Skip to content

thangktran/VisDetect

 
 

Repository files navigation

Rapeseed Detection and Spray Painting Robot

This repository contains the software for a robot that detects specific shapes and colors to simulate the detection of male rapeseed plants. The robot moves towards the detected plants and controls a nozzle to spray paint them. The software is divided into three modules: control, vision, and motion. The software is designed to be deployed on an NVIDIA Jetson platform.

Table of Contents

Features

  • Detect specific shapes and colors representing male rapeseed plants using computer vision algorithms.
  • Control the robot's motion towards the detected plants.
  • Operate a spray nozzle to paint the detected plants.
  • Coordinate between control, vision, and motion modules to perform the task.
  • Deploy on NVIDIA Jetson platform for real-time processing.

Requirements

  • Python 3.6 or higher
  • OpenCV 4.x
  • NumPy
  • NVIDIA Jetson platform (for deployment)

Installation

  1. Clone the repository to your local machine or Jetson device:

git clone https://github.com/yourusername/VisDetect.git

  1. Change to the repository's directory:

cd rapeseed-detection-robot

  1. (Optional) Create a virtual environment for the project:

python3 -m venv venv source venv/bin/activate

  1. Install the required Python packages:

pip install -r requirements.txt

Usage

  1. Ensure the robot and camera hardware are connected and configured properly.
  2. Run the main script to start the rapeseed detection and spray painting process:

python main.py

  1. Monitor the robot's progress and adjust parameters as needed.

Contributing

Contributions to this project are welcome. To contribute, please follow these steps:

  1. Fork the repository.
  2. Create a new branch with a descriptive name.
  3. Commit your changes to the branch.
  4. Create a pull request describing the changes you've made.

Please ensure your code follows the project's style guidelines and passes all tests.

License

This project is licensed under the MIT License. Please refer to the LICENSE file for more information.

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 95.4%
  • Python 4.6%