How to use the imutils.translate function in imutils

def normalize(color_im, crop_size=(512, 512)):

    # Center object in frame
    color_data = color_im.data
    nzp = color_im.nonzero_pixels().astype(np.int32)
    centroid = np.mean(nzp, axis=0)
    cx, cy = color_data.shape[1] // 2, color_data.shape[0] // 2
    color_data = imutils.translate(color_data, cx - round(centroid[1]), cy - round(centroid[0]))
    color_im = ColorImage(color_data, color_im.frame)

    # Crop about center to 512x512
    cx, cy = color_data.shape[1] // 2, color_data.shape[0] // 2
    crop_x = crop_size[0] / 2
    crop_y = crop_size[1] / 2
    color_data = imcrop(color_data, (cx-crop_x, cy-crop_y, cx+crop_x, cy+crop_y))
    color_im = ColorImage(color_data, color_im.frame)

    return color_im

def translation(move_x, move_y, image):
	# M = np.float32([[ 1, 0, move_x],[ 0, 1, move_y]])
	# dst = cv2.warpAffine( image, M, (image.shape[0], image.shape[1]) )
	dst = imutils.translate(image, move_x, move_y)
	return dst

# Load the image and show it
image = cv2.imread('C:/PythonProjects/PracticalPythonAndOpenCV_Book/images/trex.png')
cv2.imshow("Original", image)

# Translate the image 25 pixels to the right and 50 pixels down
matrix = np.float32([[1, 0, 25], [0, 1, 50]])
shifted = cv2.warpAffine(image, matrix, (image.shape[1], image.shape[0]))
cv2.imshow("Shifted Down and Right", shifted)

# Shift the image 50 pixels to the left and 90 pixels up
M = np.float32([[1, 0, -50], [0, 1, -90]])
shifted = cv2.warpAffine(image, M, (image.shape[1], image.shape[0]))
cv2.imshow("Shifted Up and Left", shifted)

# Use our own function in to shift the image down 100 pixels
shifted = imutils.translate(image, 0, 100)
cv2.imshow("Shifted Down", shifted)
cv2.waitKey(0)

# You simply need to specify how many pixels you want to shift the image
# in the X and Y direction -- let's translate the image 25 pixels to the
# right and 50 pixels down
M = np.float32([[1, 0, 25], [0, 1, 50]])
shifted = cv2.warpAffine(image, M, (image.shape[1], image.shape[0]))
cv2.imshow("Shifted Down and Right", shifted)

# now, let's shift the image 50 pixels to the left and 90 pixels up, we
# accomplish this using negative values
M = np.float32([[1, 0, -50], [0, 1, -90]])
shifted = cv2.warpAffine(image, M, (image.shape[1], image.shape[0]))
cv2.imshow("Shifted Up and Left", shifted)

# finally, let's use our helper function in imutils to shift the image down
# 100 pixels
shifted = imutils.translate(image, 0, 100)
cv2.imshow("Shifted Down", shifted)
cv2.waitKey(0)

def shiftedUp20(data):
    translated = imutils.translate(data, 0, -5)
    translated2 = translated.reshape(2304).tolist()
    return translated2
def shiftedDown20(data):