Welcome to the Face-Tagger Organization. We specialize in facial recognition and image classification, aiming to provide seamless solutions for classifying photos containing specific individuals from a collection of images. Our core components consist of the facetagger-lib library and its web-based frontend sample, facetagger-fe.
Face Tagger Library is a Python package designed for robust face recognition and photo classification.
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Key Features:
- Identify and differentiate faces in multiple images.
- Group photos based on identified individuals.
- Optimized performance with GPU acceleration.
- Simple APIs for integration into various applications.
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Installation:
pip install face-tagger
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Usage: Start by loading images, initializing the Face Tagger, and classifying images. Check out the detailed guide here.
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Contributing: We welcome contributions! Please review the contribution guide for more details.
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License: MIT
FaceTagger-FE offers a web-based frontend sample to showcase the capabilities of the FaceTagger library.
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Key Features:
- Seamless navigation using
react-router-dom. - User authentication for accessing the service.
- Drag & drop interface for image uploads.
- Real-time grouping & image classification display.
- Seamless navigation using
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Getting Started: Experience the frontend by cloning the repository, installing dependencies, and launching the sample. See detailed steps.
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License: MIT
For issues, suggestions, or feature requests, kindly raise an issue in the respective repository.
