Created
December 2, 2022 14:10
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face-unique
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| import cv2 | |
| import face_recognition | |
| # Open the video file | |
| video = cv2.VideoCapture("video.mp4") | |
| # Create an empty list to store the extracted faces | |
| faces = [] | |
| # Loop over the frames of the video | |
| while True: | |
| # Grab the current frame | |
| ret, frame = video.read() | |
| # If we are at the end of the video, break the loop | |
| if not ret: | |
| break | |
| # Convert the frame to RGB | |
| rgb_frame = frame[:, :, ::-1] | |
| # Use the face_recognition library to find all the faces in the frame | |
| face_locations = face_recognition.face_locations(rgb_frame) | |
| # Loop over the face locations | |
| for face_location in face_locations: | |
| # Extract the face from the frame and add it to the list of faces | |
| face = rgb_frame[face_location[0]:face_location[2], face_location[3]:face_location[1]] | |
| faces.append(face) | |
| # Convert the list of faces to a NumPy array | |
| faces = np.array(faces) | |
| # Save the array of faces to a file | |
| np.save("faces.npy", faces) |
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