retina-face

import cv2 import os from retinaface import RetinaFace # Create a dummy image for demonstration if it doesn't exist image_path = "test_image.jpg" if not os.path.exists(image_path): # Create a blank white image dummy_image = 255 * (1 + 0 * range(100)).reshape(100, 100, 1) # White image dummy_image = cv2.cvtColor(dummy_image, cv2.COLOR_GRAY2BGR) cv2.imwrite(image_path, dummy_image) print(f"Created a dummy image at {image_path}") try: # Detect faces in an image # The detect_faces function can accept an image path or a NumPy array. faces = RetinaFace.detect_faces(image_path) if isinstance(faces, dict): for face_name, face_data in faces.items(): print(f"--- {face_name} ---") print(f" Score: {face_data['score']}") print(f" Facial Area: {face_data['facial_area']}") print(f" Landmarks: {face_data['landmarks']}") elif faces is None: print(f"No faces detected in {image_path}") else: print("Unexpected output format from RetinaFace.detect_faces") # Optional: Draw detections on the image and display (requires opencv-python-headless or opencv-python) # img = cv2.imread(image_path) # if img is not None: # result_img = RetinaFace.draw_landmarks(img, faces) # cv2.imshow("Detected Faces", result_img) # cv2.waitKey(0) # cv2.destroyAllWindows() except Exception as e: print(f"An error occurred: {e}")