facexlib_retinaface_face_detection_quickstart.py

1import cv2
2import torch
3from facexlib.detection import init_detection_model
4
5def quickstart():
6    # 1. Choose device (CPU or GPU)
7    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
8
9    # 2. Initialize the detection model (RetinaFace with ResNet50)
10    # This will automatically download the pre-trained model weights
11    model = init_detection_model('retinaface_resnet50', device=device)
12
13    # 3. Read an image
14    img_path = 'input.jpg' # Replace with your image path
15    img = cv2.imread(img_path)
16
17    # 4. Perform face detection
18    # bboxes: [x1, y1, x2, y2, score, landmarks...]
19    with torch.no_grad():
20        bboxes = model.detect_faces(img, confidence_threshold=0.5)
21
22    # 5. Print results
23    if bboxes is not None:
24        for bbox in bboxes:
25            print(f"Face found with confidence {bbox[4]:.2f}: {bbox[:4]}")
26    else:
27        print("No faces detected.")
28
29if __name__ == '__main__':
30    quickstart()