align_dlib.py 文件源码

def align(self, imgDim, rgbImg, bb,
              landmarks=None, landmarkIndices=INNER_EYES_AND_BOTTOM_LIP, scale=1.0):
        r"""align(imgDim, rgbImg, bb=None, landmarks=None, landmarkIndices=INNER_EYES_AND_BOTTOM_LIP)

        Transform and align a face in an image.

        :param imgDim: The edge length in pixels of the square the image is resized to.
        :type imgDim: int
        :param rgbImg: RGB image to process. Shape: (height, width, 3)
        :type rgbImg: numpy.ndarray
        :param bb: Bounding box around the face to align. \
                   Defaults to the largest face.
        :type bb: dlib.rectangle
        :param landmarks: Detected landmark locations. \
                          Landmarks found on `bb` if not provided.
        :type landmarks: list of (x,y) tuples
        :param landmarkIndices: The indices to transform to.
        :type landmarkIndices: list of ints
        :param scale: Scale image before cropping to the size given by imgDim.
        :type scale: float
        :return: The aligned RGB image. Shape: (imgDim, imgDim, 3)
        :rtype: numpy.ndarray
        """
        assert imgDim is not None
        assert rgbImg is not None
        assert landmarkIndices is not None
        assert bb is not None

        bb_dlib = dlib.rectangle(left=bb[0], top=bb[1], right=bb[2], bottom=bb[3])
        if landmarks is None:
            landmarks = self.findLandmarks(rgbImg, bb_dlib)

        npLandmarks = np.float32(landmarks)
        npLandmarkIndices = np.array(landmarkIndices)

        #pylint: disable=maybe-no-member
        H = cv2.getAffineTransform(npLandmarks[npLandmarkIndices],
                                   imgDim * MINMAX_TEMPLATE[npLandmarkIndices]*scale + imgDim*(1-scale)/2)
        thumbnail = cv2.warpAffine(rgbImg, H, (imgDim, imgDim))

        return thumbnail