This is a Python project that performs dataset analysis for object detection using YOLO (You Only Look Once) algorithm. It utilizes the power of NumPy library to process and analyze the dataset.

To use the Object Detection YOLO Dataset Analysis, follow these steps:

1. Clone the repository: git clone /~https://github.com/Omerkdr/ObjectDetectionYoloDatasetAnalysisPythonNumpy.git

2. Change into the project directory: cd ObjectDetectionYoloDatasetAnalysisPythonNumpy

3. Install the required dependencies: pip install -r requirements.txt

To run the dataset analysis, execute the following command in your terminal:

python dataset_analysis.py

This will run the dataset analysis script and provide insights into the object annotations, class distribution, and other relevant statistics.

Contributions are welcome! If you have any ideas, suggestions, or bug reports, please open an issue on the GitHub repository. If you would like to contribute code, follow these steps:

1. Fork the repository.
2. Create a new branch: git checkout -b feature/my-new-feature.
3. Make your changes and commit them: git commit -am 'Add new feature'.
4. Push to the branch: git push origin feature/my-new-feature.
5. Submit a pull request.

This project is licensed under the MIT License.

If you have any questions or feedback, feel free to reach out to me at omerkdr8@outlook.com. You can also find me on GitHub at Omerkdr.