detecting license plates and cars in a video using YOLO NAS and YOLOv5
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Updated
Jun 20, 2023 - Jupyter Notebook
detecting license plates and cars in a video using YOLO NAS and YOLOv5
Object Detection and Localization using Image processing and Machine learning Algorithms like YOLO
Object Detection, YoloV4, Streamlit, DNN model, OpenCV, Python
Object detection using the YOLO (You Only Look Once) algorithm is a popular deep-learning approach that allows for real-time, efficient, and accurate detection of multiple objects in an image or video stream. YOLOv7.cfg and YOLOv3.weights are specific configurations and pre-trained weights for two versions of the YOLO algorithm.
CNN to detect, track and count passing vehicle types
Project that uses Yolov8 as license plate detector, followed by a filter that is got selecting from a filters collection with a code assigned to each filter and predicting what filter with a CNN process
🚀 YOLOv8: Extended Edition is a fork of Ultralytics YOLOv8 repository. but with new features focuses on Automotive Vechicles 🚗.
This project detects the car license plate through a free Roboflow API, submits the detected car license plate image to a battery of filters and obtains the car license plate number using paddleOcr
Yolo is used to detect objects and label them using coco dataset. The position with its accuracy are displayed using bounding boxes around the objects. This is a pre trained model with weights anf cfg file in it.
Training a computer vision algorithm on a BDD100K dataset for autonomous driving, and applying it to perform object detection task.
Semi-Supervised | Pseudo Labeling pipeline with one-stage object detection models
A multi-class classification, Yolo algorithm
Yolo algorithm applied on a video file so as to detect cars, traffic lights and a few other classes.
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