# 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 sys import os from collections import OrderedDict class ServingModels(object): def __init__(self): self.model_dict = OrderedDict() #senta for key in [ "senta_bilstm", "senta_bow", "senta_cnn", "senta_gru", "senta_lstm" ]: self.model_dict[ key] = "https://paddle-serving.bj.bcebos.com/paddle_hub_models/text/SentimentAnalysis/" + key + ".tar.gz" #image classification for key in [ "alexnet_imagenet", "darknet53-imagenet", "densenet121_imagenet", "densenet161_imagenet", "densenet169_imagenet", "densenet201_imagenet", "densenet264_imagenet" "dpn107_imagenet", "dpn131_imagenet", "dpn68_imagenet", "dpn92_imagenet", "dpn98_imagenet", "efficientnetb0_imagenet", "efficientnetb1_imagenet", "efficientnetb2_imagenet", "efficientnetb3_imagenet", "efficientnetb4_imagenet", "efficientnetb5_imagenet", "efficientnetb6_imagenet", "googlenet_imagenet", "inception_v4_imagenet", "inception_v2_imagenet", "nasnet_imagenet", "pnasnet_imagenet", "resnet_v2_101_imagenet", "resnet_v2_151_imagenet", "resnet_v2_18_imagenet", "resnet_v2_34_imagenet", "resnet_v2_50_imagenet", "resnext101_32x16d_wsl", "resnext101_32x32d_wsl", "resnext101_32x48d_wsl", "resnext101_32x8d_wsl", "resnext101_32x4d_imagenet", "resnext101_64x4d_imagenet", "resnext101_vd_32x4d_imagenet", "resnext101_vd_64x4d_imagenet", "resnext152_64x4d_imagenet", "resnext152_vd_64x4d_imagenet", "resnext50_64x4d_imagenet", "resnext50_vd_32x4d_imagenet", "resnext50_vd_64x4d_imagenet", "se_resnext101_32x4d_imagenet", "se_resnext50_32x4d_imagenet", "shufflenet_v2_imagenet", "vgg11_imagenet", "vgg13_imagenet", "vgg16_imagenet", "vgg19_imagenet", "xception65_imagenet", "xception71_imagenet", ]: self.model_dict[ key] = "https://paddle-serving.bj.bcebos.com/paddle_hub_models/image/ImageClassification/" + key + ".tar.gz" def get_model_list(self): return (self.model_dict.keys()) def download(self, model_name): if model_name in self.model_dict: url = self.model_dict[model_name] r = os.system('wget ' + url + ' --no-check-certificate') if __name__ == "__main__": models = ServingModels() print(models.get_model_list())