def _check_paths_valid(self, src_img_dir: str):
check_dir_exists(src_img_dir)
img_filename_list = []
duplicate_img_filename_list = []
for frame in self:
img_filename = get_filename(frame.img_path)
if img_filename not in img_filename_list:
img_filename_list.append(frame.img_path)
else:
duplicate_img_filename_list.append(frame.img_path)
img_path = f'{src_img_dir}/{img_filename}'
check_file_exists(img_path)
if frame.cs_img_path:
check_file_exists(
f'{src_img_dir}/{get_filename(frame.cs_img_path)}')
if frame.depth_img_path:
check_file_exists(
f'{src_img_dir}/{get_filename(frame.depth_img_path)}')
if frame.is_img_path:
check_file_exists(
f'{src_img_dir}/{get_filename(frame.is_img_path)}')
if len(duplicate_img_filename_list) > 0:
logger.error(
f'Found the following duplicate image filenames in {self.__class__.__name__}:\n{duplicate_img_filename_list}'
)
raise Exception
def load_from_dir(cls,
img_dir: str,
json_dir: str,
show_pbar: bool = True) -> NDDS_Frame_Handler:
check_dir_exists(json_dir)
check_dir_exists(img_dir)
img_pathlist = get_valid_image_paths(img_dir)
json_path_list = [
path for path in get_all_files_of_extension(dir_path=json_dir,
extension='json')
if not get_filename(path).startswith('_')
]
json_path_list.sort()
handler = NDDS_Frame_Handler()
if show_pbar:
pbar = tqdm(total=len(json_path_list), unit='ann(s)', leave=True)
pbar.set_description(f'Loading {cls.__name__}')
for json_path in json_path_list:
check_file_exists(json_path)
json_rootname = get_rootname_from_path(json_path)
matching_img_path = None
matching_cs_img_path = None
matching_depth_img_path = None
matching_is_img_path = None
for img_path in img_pathlist:
img_rootname = '.'.join(get_filename(img_path).split('.')[:-1])
if img_rootname == json_rootname:
matching_img_path = img_path
elif img_rootname == f'{json_rootname}.cs':
matching_cs_img_path = img_path
elif img_rootname == f'{json_rootname}.depth':
matching_depth_img_path = img_path
elif img_rootname == f'{json_rootname}.is':
matching_is_img_path = img_path
if matching_img_path and matching_cs_img_path and matching_depth_img_path and matching_is_img_path:
break
if matching_img_path is None:
logger.error(
f"Couldn't find image file that matches rootname of {get_filename(json_path)} in {img_dir}"
)
raise FileNotFoundError
frame = NDDS_Frame(
img_path=matching_img_path,
ndds_ann=NDDS_Annotation.load_from_path(json_path),
cs_img_path=matching_cs_img_path,
depth_img_path=matching_depth_img_path,
is_img_path=matching_is_img_path)
handler.append(frame)
if show_pbar:
pbar.update()
return handler
def _check_paths_valid(self, src_img_dir: str):
check_dir_exists(src_img_dir)
img_filename_list = []
duplicate_img_filename_list = []
for ann in self:
img_filename = get_filename(ann.img_path)
if img_filename not in img_filename_list:
img_filename_list.append(ann.img_path)
else:
duplicate_img_filename_list.append(ann.img_path)
img_path = f'{src_img_dir}/{img_filename}'
check_file_exists(img_path)
if len(duplicate_img_filename_list) > 0:
logger.error(f'Found the following duplicate image filenames in LabelmeAnnotationHandler:\n{duplicate_img_filename_list}')
raise Exception
def load_from_dir(cls,
json_dir: str,
img_dir: str = None,
camera_config_path: str = None,
obj_config_path: str = None,
show_pbar: bool = False) -> NDDS_Dataset:
"""Loads NDDS_Dataset object from a directory path.
Arguments:
json_dir {str} -- [Path to directory with all of the NDDS annotation json files.]
Keyword Arguments:
img_dir {str} -- [Path to directory with all of the NDDS image files.] (default: json_dir)
camera_config_path {str} -- [Path to the camera configuration json file.] (default: f'{json_dir}/_camera_settings.json')
obj_config_path {str} -- [Path to the object configuration json file.] (default: f'{json_dir}/_object_settings.json')
show_pbar {bool} -- [Show the progress bar.] (default: {False})
Returns:
NDDS_Dataset -- [NDDS_Dataset object]
"""
check_dir_exists(json_dir)
if img_dir is None:
img_dir = json_dir
else:
check_dir_exists(img_dir)
camera_config_path = camera_config_path if camera_config_path is not None else f'{json_dir}/_camera_settings.json'
check_file_exists(camera_config_path)
obj_config_path = obj_config_path if obj_config_path is not None else f'{json_dir}/_object_settings.json'
check_file_exists(obj_config_path)
return NDDS_Dataset(
camera_config=CameraConfig.load_from_path(camera_config_path),
obj_config=ObjectSettings.load_from_path(obj_config_path),
frames=NDDS_Frame_Handler.load_from_dir(img_dir=img_dir,
json_dir=json_dir,
show_pbar=show_pbar))
def from_dict(cls,
collection_dict: dict,
check_paths: bool = True) -> DatasetConfigCollection:
check_required_keys(collection_dict,
required_keys=[
'collection_dir', 'dataset_names',
'dataset_specific'
])
collection_dir = collection_dict['collection_dir']
check_type(collection_dir, valid_type_list=[str])
dataset_names = collection_dict['dataset_names']
check_type(dataset_names, valid_type_list=[list])
check_type_from_list(dataset_names, valid_type_list=[str])
dataset_specific = collection_dict['dataset_specific']
check_type(dataset_specific, valid_type_list=[dict])
collection_tag = None if 'tag' not in collection_dict else collection_dict[
'tag']
check_type(collection_tag, valid_type_list=[type(None), str])
check_required_keys(
dataset_specific,
required_keys=['img_dir', 'ann_path', 'ann_format'])
img_dir = dataset_specific['img_dir']
check_type(img_dir, valid_type_list=[str, list])
if type(img_dir) is list:
check_type_from_list(img_dir, valid_type_list=[str])
check_list_length(img_dir, correct_length=len(dataset_names))
ann_path = dataset_specific['ann_path']
check_type(ann_path, valid_type_list=[str, list])
if type(ann_path) is list:
check_type_from_list(ann_path, valid_type_list=[str])
check_list_length(ann_path, correct_length=len(dataset_names))
ann_format = dataset_specific['ann_format']
check_type(ann_format, valid_type_list=[str, list])
if type(ann_format) is list:
check_type_from_list(ann_format, valid_type_list=[str])
check_list_length(ann_format, correct_length=len(dataset_names))
dataset_tag = None if 'tag' not in dataset_specific else dataset_specific[
'tag']
check_type(dataset_tag, valid_type_list=[type(None), str, list])
if type(dataset_tag) is list:
check_type_from_list(dataset_tag,
valid_type_list=[type(None), str])
check_list_length(dataset_tag, correct_length=len(dataset_names))
dataset_config_list = []
for i in range(len(dataset_names)):
if type(img_dir) is str:
img_dir0 = img_dir
elif type(img_dir) is list:
if i >= len(img_dir):
raise IndexError
img_dir0 = img_dir[i]
else:
raise Exception
if type(ann_path) is str:
ann_path0 = ann_path
elif type(ann_path) is list:
if i >= len(ann_path):
raise IndexError
ann_path0 = ann_path[i]
else:
raise Exception
if type(ann_format) is str:
ann_format0 = ann_format
elif type(ann_format) is list:
if i >= len(ann_format):
raise IndexError
ann_format0 = ann_format[i]
else:
raise Exception
if type(dataset_tag) is str or dataset_tag is None:
dataset_tag0 = dataset_tag
elif type(dataset_tag) is list:
if i >= len(dataset_tag):
raise IndexError
dataset_tag0 = dataset_tag[i]
else:
raise Exception
img_dir1 = rel_to_abs_path(
f'{collection_dir}/{dataset_names[i]}/{img_dir0}')
ann_path1 = rel_to_abs_path(
f'{collection_dir}/{dataset_names[i]}/{ann_path0}')
if check_paths:
check_dir_exists(img_dir1)
check_file_exists(ann_path1)
config = DatasetConfig(img_dir=img_dir1,
ann_path=ann_path1,
ann_format=ann_format0,
tag=dataset_tag0)
dataset_config_list.append(config)
return DatasetConfigCollection(dataset_config_list=dataset_config_list,
tag=collection_tag)
def load_from_dir(cls, load_dir: str) -> LabelmeAnnotationHandler:
check_dir_exists(load_dir)
json_path_list = get_all_files_of_extension(dir_path=load_dir,
extension='json')
return cls.load_from_pathlist(json_path_list)