Class WarpAffineTransform

tensorpack/dataflow/imgaug/transform.py:150–168

class WarpAffineTransform(Transform):
    def __init__(self, mat, dsize, interp=cv2.INTER_LINEAR,
                 borderMode=cv2.BORDER_CONSTANT, borderValue=0):
        super(WarpAffineTransform, self).__init__()
        self._init(locals())

    def apply_image(self, img):
        ret = cv2.warpAffine(img, self.mat, self.dsize,
                             flags=self.interp,
                             borderMode=self.borderMode,
                             borderValue=self.borderValue)
        if img.ndim == 3 and ret.ndim == 2:
            ret = ret[:, :, np.newaxis]
        return ret

    def apply_coords(self, coords):
        coords = np.concatenate((coords, np.ones((coords.shape[0], 1), dtype='f4')), axis=1)
        coords = np.dot(coords, self.mat.T)
        return coords


class FlipTransform(Transform):