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",