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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _calc_texture_gradient(img):
 """ calculate texture gradient for entire image The original SelectiveSearch algorithm proposed Gaussian derivative for 8 orientations, but we use LBP instead. output will be [height(*)][width(*)] """

    ret = numpy.zeros((img.shape[0], img.shape[1], img.shape[2]))

    for colour_channel in (0, 1, 2):
        ret[:, :, colour_channel] = skimage.feature.local_binary_pattern(
            img[:, :, colour_channel], 8, 1.0)

    return ret