Files
uniface/scripts
Yakhyokhuja Valikhujaev 54b769c0f1 feat: Add Face Parsing model BiSeNet model trained on CelebMask dataset (#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
2025-12-14 21:13:53 +09:00
..

Scripts

Scripts for testing UniFace features.

Available Scripts

Script Description
run_detection.py Face detection on image or webcam
run_age_gender.py Age and gender prediction
run_emotion.py Emotion detection (7 or 8 emotions)
run_gaze_estimation.py Gaze direction estimation
run_landmarks.py 106-point facial landmark detection
run_recognition.py Face embedding extraction and comparison
run_face_analyzer.py Complete face analysis (detection + recognition + attributes)
run_face_search.py Real-time face matching against reference
run_video_detection.py Face detection on video files
batch_process.py Batch process folder of images
download_model.py Download model weights
sha256_generate.py Generate SHA256 hash for model files

Usage Examples

# Face detection
python scripts/run_detection.py --image assets/test.jpg
python scripts/run_detection.py --webcam

# Age and gender
python scripts/run_age_gender.py --image assets/test.jpg
python scripts/run_age_gender.py --webcam

# Emotion detection
python scripts/run_emotion.py --image assets/test.jpg
python scripts/run_emotion.py --webcam

# Gaze estimation
python scripts/run_gaze_estimation.py --image assets/test.jpg
python scripts/run_gaze_estimation.py --webcam

# Landmarks
python scripts/run_landmarks.py --image assets/test.jpg
python scripts/run_landmarks.py --webcam

# Face recognition (extract embedding)
python scripts/run_recognition.py --image assets/test.jpg

# Face comparison
python scripts/run_recognition.py --image1 face1.jpg --image2 face2.jpg

# Face search (match webcam against reference)
python scripts/run_face_search.py --image reference.jpg

# Video processing
python scripts/run_video_detection.py --input video.mp4 --output output.mp4

# Batch processing
python scripts/batch_process.py --input images/ --output results/

# Download models
python scripts/download_model.py --model-type retinaface
python scripts/download_model.py  # downloads all

Common Options

Option Description
--image Path to input image
--webcam Use webcam instead of image
--method Choose detector: retinaface, scrfd, yolov5face
--threshold Visualization confidence threshold (default: 0.25)
--save_dir Output directory (default: outputs)

Quick Test

python scripts/run_detection.py --image assets/test.jpg