face_recognition 实时人脸识别
目标 识别进入摄像头的人是谁 face_recognition face_recognition 是github上一个非常有名气的人脸识别开源工具包，我们可以通过以下指令安装到python环境内 $ pip install face_recognition 代码的设计思路 加载认识的人脸图 ray_image = face_recognition.load_image_file("ray.jpg") ray_face_encoding = face_recognition.face_encodings(ray_image)[0] 将认识的人脸变量加到数组内 known_face_encodings = [ ray_face_encoding ] known_face_names = [ "Ray" ] 全部代码如下所示： import face_recognition import cv2 video_capture = cv2.VideoCapture(0) ray_image = face_recognition.load_image_file("ray.jpg") ray_face_encoding = face_recognition.face_encodings(ray_image)[0] pinky_image = face_recognition.load_image_file("pinky.jpg") pinky_face_encoding = face_recognition.face_encodings(ray_image)[0] # Create arrays of known face encodings and their names known_face_encodings = [ ray_face_encoding, pinky_face_encoding ] known_face_names = [ "Ray", "Pinky" ] # Initialize some variables face_locations = [] face_encodings = [] face_names = [] process_this_frame = True while 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, 0, 255), 2) # Draw a 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 # Release handle to the webcam video_capture.release() cv2.destroyAllWindows()
