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