def has_checkpoint(self):
"""
Returns:
bool: whether a checkpoint exists in the target directory.
"""
save_file = os.path.join(self.save_dir, "last_checkpoint")
return megfile.smart_exists(save_file)
def convert_to_coco_json(dataset_name, output_file, allow_cached=True):
"""
Converts dataset into COCO format and saves it to a json file.
dataset_name must be registered in DatasetCatalog and in cvpods's standard format.
Args:
dataset_name:
reference from the config file to the catalogs
must be registered in DatasetCatalog and in cvpods's standard format
output_file: path of json file that will be saved to
allow_cached: if json file is already present then skip conversion
"""
# TODO: The dataset or the conversion script *may* change,
# a checksum would be useful for validating the cached data
ensure_dir(os.path.dirname(output_file))
with file_lock(output_file):
if megfile.smart_exists(output_file) and allow_cached:
logger.info(
f"Cached annotations in COCO format already exist: {output_file}"
)
else:
logger.info(
f"Converting dataset annotations in '{dataset_name}' to COCO format ...)"
)
coco_dict = convert_to_coco_dict(dataset_name)
with megfile.smart_open(output_file, "w") as json_file:
logger.info(
f"Caching annotations in COCO format: {output_file}")
json.dump(coco_dict, json_file)
def exists(path: str) -> bool:
"""
Checks if there is a resource at the given URI.
Args:
path (str): A URI supported by this PathHandler
Returns:
bool: true if the path exists
"""
return megfile.smart_exists(path)
def get_valid_files(args, cfg, logger):
if "MODEL.WEIGHTS" in args.opts:
model_weights = cfg.MODEL.WEIGHTS
assert megfile.smart_exists(model_weights), "{} not exist!!!".format(
model_weights)
return [model_weights]
file_list = glob.glob(os.path.join(cfg.OUTPUT_DIR, "model_*.pth"))
assert len(file_list) > 0, "Plz provide model to evaluate"
file_list = filter_by_iters(file_list, args.start_iter, args.end_iter)
assert file_list, "No checkpoint valid in {}.".format(cfg.OUTPUT_DIR)
logger.info("All files below will be tested in order:\n{}".format(
pformat(file_list)))
return file_list
def inner_func(path, *args, **kwargs):
cache_dir = get_cache_dir()
protocol, path_without_protocol = megfile.SmartPath._extract_protocol(
path)
local_path = os.path.join(cache_dir, path_without_protocol)
if megfile.smart_exists(local_path): # already cached
return megfile.smart_open(local_path, *args, **kwargs)
# caching logic
if protocol == "s3":
with file_lock(local_path):
megfile.s3_download(path, local_path)
elif protocol == "http" or protocol == "https":
with file_lock(local_path):
if not isinstance(path, str):
path = path.abspath()
download(path,
os.path.dirname(local_path),
filename=os.path.basename(local_path))
return megfile.smart_open(local_path, *args, **kwargs)