=tf_saved_model --output_node_names='detection_boxes,detection_classes,detection_features,detection_multiclass_scores,detection_scores,num_detections,raw_detection_boxes,raw_detection_scores' --output_format=tfjs_graph_model --signature_name=serving_default Tensorflow\\workspace\\models\\my_ssd_mobnet\\export\\saved_model Tensorflow\\workspace\\models\\my_ssd_mobnet\\tfjsexport\n"
     ]
    }
   ],
   "source": [
    "print(command)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "K7rfT4-hpfDK",
    "outputId": "532707fd-6feb-4bc6-84a3-325b5d16303c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Writing weight file Tensorflow\\workspace\\models\\my_ssd_mobnet\\tfjsexport\\model.json...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-04-03 11:54:23.153051: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:54:25.644887: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2021-04-03 11:54:25.645576: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll\n",
      "2021-04-03 11:54:25.667969: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:54:25.668001: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:54:25.671400: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:54:25.671416: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:54:25.673240: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:54:25.673772: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:54:25.677306: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:54:25.678684: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:54:25.679228: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:54:25.679291: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:54:25.679494: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2021-04-03 11:54:25.680122: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:54:25.680135: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:54:25.680141: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:54:25.680148: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:54:25.680152: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:54:25.680158: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:54:25.680163: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:54:25.680167: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:54:25.680171: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:54:25.680197: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:54:26.114383: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
      "2021-04-03 11:54:26.114403: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n",
      "2021-04-03 11:54:26.114407: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n",
      "2021-04-03 11:54:26.114533: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6611 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2070 SUPER, pci bus id: 0000:2b:00.0, compute capability: 7.5)\n",
      "2021-04-03 11:54:26.114935: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2021-04-03 11:54:34.068925: I tensorflow/core/grappler/devices.cc:69] Number of eligible GPUs (core count >= 8, compute capability >= 0.0): 1\n",
      "2021-04-03 11:54:34.069068: I tensorflow/core/grappler/clusters/single_machine.cc:356] Starting new session\n",
      "2021-04-03 11:54:34.070081: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:54:34.070099: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:54:34.070106: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:54:34.070112: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:54:34.070119: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:54:34.070123: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:54:34.070130: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:54:34.070134: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:54:34.070141: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:54:34.070164: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:54:34.070202: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
      "2021-04-03 11:54:34.070208: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n",
      "2021-04-03 11:54:34.070211: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n",
      "2021-04-03 11:54:34.070267: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6611 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2070 SUPER, pci bus id: 0000:2b:00.0, compute capability: 7.5)\n",
      "2021-04-03 11:54:34.070284: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2021-04-03 11:54:34.396918: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:928] Optimization results for grappler item: graph_to_optimize\n",
      "  function_optimizer: Graph size after: 4000 nodes (3591), 8430 edges (8014), time = 217.05ms.\n",
      "  function_optimizer: function_optimizer did nothing. time = 4.085ms.\n",
      "\n",
      "2021-04-03 11:54:37.417793: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:928] Optimization results for grappler item: graph_to_optimize\n",
      "  debug_stripper: Graph size after: 3683 nodes (0), 8201 edges (0), time = 79.922ms.\n",
      "  model_pruner: Graph size after: 3232 nodes (-451), 7750 edges (-451), time = 125.865ms.\n",
      "  constant_folding: Graph size after: 1551 nodes (-1681), 5834 edges (-1916), time = 199.089ms.\n",
      "  arithmetic_optimizer: Graph size after: 1551 nodes (0), 5834 edges (0), time = 33.234ms.\n",
      "  dependency_optimizer: Graph size after: 1453 nodes (-98), 1650 edges (-4184), time = 22.074ms.\n",
      "  model_pruner: Graph size after: 1453 nodes (0), 1650 edges (0), time = 9.534ms.\n",
      "  constant_folding: Graph size after: 1453 nodes (0), 1650 edges (0), time = 29.71ms.\n",
      "  arithmetic_optimizer: Graph size after: 1453 nodes (0), 1650 edges (0), time = 22.603ms.\n",
      "  dependency_optimizer: Graph size after: 1453 nodes (0), 1650 edges (0), time = 14.027ms.\n",
      "  debug_stripper: debug_stripper did nothing. time = 1.378ms.\n",
      "  model_pruner: Graph size after: 1453 nodes (0), 1650 edges (0), time = 7.504ms.\n",
      "  constant_folding: Graph size after: 1453 nodes (0), 1650 edges (0), time = 29.06ms.\n",
      "  arithmetic_optimizer: Graph size after: 1453 nodes (0), 1650 edges (0), time = 23.745ms.\n",
      "  dependency_optimizer: Graph size after: 1453 nodes (0), 1650 edges (0), time = 12.714ms.\n",
      "  model_pruner: Graph size after: 1453 nodes (0), 1650 edges (0), time = 8.842ms.\n",
      "  constant_folding: Graph size after: 1453 nodes (0), 1650 edges (0), time = 29.59ms.\n",
      "  arithmetic_optimizer: Graph size after: 1453 nodes (0), 1650 edges (0), time = 23.085ms.\n",
      "  dependency_optimizer: Graph size after: 1453 nodes (0), 1650 edges (0), time = 14.073ms.\n",
      "\n",
      "2021-04-03 11:54:45.020557: I tensorflow/core/grappler/optimizers/meta_optimizer.cc:928] Optimization results for grappler item: graph_to_optimize\n",
      "  remapper: Graph size after: 1415 nodes (-114), 1308 edges (-114), time = 6.93ms.\n",
      "  constant_folding: Graph size after: 1111 nodes (-304), 1308 edges (0), time = 45.571ms.\n",
      "  arithmetic_optimizer: Graph size after: 1111 nodes (0), 1308 edges (0), time = 18.394ms.\n",
      "  dependency_optimizer: Graph size after: 1111 nodes (0), 1308 edges (0), time = 9.992ms.\n",
      "  remapper: Graph size after: 1111 nodes (0), 1308 edges (0), time = 5.143ms.\n",
      "  constant_folding: Graph size after: 1111 nodes (0), 1308 edges (0), time = 22.813ms.\n",
      "  arithmetic_optimizer: Graph size after: 1111 nodes (0), 1308 edges (0), time = 18.23ms.\n",
      "  dependency_optimizer: Graph size after: 1111 nodes (0), 1308 edges (0), time = 9.571ms.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!{command}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "o8_hm-itpfDK"
   },
   "outputs": [],
   "source": [
    "# Test Code: https://github.com/nicknochnack/RealTimeSignLanguageDetectionwithTFJS"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "VtUw73FHpfDK"
   },
   "source": [
    "# 12. Conversion to TFLite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "id": "XviMtewLpfDK"
   },
   "outputs": [],
   "source": [
    "TFLITE_SCRIPT = os.path.join(paths['APIMODEL_PATH'], 'research', 'object_detection', 'export_tflite_graph_tf2.py ')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "id": "us86cjC4pfDL"
   },
   "outputs": [],
   "source": [
    "command = \"python {} --pipeline_config_path={} --trained_checkpoint_dir={} --output_directory={}\".format(TFLITE_SCRIPT ,files['PIPELINE_CONFIG'], paths['CHECKPOINT_PATH'], paths['TFLITE_PATH'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "n1r5YO3rpfDL",
    "outputId": "5fcdf7a4-eee2-4365-f1ca-1751968379ea"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "python Tensorflow\\models\\research\\object_detection\\export_tflite_graph_tf2.py  --pipeline_config_path=Tensorflow\\workspace\\models\\my_ssd_mobnet\\pipeline.config --trained_checkpoint_dir=Tensorflow\\workspace\\models\\my_ssd_mobnet --output_directory=Tensorflow\\workspace\\models\\my_ssd_mobnet\\tfliteexport\n"
     ]
    }
   ],
   "source": [
    "print(command)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "I-xWpHN8pfDL",
    "outputId": "7f6bacd8-d077-43b5-c131-5b081fba24a4"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-04-03 11:55:05.530772: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:55:08.004889: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2021-04-03 11:55:08.005672: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll\n",
      "2021-04-03 11:55:08.028532: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:55:08.028559: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:55:08.032092: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:55:08.032116: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:55:08.033961: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:55:08.034525: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:55:08.038018: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:55:08.039361: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:55:08.039837: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:55:08.039899: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:55:08.040128: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2021-04-03 11:55:08.040849: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:55:08.040866: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:55:08.040873: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:55:08.040882: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:55:08.040897: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:55:08.040905: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:55:08.040912: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:55:08.040919: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:55:08.040924: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:55:08.040953: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:55:08.479708: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
      "2021-04-03 11:55:08.479731: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n",
      "2021-04-03 11:55:08.479735: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n",
      "2021-04-03 11:55:08.479858: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6611 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2070 SUPER, pci bus id: 0000:2b:00.0, compute capability: 7.5)\n",
      "2021-04-03 11:55:08.480359: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2021-04-03 11:55:13.777905: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:55:13.777932: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:55:13.777938: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:55:13.777947: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:55:13.777952: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:55:13.777959: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:55:13.777963: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:55:13.777971: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:55:13.777975: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:55:13.778002: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:55:13.778043: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
      "2021-04-03 11:55:13.778049: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n",
      "2021-04-03 11:55:13.778052: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n",
      "2021-04-03 11:55:13.778142: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6611 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2070 SUPER, pci bus id: 0000:2b:00.0, compute capability: 7.5)\n",
      "2021-04-03 11:55:13.778159: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2021-04-03 11:55:13.794562: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:196] None of the MLIR optimization passes are enabled (registered 0 passes)\n",
      "2021-04-03 11:55:14.883921: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:55:14.883947: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:55:14.883954: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:55:14.883960: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:55:14.883966: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:55:14.883971: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:55:14.883977: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:55:14.883983: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:55:14.883987: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:55:14.884071: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:55:14.884109: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-04-03 11:55:14.884114: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n",
      "2021-04-03 11:55:14.884117: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n",
      "2021-04-03 11:55:14.884182: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6611 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2070 SUPER, pci bus id: 0000:2b:00.0, compute capability: 7.5)\n",
      "2021-04-03 11:55:14.884197: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x00000224AC2B1908>, because it is not built.\n",
      "W0403 11:55:15.360029 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.meta_architectures.ssd_meta_arch.SSDMetaArch object at 0x00000224AC2B1908>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x00000224D6D42B00>, because it is not built.\n",
      "W0403 11:55:15.925411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x00000224D6D42B00>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6CEA748>, because it is not built.\n",
      "W0403 11:55:15.925411 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6CEA748>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D4763198>, because it is not built.\n",
      "W0403 11:55:15.925411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D4763198>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x00000224D4763D68>, because it is not built.\n",
      "W0403 11:55:15.925411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x00000224D4763D68>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D01A90>, because it is not built.\n",
      "W0403 11:55:15.925411 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D01A90>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D01358>, because it is not built.\n",
      "W0403 11:55:15.925411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D01358>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x00000224D6D015C0>, because it is not built.\n",
      "W0403 11:55:15.925411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x00000224D6D015C0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6CE36D8>, because it is not built.\n",
      "W0403 11:55:15.925411 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6CE36D8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6CE3CF8>, because it is not built.\n",
      "W0403 11:55:15.925411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6CE3CF8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x00000224D6CE3F98>, because it is not built.\n",
      "W0403 11:55:15.925411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.convolutional.SeparableConv2D object at 0x00000224D6CE3F98>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6CB2470>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6CB2470>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D477FDD8>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D477FDD8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D57390>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D57390>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D576D8>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D576D8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D6F390>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D6F390>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D6F630>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D6F630>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D6FCF8>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D6FCF8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D4753320>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D4753320>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D47534A8>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D47534A8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D5F550>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D5F550>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D4774908>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D4774908>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D46CBD68>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D46CBD68>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D46CBDA0>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D46CBDA0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D46CB7B8>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D46CB7B8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D46CB8D0>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D46CB8D0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D26828>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D26828>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D26940>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D26940>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D262E8>, because it is not built.\n",
      "W0403 11:55:15.926413 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D262E8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D12B70>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D12B70>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D088D0>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D088D0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D08550>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D08550>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D08F60>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D08F60>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D08CF8>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D08CF8>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D08710>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D08710>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D086A0>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D086A0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D0C320>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D0C320>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D72320>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D72320>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D37748>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D37748>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D37240>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D37240>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D376A0>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D376A0>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D37710>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D37710>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D76198>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D76198>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D76550>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <object_detection.core.freezable_batch_norm.FreezableBatchNorm object at 0x00000224D6D76550>, because it is not built.\n",
      "WARNING:tensorflow:Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D766A0>, because it is not built.\n",
      "W0403 11:55:15.927411 15552 save_impl.py:78] Skipping full serialization of Keras layer <tensorflow.python.keras.layers.core.Lambda object at 0x00000224D6D766A0>, because it is not built.\n",
      "2021-04-03 11:55:22.118760: W tensorflow/python/util/util.cc:348] Sets are not currently considered sequences, but this may change in the future, so consider avoiding using them.\n",
      "2021-04-03 11:55:23.021692: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:55:23.021718: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:55:23.021724: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:55:23.021731: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:55:23.021737: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:55:23.021742: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:55:23.021748: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:55:23.021754: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:55:23.021758: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:55:23.021783: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:55:23.021821: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
      "2021-04-03 11:55:23.021825: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n",
      "2021-04-03 11:55:23.021828: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n",
      "2021-04-03 11:55:23.021886: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6611 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2070 SUPER, pci bus id: 0000:2b:00.0, compute capability: 7.5)\n",
      "2021-04-03 11:55:23.021901: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:55:27.221577 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:55:27.221577 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4F28>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A46D8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4518>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:55:27.222574 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4F28>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A46D8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4518>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095EB8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095C88>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095D68>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:55:27.222574 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095EB8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095C88>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095D68>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4F28>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A46D8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4518>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:55:29.965919 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4F28>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A46D8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4518>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095EB8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095C88>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095D68>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:55:29.965919 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095EB8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095C88>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095D68>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:55:29.965919 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:55:29.965919 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:55:29.965919 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:55:29.966920 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "W0403 11:55:32.109875 15552 save.py:241] Found untraced functions such as WeightSharedConvolutionalBoxPredictor_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxPredictor_layer_call_fn, WeightSharedConvolutionalBoxHead_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxHead_layer_call_fn, WeightSharedConvolutionalBoxPredictor_layer_call_fn while saving (showing 5 of 155). These functions will not be directly callable after loading.\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:55:32.256875 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:55:32.256875 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4F28>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A46D8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4518>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:55:32.256875 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4F28>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A46D8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4518>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095EB8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095C88>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095D68>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:55:32.257873 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095EB8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095C88>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095D68>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4F28>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A46D8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4518>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:55:32.455873 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4F28>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A46D8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4518>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095EB8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095C88>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095D68>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:55:32.455873 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095EB8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095C88>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095D68>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:55:32.455873 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:55:32.455873 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:55:32.456872 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:55:32.456872 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "W0403 11:55:32.827284 15552 save.py:241] Found untraced functions such as WeightSharedConvolutionalBoxPredictor_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxPredictor_layer_call_fn, WeightSharedConvolutionalBoxHead_layer_call_and_return_conditional_losses, WeightSharedConvolutionalBoxHead_layer_call_fn, WeightSharedConvolutionalBoxPredictor_layer_call_fn while saving (showing 5 of 155). These functions will not be directly callable after loading.\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:55:35.860894 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C208>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C2E8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A05C550>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:55:35.860894 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A860>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A5F8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A02A748>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4F28>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A46D8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4518>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "I0403 11:55:35.860894 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4F28>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A46D8>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A0A4518>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], False), {}).\n",
      "INFO:tensorflow:Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095EB8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095C88>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095D68>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "I0403 11:55:35.860894 15552 def_function.py:1170] Unsupported signature for serialization: (([(<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095EB8>, TensorSpec(shape=(None, 40, 40, 32), dtype=tf.float32, name='image_features/0/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095C88>, TensorSpec(shape=(None, 20, 20, 96), dtype=tf.float32, name='image_features/1/1')), (<tensorflow.python.framework.func_graph.UnknownArgument object at 0x000002269A095D68>, TensorSpec(shape=(None, 10, 10, 1280), dtype=tf.float32, name='image_features/2/1'))], True), {}).\n",
      "INFO:tensorflow:Assets written to: Tensorflow\\workspace\\models\\my_ssd_mobnet\\tfliteexport\\saved_model\\assets\n",
      "I0403 11:55:36.624916 15552 builder_impl.py:775] Assets written to: Tensorflow\\workspace\\models\\my_ssd_mobnet\\tfliteexport\\saved_model\\assets\n"
     ]
    }
   ],
   "source": [
    "!{command}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "id": "iJfYMbN6pfDL"
   },
   "outputs": [],
   "source": [
    "FROZEN_TFLITE_PATH = os.path.join(paths['TFLITE_PATH'], 'saved_model')\n",
    "TFLITE_MODEL = os.path.join(paths['TFLITE_PATH'], 'saved_model', 'detect.tflite')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "command = \"tflite_convert \\\n",
    "--saved_model_dir={} \\\n",
    "--output_file={} \\\n",
    "--input_shapes=1,300,300,3 \\\n",
    "--input_arrays=normalized_input_image_tensor \\\n",
    "--output_arrays='TFLite_Detection_PostProcess','TFLite_Detection_PostProcess:1','TFLite_Detection_PostProcess:2','TFLite_Detection_PostProcess:3' \\\n",
    "--inference_type=FLOAT \\\n",
    "--allow_custom_ops\".format(FROZEN_TFLITE_PATH, TFLITE_MODEL, )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "E8GwUeoFpfDL",
    "outputId": "fac43ea4-cc85-471b-a362-e994b06fd583"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tflite_convert --saved_model_dir=Tensorflow\\workspace\\models\\my_ssd_mobnet\\tfliteexport\\saved_model --output_file=Tensorflow\\workspace\\models\\my_ssd_mobnet\\tfliteexport\\saved_model\\detect.tflite --input_shapes=1,300,300,3 --input_arrays=normalized_input_image_tensor --output_arrays='TFLite_Detection_PostProcess','TFLite_Detection_PostProcess:1','TFLite_Detection_PostProcess:2','TFLite_Detection_PostProcess:3' --inference_type=FLOAT --allow_custom_ops\n"
     ]
    }
   ],
   "source": [
    "print(command)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Nbd7gqHMpfDL",
    "outputId": "7c8fe6d5-2415-4641-8548-39d425c202f7"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-04-03 11:55:38.653963: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:55:41.159460: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2021-04-03 11:55:41.160164: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library nvcuda.dll\n",
      "2021-04-03 11:55:41.183623: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:55:41.183649: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:55:41.187402: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:55:41.187424: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:55:41.189452: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:55:41.190052: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:55:41.193535: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:55:41.194888: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:55:41.195377: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:55:41.195440: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:55:41.195644: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
      "2021-04-03 11:55:41.196333: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:55:41.196347: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:55:41.196353: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:55:41.196361: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:55:41.196366: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:55:41.196373: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:55:41.196378: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:55:41.196385: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:55:41.196389: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:55:41.196414: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:55:41.624429: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
      "2021-04-03 11:55:41.624448: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n",
      "2021-04-03 11:55:41.624452: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n",
      "2021-04-03 11:55:41.624581: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6611 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2070 SUPER, pci bus id: 0000:2b:00.0, compute capability: 7.5)\n",
      "2021-04-03 11:55:41.624988: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2021-04-03 11:55:50.392224: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:316] Ignored output_format.\n",
      "2021-04-03 11:55:50.392245: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:319] Ignored drop_control_dependency.\n",
      "2021-04-03 11:55:50.392250: W tensorflow/compiler/mlir/lite/python/tf_tfl_flatbuffer_helpers.cc:325] Ignored change_concat_input_ranges.\n",
      "2021-04-03 11:55:50.392901: I tensorflow/cc/saved_model/reader.cc:32] Reading SavedModel from: Tensorflow\\workspace\\models\\my_ssd_mobnet\\tfliteexport\\saved_model\n",
      "2021-04-03 11:55:50.467288: I tensorflow/cc/saved_model/reader.cc:55] Reading meta graph with tags { serve }\n",
      "2021-04-03 11:55:50.467341: I tensorflow/cc/saved_model/reader.cc:93] Reading SavedModel debug info (if present) from: Tensorflow\\workspace\\models\\my_ssd_mobnet\\tfliteexport\\saved_model\n",
      "2021-04-03 11:55:50.467439: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
      "2021-04-03 11:55:50.467446: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      \n",
      "2021-04-03 11:55:50.467452: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n",
      "2021-04-03 11:55:50.748887: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:196] None of the MLIR optimization passes are enabled (registered 0 passes)\n",
      "2021-04-03 11:55:50.790035: I tensorflow/cc/saved_model/loader.cc:206] Restoring SavedModel bundle.\n",
      "2021-04-03 11:55:51.366069: I tensorflow/cc/saved_model/loader.cc:190] Running initialization op on SavedModel bundle at path: Tensorflow\\workspace\\models\\my_ssd_mobnet\\tfliteexport\\saved_model\n",
      "2021-04-03 11:55:51.623706: I tensorflow/cc/saved_model/loader.cc:277] SavedModel load for tags { serve }; Status: success: OK. Took 1230797 microseconds.\n",
      "2021-04-03 11:55:52.694959: I tensorflow/compiler/mlir/tensorflow/utils/dump_mlir_util.cc:194] disabling MLIR crash reproducer, set env var `MLIR_CRASH_REPRODUCER_DIRECTORY` to enable.\n",
      "2021-04-03 11:55:53.295613: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties: \n",
      "pciBusID: 0000:2b:00.0 name: GeForce RTX 2070 SUPER computeCapability: 7.5\n",
      "coreClock: 1.785GHz coreCount: 40 deviceMemorySize: 8.00GiB deviceMemoryBandwidth: 417.29GiB/s\n",
      "2021-04-03 11:55:53.295643: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudart64_110.dll\n",
      "2021-04-03 11:55:53.295652: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublas64_11.dll\n",
      "2021-04-03 11:55:53.295658: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cublasLt64_11.dll\n",
      "2021-04-03 11:55:53.295666: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cufft64_10.dll\n",
      "2021-04-03 11:55:53.295671: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library curand64_10.dll\n",
      "2021-04-03 11:55:53.295678: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusolver64_10.dll\n",
      "2021-04-03 11:55:53.295683: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cusparse64_11.dll\n",
      "2021-04-03 11:55:53.295689: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library cudnn64_8.dll\n",
      "2021-04-03 11:55:53.295714: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1862] Adding visible gpu devices: 0\n",
      "2021-04-03 11:55:53.295753: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:\n",
      "2021-04-03 11:55:53.295759: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267]      0 \n",
      "2021-04-03 11:55:53.295762: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0:   N \n",
      "2021-04-03 11:55:53.295817: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1406] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 6611 MB memory) -> physical GPU (device: 0, name: GeForce RTX 2070 SUPER, pci bus id: 0000:2b:00.0, compute capability: 7.5)\n",
      "2021-04-03 11:55:53.295834: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set\n"
     ]
    }
   ],
   "source": [
    "!{command}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "5NQqZRdA21Uc"
   },
   "source": [
    "# 13. Zip and Export Models "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "tTVTGCQp2ZJJ"
   },
   "outputs": [],
   "source": [
    "!tar -czf models.tar.gz {paths['CHECKPOINT_PATH']}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "whShhB0x3PYJ",
    "outputId": "b773201d-35c9-46a8-b893-4a76bd4d5d97"
   },
   "outputs": [],
   "source": [
    "from google.colab import drive\n",
    "drive.mount('/content/drive')"
   ]
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "name": "3. Training and Detection.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "tfod",
   "language": "python",
   "name": "tfod"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}