img_fg = np.hstack([img_l, img_c, img_r]) img_bg = np.ones([img_fg.shape[0], img_fg.shape[1], img_fg.shape[2]], np.uint8) * 255

# The code above is using numpy library to concatenate three images (img_l, img_c, and img_r) horizontally.
# It then creates a new image (img_bg) with the same shape as img_fg but with all pixels set to white (255).

# Explanation of each line:

# 1. img_fg = np.hstack([img_l, img_c, img_r])
# This line concatenates three images horizontally using np.hstack function.
# The images are passed as a list to the function [img_l, img_c, img_r].
# The resulting image is assigned to a new variable called img_fg.

# 2. img_bg = np.ones([img_fg.shape[0], img_fg.shape[1], img_fg.shape[2]], np.uint8) * 255
# This line creates a new image (img_bg) with the same shape as img_fg.
# It uses np.ones function to create an array of shape (img_fg.shape[0], img_fg.shape[1], img_fg.shape[2])
# filled with ones (i.e., white pixels).
# The data type of the array is set to np.uint8, which is an 8-bit unsigned integer data type.
# Finally, the array is multiplied by 255 to set all pixels to maximum intensity (also white).