def test_get_img_name_and_img_path_from_text_filename(self):
coco_reader = CocoDatasetReader()
labels_folder_path = os.path.join(self.dataset_name, 'train_labels')
images_folder_path = os.path.join(self.dataset_name, 'train_images')
text_path = load_text_paths(labels_folder_path)[0]
coco_reader._save_to_instance_folder_paths(self.dataset_name)
image_filepath, image_filename = coco_reader._get_img_name_and_img_path_from_text_filename(
text_path)
self.assertEqual(image_filepath in load_images(images_folder_path),
True)
def test_read_text(self):
coco_reader = CocoDatasetReader()
labels_folder_path = os.path.join(self.dataset_name, 'train_labels')
images_folder_path = os.path.join(self.dataset_name, 'train_images')
text_path = load_text_paths(labels_folder_path)[0]
coco_reader._save_to_instance_folder_paths(self.dataset_name)
data_in_output_format, _ = coco_reader._read_text(
text_path, ["test", "test"])
self.assertEqual(len(data_in_output_format['boxes']) > 0, True)
self.assertEqual(len(data_in_output_format['labels']) > 0, True)
self.assertEqual(len(data_in_output_format['boxes']),
len(data_in_output_format['labels']))
def test_txt_file_to_image(self):
images = load_images_names(self.images_path)
folder_txts = load_text_paths(self.annotations_path)
folder_txts.sort()
txts_form_images_names = []
for image in images:
label_txt_filename = image + '.txt'
label_txt_filepath = os.path.join(self.annotations_path,
label_txt_filename)
txts_form_images_names.append(label_txt_filepath)
txts_form_images_names.sort()
self.assertEqual(txts_form_images_names == folder_txts, True)
def _extract_data_from_annotations_folder(
self, output_data_in_universa_od_format):
"""
Method that extract data form annotations folder.
:param output_data_in_universa_od_format: dict in universal object detection format without annotations
:type output_data_in_universa_od_format: dict
:return: dict in universal object detection format with annotations
:rtype: dict
"""
txts_paths = load_text_paths(self.annotations_folder_path)
uniq_dataset_classes = []
uniq_dataset_classes = self._load_dataset_classes_names()
objects = []
for text_path in txts_paths:
text_object_dict, uniq_dataset_classes = self._read_text(
text_path, uniq_dataset_classes)
objects.append(text_object_dict)
output_data_in_universa_od_format.update({'objects': objects})
uniq_dataset_classes = self._format_dataset_classes(
uniq_dataset_classes)
output_data_in_universa_od_format.update(
{'dataset_classes': uniq_dataset_classes})
return output_data_in_universa_od_format
def test_text_paths_loading(self):
coco_reader = CocoDatasetReader()
coco_reader._test_structure_exist(self.dataset_name)
texts = load_text_paths(coco_reader.annotations_folder_path)
self.assertEqual(len(texts) > 0, True)