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FaceRecognitionCode.py
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FaceRecognitionCode.py
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video_capture = cv2.VideoCapture(0)
while True:
ret, frame = video_capture.read()
small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
rgb_small_frame = small_frame[:, :, ::-1]
if process_this_frame:
face_locations = face_recognition.face_locations( rgb_small_frame)
face_encodings = face_recognition.face_encodings( rgb_small_frame, face_locations)
face_names = []
for face_encoding in face_encodings:
matches = face_recognition.compare_faces (faces_encodings, face_encoding)
name = "Unknown"
face_distances = face_recognition.face_distance( faces_encodings, face_encoding)
best_match_index = np.argmin(face_distances)
if matches[best_match_index]:
name = faces_names[best_match_index]
face_names.append(name)
process_this_frame = not process_this_frame
# Display the results
for (top, right, bottom, left), name in zip(face_locations, face_names):
top *= 4
right *= 4
bottom *= 4
left *= 4
# Draw a rectangle around the face
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)
# Input text label with a name below the face
cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
font = cv2.FONT_HERSHEY_DUPLEX
cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)
# Display the resulting image
cv2.imshow('Video', frame)
# Hit 'q' on the keyboard to quit!
if cv2.waitKey(1) & 0xFF == ord('q'):
break