face_recognition 和黑白图像

face_recognition and black&white images

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

我试过用

face_recognition.api.load_image_file(file, mode='RGB')</pre>,没问题。但我需要使用 L 模式,这就是重点。问题是 mode='RGB' 生成 numpy.array (x,y,3) 和 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。

如果我们将在 L 模式下生成的数组放入 face_encodings,我们会得到以下错误:


    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
</pre>

任何想法,我应该如何使用这个黑白图像库来获得 128 维面图?

抛出错误的完整列表(您可以使用任何人的图像作为 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)
</pre>

回溯:

</p>

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

<p>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]</p>

<p>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]</p>

<p>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</p>

<p>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
</pre>

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

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