python摄像头采集图像与库中图像分析，输出人脸姓名或unknown

摄像头采集图像与库中图像分析，输出人脸姓名或unknown

#摄像头采集图像与库中图像分析，输出人脸姓名或unknownimport face_recognitionimport cv2video_capture = cv2.VideoCapture(0)# Load a sample picture and learn how to recognize it.chenglong_image = face_recognition.load_image_file("C:/Users/hp/Pictures/chenglong.jpg")chenglong_face_encoding = face_recognition.face_encodings(chenglong_image)[0]# Load a second sample picture and learn how to recognize it.zaixia_image = face_recognition.load_image_file("C:/Users/hp/Pictures/zaixia.jpg")zaixia_face_encoding = face_recognition.face_encodings(zaixia_image)[0]# Create arrays of known face encodings and their namesknown_face_encodings = [ chenglong_face_encoding, zaixia_face_encoding]known_face_names = [ "ChengLong", "mike"]# Initialize some variablesface_locations = []face_encodings = []face_names = []process_this_frame = Truewhile True: # Grab a single frame of video ret, frame = video_capture.read() # Resize frame of video to 1/4 size for faster face recognition processing small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25) # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses) rgb_small_frame = small_frame[:, :, ::-1] # Only process every other frame of video to save time if process_this_frame: # Find all the faces and face encodings in the current frame of video 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: # See if the face is a match for the known face(s) matches = face_recognition.compare_faces(known_face_encodings, face_encoding) name = "Unknown" # If a match was found in known_face_encodings, just use the first one. if True in matches: first_match_index = matches.index(True) name = known_face_names[first_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): # Scale back up face locations since the frame we detected in was scaled to 1/4 size top *= 4 right *= 4 bottom *= 4 left *= 4 # Draw a box around the face cv2.rectangle(frame, (left, top), (right, bottom), (0, 255, 0), 2) # Draw a label with a name below the face cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 255, 0), 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-exist', frame) # Hit 'q' on the keyboard to quit! if cv2.waitKey(1) & 0xFF == ord('q'): break# Release handle to the webcamvideo_capture.release()cv2.destroyAllWindows()