45 lines
1.8 KiB
Python
45 lines
1.8 KiB
Python
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import face_recognition
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import cv2
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import os
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image_data_folder = 'faces/'
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# Load the images in the image_data_folder and save their face encodings in a list
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image_dataset = []
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for filename in os.listdir(image_data_folder):
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image_data_path = os.path.join(os.getcwd(), image_data_folder, filename)
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image_data = face_recognition.load_image_file(image_data_path)
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image_data_encoding = face_recognition.face_encodings(image_data)[0]
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image_dataset.append((filename, image_data_encoding))
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# Initialize the webcam
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video_capture = cv2.VideoCapture(-1)
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while True:
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# Capture a single frame from the webcam
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ret, frame = video_capture.read()
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# Find the face locations and encodings in the frame
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face_locations = face_recognition.face_locations(frame)
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face_encodings = face_recognition.face_encodings(frame, face_locations)
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# Compare the face encodings in the frame to the face encodings in image_dataset
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for (top, right, bottom, left), face_encoding in zip(face_locations, face_encodings):
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matches = face_recognition.compare_faces([x[1] for x in image_dataset], face_encoding, tolerance=0.55)
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if True in matches:
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# Find the name of the matching face
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name = image_dataset[matches.index(True)][0]
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# Draw a box around the face and show the name on the top right of the box
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cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
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cv2.putText(frame, name, (right, top), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
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# Display the resulting image
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cv2.imshow('Video', frame)
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# Exit the loop if the 'q' key is pressed
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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# Release the webcam and close all windows
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video_capture.release()
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cv2.destroyAllWindows()
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