def _extract_model(silent=False):
"""Extract model from Tensorflow model zoo.
Args:
silent (bool): if False, writes progress messages to stdout
"""
maybe_print(not silent, "Preparing pretrained model")
model_dir = PATHS.get_models_dir_path()
maybe_mkdir(model_dir)
model_archive_path = PATHS.get_data_file_path(
'ssd_inception_v2_coco_2017_11_17.tar.gz')
maybe_print(not silent, "Unpacking {}".format(model_archive_path))
with tarfile.open(model_archive_path, "r:gz") as tar:
tar.extractall(path=model_dir)
maybe_print(not silent, "Model ready")
def download_model(model_name, silent=False):
"""Downloads model_name from Tensorflow model zoo.
Args:
model_name (str): chosen object detection model
silent (bool): if True, writes progress messages to stdout
"""
maybe_print(not silent, "Preparing pretrained model")
model_dir = PATHS.get_models_dir_path()
maybe_mkdir(model_dir)
model_url = PATHS.get_model_url(model_name)
model_archive_path = os.path.join(model_dir, "{}.tar.gz".format(model_name))
download_file(model_url, model_archive_path, silent)
maybe_print(not silent, "Download complete\nUnpacking {}".format(model_archive_path))
with tarfile.open(model_archive_path, "r:gz") as tar:
tar.extractall(path=model_dir)
maybe_print(not silent, "Extracting complete\nRemoving {}".format(model_archive_path))
os.remove(model_archive_path)
maybe_print(not silent, "Model ready")