Question

我正在使用face_recognition library来识别图像上的人物。根据{{3}}，它支持两种输入图像格式以进行进一步处理：RGB（8位，3通道）和L（黑白）。

我尝试使用

face_recognition.api.load_image_file(file, mode='RGB')

，没关系。但是我需要使用L模式，这就是重点。问题是mode ='RGB'生成numpy.array（x，y，3）而mode ='L'生成numpy.array（x，y）。

稍后应将数组输入face_recognition.face_locations和face_recognition.face_encodings函数。

如果将以L模式生成的数组放在face_encodings中，则会出现以下错误：


    TypeError: compute_face_descriptor(): incompatible function arguments. The following argument types are supported:
        1. (self: dlib.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),uint8], face: dlib.full_object_detection, num_jitters: int=0) -> dlib.vector
        2. (self: dlib.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),uint8], faces: dlib.full_object_detections, num_jitters: int=0) -> dlib.vectors
        3. (self: dlib.face_recognition_model_v1, batch_img: List[numpy.ndarray[(rows,cols,3),uint8]], batch_faces: List[dlib.full_object_detections], num_jitters: int=0) -> dlib.vectorss

有什么想法，我应该如何使用该库处理黑白图像以获得128维人脸图？

引发错误的完整列表（您可以将任何人的图像用作image.jpg）：


    import face_recognition
    image = face_recognition.load_image_file('image.jpg', mode='L')
    face_locations = face_recognition.face_locations(image)
    face_encodings = face_recognition.face_encodings(image, face_locations)

跟踪：



File "D:/PythonProjects/face_recognition_grayscale_test.py", line 18, in 
    face_encodings = face_recognition.face_encodings(image, face_locations)

File "C:\ProgramData\Anaconda3\lib\site-packages\face_recognition\api.py", line 200, in face_encodings
    return [np.array(face_encoder.compute_face_descriptor(face_image, raw_landmark_set, num_jitters)) for raw_landmark_set in raw_landmarks]

File "C:\ProgramData\Anaconda3\lib\site-packages\face_recognition\api.py", line 200, in 
    return [np.array(face_encoder.compute_face_descriptor(face_image, raw_landmark_set, num_jitters)) for raw_landmark_set in raw_landmarks]

TypeError: compute_face_descriptor(): incompatible function arguments. The following argument types are supported:
    1. (self: dlib.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),uint8], face: dlib.full_object_detection, num_jitters: int=0) -> dlib.vector
    2. (self: dlib.face_recognition_model_v1, img: numpy.ndarray[(rows,cols,3),uint8], faces: dlib.full_object_detections, num_jitters: int=0) -> dlib.vectors
    3. (self: dlib.face_recognition_model_v1, batch_img: List[numpy.ndarray[(rows,cols,3),uint8]], batch_faces: List[dlib.full_object_detections], num_jitters: int=0) -> dlib.vectorss

Invoked with: , array([[167, 167, 167, ..., 172, 172, 170],
       [167, 167, 167, ..., 172, 172, 170],
       [167, 167, 167, ..., 172, 172, 170],
       ...,
       [188, 186, 181, ..., 201, 201, 198],
       [193, 189, 184, ..., 201, 201, 198],
       [181, 180, 178, ..., 201, 201, 198]], dtype=uint8), , 1

Answer 1

根据错误消息，它似乎不接受单通道图像。您需要一个（行，列，3）的ndarray。您可以尝试传入image.repeat(3, 2)，它只会重复L值三次。

face_encodings = face_recognition.face_encodings(image.repeat(3, 2), face_locations)

人脸识别和黑白图像

1 个答案: