def show_labels(dataset_item):
"""Puts the dataset image into the output dir with the labeled quad"""
img = np.copy(dataset_item.img)
# red receipt outline
cv2.polylines(img, [dataset_item.quad.to_polyline()], True,
(0, 0, 255), 5)
# purple region of interest
cv2.polylines(img, [dataset_item.distribution_rect.to_polyline()],
True, (255, 0, 255), 3)
# blue inner region of interest
cv2.polylines(img, [dataset_item.small_roi_rect().to_polyline()], True,
(255, 0, 0), 2)
Output.write_image(dataset_item.file + "_0_labeled.jpg", img)
#if item.file != "008.jpg":
# continue
#
# run the segmentation algorithm
#
quad = segmenter.segment(item.img, item.distribution_rect)
#
# draw the result
#
# reference image
Output.write_image(item.file + "_0_norm.jpg", segmenter.img_normalized)
# preprocessed image
Output.write_image(item.file + "_1_preprop.jpg",
segmenter.img_preprocessed)
# distance map
Output.write_image(item.file + "_2_distances.jpg", segmenter.distances_img)
if quad is None:
print("No region found.")
continue
# poly to quad process
Output.write_image(
item.file + "_3_region.jpg",
