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updating augmentations
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parent
7be326d689
commit
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2 changed files with 46 additions and 3 deletions
8
train.py
8
train.py
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@ -53,6 +53,7 @@ def config_params():
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degrading = False # If true, degrading will be applied to the image. The amount of degrading is defined with "degrade_scales" in config_params.json.
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degrading = False # If true, degrading will be applied to the image. The amount of degrading is defined with "degrade_scales" in config_params.json.
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brightening = False # If true, brightening will be applied to the image. The amount of brightening is defined with "brightness" in config_params.json.
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brightening = False # If true, brightening will be applied to the image. The amount of brightening is defined with "brightness" in config_params.json.
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binarization = False # If true, Otsu thresholding will be applied to augment the input with binarized images.
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binarization = False # If true, Otsu thresholding will be applied to augment the input with binarized images.
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rgb_background = False
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dir_train = None # Directory of training dataset with subdirectories having the names "images" and "labels".
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dir_train = None # Directory of training dataset with subdirectories having the names "images" and "labels".
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dir_eval = None # Directory of validation dataset with subdirectories having the names "images" and "labels".
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dir_eval = None # Directory of validation dataset with subdirectories having the names "images" and "labels".
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dir_output = None # Directory where the output model will be saved.
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dir_output = None # Directory where the output model will be saved.
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@ -95,7 +96,7 @@ def run(_config, n_classes, n_epochs, input_height,
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index_start, dir_of_start_model, is_loss_soft_dice,
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index_start, dir_of_start_model, is_loss_soft_dice,
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n_batch, patches, augmentation, flip_aug,
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n_batch, patches, augmentation, flip_aug,
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blur_aug, padding_white, padding_black, scaling, degrading,
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blur_aug, padding_white, padding_black, scaling, degrading,
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brightening, binarization, blur_k, scales, degrade_scales,
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brightening, binarization, rgb_background, blur_k, scales, degrade_scales,
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brightness, dir_train, data_is_provided, scaling_bluring,
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brightness, dir_train, data_is_provided, scaling_bluring,
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scaling_brightness, scaling_binarization, rotation, rotation_not_90,
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scaling_brightness, scaling_binarization, rotation, rotation_not_90,
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thetha, scaling_flip, continue_training, transformer_projection_dim,
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thetha, scaling_flip, continue_training, transformer_projection_dim,
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@ -108,6 +109,7 @@ def run(_config, n_classes, n_epochs, input_height,
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if data_is_provided:
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if data_is_provided:
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dir_train_flowing = os.path.join(dir_output, 'train')
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dir_train_flowing = os.path.join(dir_output, 'train')
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dir_eval_flowing = os.path.join(dir_output, 'eval')
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dir_eval_flowing = os.path.join(dir_output, 'eval')
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dir_flow_train_imgs = os.path.join(dir_train_flowing, 'images')
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dir_flow_train_imgs = os.path.join(dir_train_flowing, 'images')
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dir_flow_train_labels = os.path.join(dir_train_flowing, 'labels')
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dir_flow_train_labels = os.path.join(dir_train_flowing, 'labels')
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@ -161,7 +163,7 @@ def run(_config, n_classes, n_epochs, input_height,
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# writing patches into a sub-folder in order to be flowed from directory.
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# writing patches into a sub-folder in order to be flowed from directory.
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provide_patches(imgs_list, segs_list, dir_img, dir_seg, dir_flow_train_imgs,
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provide_patches(imgs_list, segs_list, dir_img, dir_seg, dir_flow_train_imgs,
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dir_flow_train_labels, input_height, input_width, blur_k,
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dir_flow_train_labels, input_height, input_width, blur_k,
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blur_aug, padding_white, padding_black, flip_aug, binarization,
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blur_aug, padding_white, padding_black, flip_aug, binarization, rgb_background,
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scaling, degrading, brightening, scales, degrade_scales, brightness,
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scaling, degrading, brightening, scales, degrade_scales, brightness,
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flip_index, scaling_bluring, scaling_brightness, scaling_binarization,
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flip_index, scaling_bluring, scaling_brightness, scaling_binarization,
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rotation, rotation_not_90, thetha, scaling_flip, task, augmentation=augmentation,
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rotation, rotation_not_90, thetha, scaling_flip, task, augmentation=augmentation,
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@ -169,7 +171,7 @@ def run(_config, n_classes, n_epochs, input_height,
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provide_patches(imgs_list_test, segs_list_test, dir_img_val, dir_seg_val,
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provide_patches(imgs_list_test, segs_list_test, dir_img_val, dir_seg_val,
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dir_flow_eval_imgs, dir_flow_eval_labels, input_height, input_width,
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dir_flow_eval_imgs, dir_flow_eval_labels, input_height, input_width,
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blur_k, blur_aug, padding_white, padding_black, flip_aug, binarization,
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blur_k, blur_aug, padding_white, padding_black, flip_aug, binarization, rgb_background,
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scaling, degrading, brightening, scales, degrade_scales, brightness,
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scaling, degrading, brightening, scales, degrade_scales, brightness,
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flip_index, scaling_bluring, scaling_brightness, scaling_binarization,
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flip_index, scaling_bluring, scaling_brightness, scaling_binarization,
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rotation, rotation_not_90, thetha, scaling_flip, task, augmentation=False, patches=patches)
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rotation, rotation_not_90, thetha, scaling_flip, task, augmentation=False, patches=patches)
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41
utils.py
41
utils.py
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@ -695,6 +695,47 @@ def provide_patches(imgs_list_train, segs_list_train, dir_img, dir_seg, dir_flow
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cv2.imwrite(dir_flow_train_labels + '/img_' + str(indexer) + '.png',
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cv2.imwrite(dir_flow_train_labels + '/img_' + str(indexer) + '.png',
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resize_image(cv2.imread(dir_of_label_file), input_height, input_width))
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resize_image(cv2.imread(dir_of_label_file), input_height, input_width))
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indexer += 1
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indexer += 1
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if rotation_not_90:
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for thetha_i in thetha:
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img_max_rotated, label_max_rotated = rotation_not_90_func(cv2.imread(dir_img + '/'+im),
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cv2.imread(dir_of_label_file), thetha_i)
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cv2.imwrite(dir_flow_train_imgs + '/img_' + str(indexer) + '.png', resize_image(img_max_rotated, input_height, input_width))
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cv2.imwrite(dir_flow_train_labels + '/img_' + str(indexer) + '.png', resize_image(label_max_rotated, input_height, input_width))
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indexer += 1
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if channels_shuffling:
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for shuffle_index in shuffle_indexes:
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cv2.imwrite(dir_flow_train_imgs + '/img_' + str(indexer) + '.png',
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(resize_image(return_shuffled_channels(cv2.imread(dir_img + '/' + im), shuffle_index), input_height, input_width)))
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cv2.imwrite(dir_flow_train_labels + '/img_' + str(indexer) + '.png',
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resize_image(cv2.imread(dir_of_label_file), input_height, input_width))
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indexer += 1
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if scaling:
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for sc_ind in scales:
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img_scaled, label_scaled = scale_image_for_no_patch(cv2.imread(dir_img + '/'+im),
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cv2.imread(dir_of_label_file), sc_ind)
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cv2.imwrite(dir_flow_train_imgs + '/img_' + str(indexer) + '.png', resize_image(img_scaled, input_height, input_width))
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cv2.imwrite(dir_flow_train_labels + '/img_' + str(indexer) + '.png', resize_image(label_scaled, input_height, input_width))
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indexer += 1
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if rgb_color_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)
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cv2.imwrite(dir_flow_train_imgs + '/img_' + str(indexer) + '.png', resize_image(img_with_overlayed_background, input_height, input_width))
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cv2.imwrite(dir_flow_train_labels + '/img_' + str(indexer) + '.png',
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resize_image(cv2.imread(dir_of_label_file), input_height, input_width))
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if patches:
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if patches:
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