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* 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
75 lines
2.3 KiB
Markdown
75 lines
2.3 KiB
Markdown
# Scripts
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Scripts for testing UniFace features.
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## Available Scripts
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| Script | Description |
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|--------|-------------|
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| `run_detection.py` | Face detection on image or webcam |
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| `run_age_gender.py` | Age and gender prediction |
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| `run_emotion.py` | Emotion detection (7 or 8 emotions) |
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| `run_landmarks.py` | 106-point facial landmark detection |
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| `run_recognition.py` | Face embedding extraction and comparison |
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| `run_face_analyzer.py` | Complete face analysis (detection + recognition + attributes) |
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| `run_face_search.py` | Real-time face matching against reference |
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| `run_video_detection.py` | Face detection on video files |
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| `batch_process.py` | Batch process folder of images |
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| `download_model.py` | Download model weights |
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| `sha256_generate.py` | Generate SHA256 hash for model files |
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## Usage Examples
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```bash
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# Face detection
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python scripts/run_detection.py --image assets/test.jpg
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python scripts/run_detection.py --webcam
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# Age and gender
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python scripts/run_age_gender.py --image assets/test.jpg
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python scripts/run_age_gender.py --webcam
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# Emotion detection
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python scripts/run_emotion.py --image assets/test.jpg
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python scripts/run_emotion.py --webcam
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# Landmarks
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python scripts/run_landmarks.py --image assets/test.jpg
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python scripts/run_landmarks.py --webcam
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# Face recognition (extract embedding)
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python scripts/run_recognition.py --image assets/test.jpg
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# Face comparison
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python scripts/run_recognition.py --image1 face1.jpg --image2 face2.jpg
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# Face search (match webcam against reference)
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python scripts/run_face_search.py --image reference.jpg
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# Video processing
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python scripts/run_video_detection.py --input video.mp4 --output output.mp4
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# Batch processing
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python scripts/batch_process.py --input images/ --output results/
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# Download models
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python scripts/download_model.py --model-type retinaface
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python scripts/download_model.py # downloads all
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```
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## Common Options
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| Option | Description |
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|--------|-------------|
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| `--image` | Path to input image |
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| `--webcam` | Use webcam instead of image |
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| `--method` | Choose detector: `retinaface`, `scrfd`, `yolov5face` |
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| `--threshold` | Visualization confidence threshold (default: 0.25) |
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| `--save_dir` | Output directory (default: `outputs`) |
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## Quick Test
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```bash
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python scripts/run_detection.py --image assets/test.jpg
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```
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