# coding: utf8 # Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserve. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import argparse import os import sys __dir__ = os.path.dirname(os.path.abspath(__file__)) sys.path.append(os.path.abspath(os.path.join(__dir__, '../../../'))) from paddleseg.utils.download import download_file_and_uncompress model_urls = { "portrait_pp_humansegv1_lite_398x224_inference_model_with_softmax": "https://paddleseg.bj.bcebos.com/dygraph/pp_humanseg_v2/portrait_pp_humansegv1_lite_398x224_inference_model_with_softmax.zip", "portrait_pp_humansegv2_lite_256x144_inference_model_with_softmax": "https://paddleseg.bj.bcebos.com/dygraph/pp_humanseg_v2/portrait_pp_humansegv2_lite_256x144_smaller/portrait_pp_humansegv2_lite_256x144_inference_model_with_softmax.zip", "human_pp_humansegv1_lite_192x192_inference_model_with_softmax": "https://paddleseg.bj.bcebos.com/dygraph/pp_humanseg_v2/human_pp_humansegv1_lite_192x192_inference_model_with_softmax.zip", "human_pp_humansegv2_lite_192x192_inference_model_with_softmax": "https://paddleseg.bj.bcebos.com/dygraph/pp_humanseg_v2/human_pp_humansegv2_lite_192x192_inference_model_with_softmax.zip", "human_pp_humansegv1_mobile_192x192_inference_model_with_softmax": "https://paddleseg.bj.bcebos.com/dygraph/pp_humanseg_v2/human_pp_humansegv1_mobile_192x192_inference_model_with_softmax.zip", "human_pp_humansegv2_mobile_192x192_inference_model_with_softmax": "https://paddleseg.bj.bcebos.com/dygraph/pp_humanseg_v2/human_pp_humansegv2_mobile_192x192_inference_model_with_softmax.zip", } if __name__ == "__main__": data_path = os.path.abspath("./inference_models") for model_name, url in model_urls.items(): download_file_and_uncompress( url=url, savepath=data_path, extrapath=data_path, extraname=model_name) print("Download inference models finished.")