deepface

import os import cv2 import numpy as np from deepface import DeepFace # Create dummy image files for demonstration # In a real scenario, these would be actual image paths img1_path = "img1.jpg" img2_path = "img2.jpg" person_img_path = "person.jpg" # Generate dummy images (replace with actual image files for real usage) if not os.path.exists(img1_path): cv2.imwrite(img1_path, np.zeros((224, 224, 3), dtype=np.uint8) + 100) if not os.path.exists(img2_path): cv2.imwrite(img2_path, np.zeros((224, 224, 3), dtype=np.uint8) + 150) if not os.path.exists(person_img_path): cv2.imwrite(person_img_path, np.zeros((224, 224, 3), dtype=np.uint8) + 200) try: # Verify two faces result_verify = DeepFace.verify(img1_path, img2_path) print("Face Verification Result:", result_verify) # Analyze facial attributes analysis_result = DeepFace.analyze(person_img_path, actions=['age', 'gender', 'emotion', 'race']) print("\nFacial Analysis Result:", analysis_result) # Generate a face embedding (representation) embedding = DeepFace.represent(img1_path) print("\nFace Embedding (first 5 elements of first face):", embedding[0]['embedding'][:5]) except Exception as e: print(f"An error occurred: {e}") print("Please ensure you have valid image files at the specified paths.") print("Also, DeepFace downloads models on first run, requiring an internet connection.") # Clean up dummy images (optional) # os.remove(img1_path) # os.remove(img2_path) # os.remove(person_img_path)