Welcome to DeepLearning 0x02, a repository dedicated to advanced computer vision projects. This repository covers essential topics such as segmentation, object detection, and object tracking. All projects leverage powerful frameworks and libraries like PyTorch, OpenCV, and Ultralytics. More tools may be integrated as the projects evolve.
This repository includes:
- Segmentation: Projects that involve the division of an image into segments to identify and analyze objects or areas.
- Object Detection: Projects focused on detecting and classifying objects within images or videos.
- Object Tracking: Projects that track objects in real-time from video feeds, leveraging state-of-the-art algorithms.
We utilize:
- PyTorch: A powerful deep learning library for building and training neural networks.
- OpenCV: A popular library for computer vision tasks such as image processing and video manipulation.
- Ultralytics: A framework known for the YOLO (You Only Look Once) models, commonly used in real-time object detection.
To run the projects in this repository, you'll need the following dependencies:
pip install torch torchvision opencv-python ultralyticsAdditional dependencies may be required for future projects.
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Clone the repository:
git clone https://github.com/your-username/DeepLearning-0x02.git cd DeepLearning-0x02 -
Install the required packages:
pip install -r requirements.txt
Each project includes detailed instructions. To run a specific project:
- Navigate to the project folder.
- Follow the instructions in the README.md of that project.
Contributions are welcome! If you'd like to contribute, please fork the repository and submit a pull request.
- Fork the repository.
- Create a new feature branch.
- Make your changes and commit them.
- Push to your branch.
- Open a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.