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b/RefineNet & SESNet/utils/pascal_voc.py |
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import os |
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def pascal_segmentation_lut(): |
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"""Return look-up table with number and correspondng class names |
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for PASCAL VOC segmentation dataset. Two special classes are: 0 - |
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background and 255 - ambigious region. All others are numerated from |
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1 to 20. |
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Returns |
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------- |
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classes_lut : dict |
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look-up table with number and correspondng class names |
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""" |
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classes_lut = dict([(0, 'background'), (255, 'teeth')]) |
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return classes_lut |
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def get_pascal_segmentation_images_lists_txts(pascal_root): |
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segmentation_images_lists_relative_folder = 'ImageSets/Segmentation' |
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segmentation_images_lists_folder = os.path.join(pascal_root, |
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segmentation_images_lists_relative_folder) |
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pascal_train_list_filename = os.path.join(segmentation_images_lists_folder, |
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'train.txt') |
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pascal_validation_list_filename = os.path.join(segmentation_images_lists_folder, |
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'val.txt') |
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pascal_trainval_list_filname = os.path.join(segmentation_images_lists_folder, |
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'trainval.txt') |
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return [ |
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pascal_train_list_filename, |
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pascal_validation_list_filename, |
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pascal_trainval_list_filname |
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] |
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def readlines_with_strip(filename): |
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# Get raw filnames from the file |
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with open(filename, 'r') as f: |
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lines = f.readlines() |
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# Clean filenames from whitespaces and newline symbols |
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clean_lines = list(map(lambda x: x.strip(), lines)) |
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return clean_lines |
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def readlines_with_strip_array_version(filenames_array): |
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multiple_files_clean_lines = list(map(readlines_with_strip, filenames_array)) |
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return multiple_files_clean_lines |
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def add_full_path_and_extention_to_filenames(filenames_array, full_path, extention): |
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full_filenames = list(map(lambda x: os.path.join(full_path, x) + '.' + extention, filenames_array)) |
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return full_filenames |
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def add_full_path_and_extention_to_filenames_array_version(filenames_array_array, full_path, extention): |
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result = list(map(lambda x: add_full_path_and_extention_to_filenames(x, full_path, extention), |
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filenames_array_array)) |
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return result |
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def get_pascal_segmentation_image_annotation_filenames_pairs(pascal_root): |
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pascal_relative_images_folder = 'JPEGImages' |
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pascal_relative_class_annotations_folder = 'SegmentationClass' |
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images_extention = 'jpg' |
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annotations_extention = 'png' |
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pascal_images_folder = os.path.join(pascal_root, pascal_relative_images_folder) |
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pascal_class_annotations_folder = os.path.join(pascal_root, pascal_relative_class_annotations_folder) |
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pascal_images_lists_txts = get_pascal_segmentation_images_lists_txts(pascal_root) |
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pascal_image_names = readlines_with_strip_array_version(pascal_images_lists_txts) |
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images_full_names = add_full_path_and_extention_to_filenames_array_version(pascal_image_names, |
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pascal_images_folder, |
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images_extention) |
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annotations_full_names = add_full_path_and_extention_to_filenames_array_version(pascal_image_names, |
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pascal_class_annotations_folder, |
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annotations_extention) |
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temp = zip(images_full_names, annotations_full_names) |
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image_annotation_filename_pairs = list(map(lambda x: zip(*x), temp)) |
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return image_annotation_filename_pairs |
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def get_pascal_selected_image_annotation_filenames_pairs(pascal_root, selected_names): |
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"""Returns (image, annotation) filenames pairs from PASCAL VOC segmentation dataset for selected names. |
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The function accepts the selected file names from PASCAL VOC segmentation dataset |
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and returns image, annotation pairs with fullpath and extention for those names. |
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Parameters |
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---------- |
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pascal_root : string |
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Path to the PASCAL VOC dataset root that is usually named 'VOC2012' |
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after being extracted from tar file. |
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selected_names : array of strings |
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Selected filenames from PASCAL VOC that can be read from txt files that |
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come with dataset. |
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Returns |
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------- |
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image_annotation_pairs : |
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Array with filename pairs with fullnames. |
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""" |
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pascal_relative_images_folder = 'JPEGImages' |
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pascal_relative_class_annotations_folder = 'SegmentationClass' |
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images_extention = 'jpg' |
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annotations_extention = 'png' |
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pascal_images_folder = os.path.join(pascal_root, pascal_relative_images_folder) |
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pascal_class_annotations_folder = os.path.join(pascal_root, pascal_relative_class_annotations_folder) |
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images_full_names = add_full_path_and_extention_to_filenames(selected_names, |
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pascal_images_folder, |
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images_extention) |
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annotations_full_names = add_full_path_and_extention_to_filenames(selected_names, |
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pascal_class_annotations_folder, |
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annotations_extention) |
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image_annotation_pairs = zip(images_full_names, |
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annotations_full_names) |
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return image_annotation_pairs |
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def get_augmented_pascal_image_annotation_filename_pairs(pascal_root): |
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pascal_txts = get_pascal_segmentation_images_lists_txts(pascal_root=pascal_root) |
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pascal_name_lists = readlines_with_strip_array_version(pascal_txts) |
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pascal_train_name_set, pascal_val_name_set, _ = list(map(lambda x: set(x), pascal_name_lists)) |
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all_pascal = pascal_train_name_set | pascal_val_name_set |
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everything = all_pascal |
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validation = pascal_val_name_set |
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# The rest of the dataset is for training |
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train = everything - validation |
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# The rest of the data will be loaded from pascal |
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train_from_pascal = train |
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train_from_pascal_image_annotation_pairs = \ |
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get_pascal_selected_image_annotation_filenames_pairs(pascal_root, |
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list(train_from_pascal)) |
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overall_train_image_annotation_filename_pairs = train_from_pascal_image_annotation_pairs |
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overall_val_image_annotation_filename_pairs = \ |
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get_pascal_selected_image_annotation_filenames_pairs(pascal_root, |
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validation) |
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return overall_train_image_annotation_filename_pairs, overall_val_image_annotation_filename_pairs |