Tags: yakhyo/uniface
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feat: Add BiSeNet face parsing model (#36) * Add BiSeNet face parsing implementation * Add parsing model weights configuration * Export BiSeNet in main package * Add face parsing tests * Add face parsing examples and script * Bump version to 1.5.0 * Update documentation for face parsing * Fix face parsing notebook to use lips instead of mouth * chore: Update the face parsing example * fix: Fix model argument to use Enum * ref: Move vis_parsing_map function into visualization.py * docs: Update README.md
feat: Add Face Parsing model BiSeNet model trained on CelebMask datas… …et (#35) * Add BiSeNet face parsing implementation * Add parsing model weights configuration * Export BiSeNet in main package * Add face parsing tests * Add face parsing examples and script * Bump version to 1.5.0 * Update documentation for face parsing * Fix face parsing notebook to use lips instead of mouth * chore: Update the face parsing example * fix: Fix model argument to use Enum * ref: Move vis_parsing_map function into visualization.py * docs: Update README.md
fix: Fix type conversion and remove redundant type conversion (#29) * ref: Remove type conversion and update face class * fix: change the type to float32 * chore: Update all examples, testing with latest version * docs: Update docs reflecting the recent changes
feat: Update examples and some minor changes to UniFace API (#28) * chore: Style changes and create jupyter notebook template * docs: Update docstring for detection * feat: Keyword only for common parameters: model_name, conf_thresh, nms_thresh, input_size * chore: Update drawing and let the conf text optional for drawing * feat: add fancy bbox draw * docs: Add examples of using UniFace * feat: Add version to all examples
feat: Enhace emotion inference speed on ARM and add FaceAnalyzer, Fac… …e classes for ease of use. (#25) * feat: Update linting and type annotations, return types in detect * feat: add face analyzer and face classes * chore: Update the format and clean up some docstrings * docs: Update usage documentation * feat: Change AgeGender model output to 0, 1 instead of string (Female, Male) * test: Update testing code * feat: Add Apple silicon backend for torchscript inference * feat: Add face analyzer example and add run emotion for testing
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