【PYTHON OPENCV】This script makes used of face_recognition package to calculate the 128D descriptor to be used for face recognition and compare the faces using some distance metrics

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This script makes used of face_recognition package to calculate the 128D descriptor to be used for face recognition and compare the faces using some distance metrics """ # Import required packages: import face_recognition # Load known images (remember that these images are loaded in RGB order): known_image_1 = face_recognition.load_image_file("jared_1.jpg") known_image_2 = face_recognition.load_image_file("jared_2.jpg") known_image_3 = face_recognition.load_image_file("jared_3.jpg") known_image_4 = face_recognition.load_image_file("obama.jpg") # Crate names for each loaded image: names = ["jared_1.jpg", "jared_2.jpg", "jared_3.jpg", "obama.jpg"] # Load unknown image (this image is going to be compared against all the previous loaded images): unknown_image = face_recognition.load_image_file("jared_4.jpg") # Calculate the encodings for every of the images: known_image_1_encoding = face_recognition.face_encodings(known_image_1)[0] known_image_2_encoding = face_recognition.face_encodings(known_image_2)[0] known_image_3_encoding = face_recognition.face_encodings(known_image_3)[0] known_image_4_encoding = face_recognition.face_encodings(known_image_4)[0] known_encodings = [known_image_1_encoding, known_image_2_encoding, known_image_3_encoding, known_image_4_encoding] unknown_encoding = face_recognition.face_encodings(unknown_image)[0] # Compare the faces: results = face_recognition.compare_faces(known_encodings, unknown_encoding) # Print the results: print(results)