Face Identification is a Python-based project designed for Raspberry Pi, utilizing OpenCV libraries for accurate face recognition.
This project enables face identification functionality on Raspberry Pi, allowing users to capture images of faces, train the model, and perform real-time face recognition.
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Capture Headshots: Use the "headshots_picam" script to capture images of faces. Save these images in a folder named after each individual's name within the "data" directory.
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Model Training: Run the "train_model" script to train the face recognition model. This step is crucial for the model to accurately identify faces based on the provided images.
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Face Identification: Execute the "facial_req" script to perform face identification in real-time. The trained model will compare input images with the stored data to recognize faces.
To utilize the face identification functionality:
- Ensure the Raspberry Pi is connected to a compatible camera module.
- Run the scripts as per the provided instructions.
- Follow on-screen prompts for capturing headshots, training the model, and performing face identification.
- This project assumes basic familiarity with Raspberry Pi setup and Python programming.
- Ensure proper lighting conditions and camera placement for optimal face recognition accuracy.
- Additional customization and fine-tuning of the model parameters may be required based on specific use cases and environments.
Contributions to this project, including bug fixes, feature enhancements, and documentation improvements, are welcome. Please refer to the contribution guidelines outlined in the repository for more information.
This project is licensed under the MIT License, granting users the freedom to modify, distribute, and utilize the codebase as per their requirements.