32 lines
1.2 KiB
Python
32 lines
1.2 KiB
Python
import face_recognition
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import cv2
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import os
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image_load = 'image1.jpg'
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# image_data = 'faces/rika.png'
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image_data = 'faces/rika.png'
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# Load the images
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image_load_path = os.path.join(os.getcwd(), image_load)
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image_data_path = os.path.join(os.getcwd(), image_data)
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image_load = face_recognition.load_image_file(image_load_path)
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image_data = face_recognition.load_image_file(image_data_path)
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# Find the face locations and encodings in each image
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image_load_face_locations = face_recognition.face_locations(image_load)
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image_load_face_encodings = face_recognition.face_encodings(image_load, image_load_face_locations)
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image_data_face_locations = face_recognition.face_locations(image_data)
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image_data_face_encodings = face_recognition.face_encodings(image_data, image_data_face_locations)
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# Compare the face encodings
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matches = face_recognition.compare_faces(image_data_face_encodings, image_load_face_encodings[0])
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# Draw boxes around the faces in the image_load image
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for (top, right, bottom, left), match in zip(image_load_face_locations, matches):
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if match:
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cv2.rectangle(image_load, (left, top), (right, bottom), (0, 0, 255), 2)
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# Display the image with the boxes around the matching faces
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cv2.imshow('Image', image_load)
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cv2.waitKey(0)
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cv2.destroyAllWindows() |