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@ -823,6 +823,53 @@ def provide_patches(imgs_list_train, segs_list_train, dir_img, dir_seg, dir_flow
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img_max_rotated,
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label_max_rotated,
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input_height, input_width, indexer=indexer)
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if channels_shuffling:
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for shuffle_index in shuffle_indexes:
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indexer = get_patches(dir_flow_train_imgs, dir_flow_train_labels,
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return_shuffled_channels(cv2.imread(dir_img + '/' + im), shuffle_index),
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cv2.imread(dir_of_label_file),
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input_height, input_width, indexer=indexer)
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if adding_rgb_background:
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img_bin_corr = cv2.imread(dir_img_bin + '/' + img_name+'.png')
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for i_n in range(number_of_backgrounds_per_image):
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background_image_chosen_name = random.choice(list_all_possible_background_images)
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img_rgb_background_chosen = cv2.imread(dir_rgb_backgrounds + '/' + background_image_chosen_name)
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img_with_overlayed_background = return_binary_image_with_given_rgb_background(img_bin_corr, img_rgb_background_chosen)
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indexer = get_patches(dir_flow_train_imgs, dir_flow_train_labels,
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img_with_overlayed_background,
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cv2.imread(dir_of_label_file),
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input_height, input_width, indexer=indexer)
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if adding_rgb_foreground:
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img_bin_corr = cv2.imread(dir_img_bin + '/' + img_name+'.png')
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for i_n in range(number_of_backgrounds_per_image):
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background_image_chosen_name = random.choice(list_all_possible_background_images)
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foreground_rgb_chosen_name = random.choice(list_all_possible_foreground_rgbs)
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img_rgb_background_chosen = cv2.imread(dir_rgb_backgrounds + '/' + background_image_chosen_name)
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foreground_rgb_chosen = np.load(dir_rgb_foregrounds + '/' + foreground_rgb_chosen_name)
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img_with_overlayed_background = return_binary_image_with_given_rgb_background_and_given_foreground_rgb(img_bin_corr, img_rgb_background_chosen, foreground_rgb_chosen)
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indexer = get_patches(dir_flow_train_imgs, dir_flow_train_labels,
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img_with_overlayed_background,
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cv2.imread(dir_of_label_file),
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input_height, input_width, indexer=indexer)
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if add_red_textlines:
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img_bin_corr = cv2.imread(dir_img_bin + '/' + img_name+'.png')
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img_red_context = return_image_with_red_elements(cv2.imread(dir_img + '/'+im), img_bin_corr)
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indexer = get_patches(dir_flow_train_imgs, dir_flow_train_labels,
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img_red_context,
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cv2.imread(dir_of_label_file),
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input_height, input_width, indexer=indexer)
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if flip_aug:
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for f_i in flip_index:
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indexer = get_patches(dir_flow_train_imgs, dir_flow_train_labels,
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@ -871,10 +918,19 @@ def provide_patches(imgs_list_train, segs_list_train, dir_img, dir_seg, dir_flow
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input_height, input_width, indexer=indexer)
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if binarization:
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indexer = get_patches(dir_flow_train_imgs, dir_flow_train_labels,
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otsu_copy(cv2.imread(dir_img + '/' + im)),
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cv2.imread(dir_of_label_file),
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input_height, input_width, indexer=indexer)
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if dir_img_bin:
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img_bin_corr = cv2.imread(dir_img_bin + '/' + img_name+'.png')
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indexer = get_patches(dir_flow_train_imgs, dir_flow_train_labels,
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img_bin_corr,
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cv2.imread(dir_of_label_file),
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input_height, input_width, indexer=indexer)
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else:
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indexer = get_patches(dir_flow_train_imgs, dir_flow_train_labels,
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otsu_copy(cv2.imread(dir_img + '/' + im)),
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cv2.imread(dir_of_label_file),
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input_height, input_width, indexer=indexer)
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if scaling_brightness:
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for sc_ind in scales:
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