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face-detection's Introduction

Face Detection

This is Deep Face Detection Model built from scratch.

Dependencies

This project makes use of several Python libraries and frameworks to achieve accurate face detection. Some of the key dependencies include:

  • TensorFlow: Deep learning library for model development.
  • NumPy: Essential for numerical operations and data manipulation.
  • OpenCV: Used for image processing and manipulation.
  • Albumentations: Employed for data augmentation to enhance model performance.
  • Label Me: A labeling tool used to annotate the training dataset.
  • Matplotlib: Used for visualizing the results and model performance.

Please ensure that you have these dependencies installed in your environment to run the project successfully.

Model Accuracy

Please note that while this face detection model is a functional and valuable tool, it may not be 100% accurate in all scenarios. Face detection is a challenging computer vision task, and the model's performance depends on factors such as lighting conditions, image quality, and the diversity of faces in our dataset.

Improvements in Progress: I am actively working on refining and improving the model's accuracy. My goal is to make it more robust and capable of handling a wider range of scenarios.

Contributions Welcome: I welcome contributions from the open-source community to help enhance the model's performance. If you have ideas, improvements, or bug fixes, please feel free to open an issue or submit a pull request.

I appreciate your understanding and patience as I continue to make this model more powerful and reliable for face detection tasks.

face-detection's People

Contributors

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