--- a +++ b/misc/download_pretrained_model.py @@ -0,0 +1,133 @@ +# Modified from https://github.com/PaddlePaddle/PaddleSeg/blob/release/2.3/paddleseg/utils/download.py + +# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. +# +# 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 os +import shutil +import requests +import time +import sys +import zipfile +lasttime = time.time() +FLUSH_INTERVAL = 0.1 + + +def progress(str, end=False): + global lasttime + if end: + str += "\n" + lasttime = 0 + if time.time() - lasttime >= FLUSH_INTERVAL: + sys.stdout.write("\r%s" % str) + lasttime = time.time() + sys.stdout.flush() + + +def _download_file(url, savepath, print_progress): + if print_progress: + print("Connecting to {}".format(url)) + r = requests.get(url, stream=True, timeout=15) + total_length = r.headers.get('content-length') + + if total_length is None: + with open(savepath, 'wb') as f: + shutil.copyfileobj(r.raw, f) + else: + with open(savepath, 'wb') as f: + dl = 0 + total_length = int(total_length) + if print_progress: + print("Downloading %s" % os.path.basename(savepath)) + for data in r.iter_content(chunk_size=4096): + dl += len(data) + f.write(data) + if print_progress: + done = int(50 * dl / total_length) + progress("[%-50s] %.2f%%" % + ('=' * done, float(100 * dl) / total_length)) + if print_progress: + progress("[%-50s] %.2f%%" % ('=' * 50, 100), end=True) + + +def _uncompress_file_zip(filepath, extrapath): + files = zipfile.ZipFile(filepath, 'r') + filelist = files.namelist() + rootpath = filelist[0] + total_num = len(filelist) + for index, file in enumerate(filelist): + files.extract(file, extrapath) + yield total_num, index, rootpath + files.close() + yield total_num, index, rootpath + + +def download_file_and_uncompress(url, + savepath=None, + print_progress=True, + replace=False, + extrapath=None, + delete_file=True): + if savepath is None: + savepath = "." + if extrapath is None: + extrapath = "." + savename = url.split("/")[-1] + if not savename.endswith("zip"): + raise NotImplementedError( + "Only support zip file, but got {}!".format(savename)) + if not os.path.exists(savepath): + os.makedirs(savepath) + + savepath = os.path.join(savepath, savename) + savename = ".".join(savename.split(".")[:-1]) + + if replace: + if os.path.exists(savepath): + shutil.rmtree(savepath) + + if not os.path.exists(savename): + if not os.path.exists(savepath): + _download_file(url, savepath, print_progress) + + if print_progress: + print("Uncompress %s" % os.path.basename(savepath)) + for total_num, index, rootpath in _uncompress_file_zip(savepath, extrapath): + if print_progress: + done = int(50 * float(index) / total_num) + progress( + "[%-50s] %.2f%%" % ('=' * done, float(100 * index) / total_num)) + if print_progress: + progress("[%-50s] %.2f%%" % ('=' * 50, 100), end=True) + + if delete_file: + os.remove(savepath) + + return rootpath + + +if __name__ == "__main__": + urls = [ + "https://github.com/ShiqiYu/OpenGait/releases/download/v1.0/pretrained_casiab_model.zip", + "https://github.com/ShiqiYu/OpenGait/releases/download/v1.1/pretrained_oumvlp_model.zip", + "https://github.com/ShiqiYu/OpenGait/releases/download/v1.1/pretrained_grew_model.zip"] + for url in urls: + download_file_and_uncompress( + url=url, extrapath='output') + gaitgl_grew = ['https://github.com/ShiqiYu/OpenGait/releases/download/v1.1/pretrained_grew_gaitgl.zip', + 'https://github.com/ShiqiYu/OpenGait/releases/download/v1.1/pretrained_grew_gaitgl_bnneck.zip'] + for gaitgl in gaitgl_grew: + download_file_and_uncompress( + url=gaitgl, extrapath='output/GREW/GaitGL') + print("Pretrained model download success!")