verticalize

def centralizeslice(image, threshold=None, verbose=False):
    '''
    Move detected region centroid to center of image
    This function can successively be applied to 'verticalize' slices of a tomographic dataset of a cylindrical object not scanned perfectly vertical
    '''
    if not threshold:
        print('Calculating threshold')
        threshold = skimage.filters.threshold_otsu(image)
    label_img = skimage.measure.label(image > threshold)
    # Detect centroid
    try:
        regions = skimage.measure.regionprops(label_img)[0]
        # roll image to the detected centerdata
        # to do so, we roll to half the image size on both axes
        shifted = numpy.roll(image,
                             shift=(image.shape[0] / 2 - regions.centroid[0], image.shape[1] / 2 - regions.centroid[1]),
                             axis=(0,1))
    except IndexError:
        # If no regions are found in the image, juyt return the original (empty) image
        shifted = image
    if verbose:
        plt.imshow(image)
        plt.imshow(shifted, cmap='viridis', alpha=0.5)
        try:
            plt.scatter(regions.centroid[1], regions.centroid[0], c='white')
        except UnboundLocalError:
            # No region, nothing to plot
            pass
        plt.axis('off')
        plt.show()
    return(shifted)