def extract_voc_data_if_needed():
if os.path.exists(PATHS.get_voc_dir_path()):
return
voc_archive_path = PATHS.get_data_file_path('VOCtest_06-Nov-2007.tar')
print("Unpacking {}".format(voc_archive_path))
with tarfile.open(voc_archive_path, "r") as tar:
tar.extractall(path=PATHS.get_sample_root())
print("Unpacking done!")
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")