# Copyright (c) 2022 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 os.path as osp import glob import paddle from . import logging from .download import download_and_decompress cls_pretrain_weights_dict = { 'ResNet50_vd': ['IMAGENET'], 'MobileNetV3_small_x1_0': ['IMAGENET'], 'HRNet_W18_C': ['IMAGENET'], } seg_pretrain_weights_dict = { 'UNet': ['CITYSCAPES'], 'DeepLabV3P': ['CITYSCAPES', 'PascalVOC', 'IMAGENET'], 'FastSCNN': ['CITYSCAPES'], 'HRNet': ['CITYSCAPES', 'PascalVOC'], 'BiSeNetV2': ['CITYSCAPES'] } det_pretrain_weights_dict = { 'PicoDet_ESNet_s': ['COCO', 'IMAGENET'], 'PicoDet_ESNet_m': ['COCO', 'IMAGENET'], 'PicoDet_ESNet_l': ['COCO', 'IMAGENET'], 'PicoDet_LCNet': ['COCO', 'IMAGENET'], 'PicoDet_MobileNetV3': ['COCO', 'IMAGENET'], 'PicoDet_ResNet18_vd': ['IMAGENET'], 'YOLOv3_MobileNetV1': ['COCO', 'PascalVOC', 'IMAGENET'], 'YOLOv3_MobileNetV1_ssld': ['COCO', 'PascalVOC', 'IMAGENET'], 'YOLOv3_DarkNet53': ['COCO', 'IMAGENET'], 'YOLOv3_ResNet50_vd_dcn': ['COCO', 'IMAGENET'], 'YOLOv3_ResNet34': ['COCO', 'IMAGENET'], 'YOLOv3_MobileNetV3': ['COCO', 'PascalVOC', 'IMAGENET'], 'YOLOv3_MobileNetV3_ssld': ['PascalVOC', 'IMAGENET'], 'FasterRCNN_ResNet50_vd': ['COCO', 'IMAGENET'], 'FasterRCNN_ResNet50_vd_fpn': ['COCO', 'IMAGENET'], 'FasterRCNN_ResNet50': ['COCO', 'IMAGENET'], 'FasterRCNN_ResNet50_fpn': ['COCO', 'IMAGENET'], 'FasterRCNN_ResNet34_fpn': ['COCO', 'IMAGENET'], 'FasterRCNN_ResNet34_vd_fpn': ['COCO', 'IMAGENET'], 'FasterRCNN_ResNet101_fpn': ['COCO', 'IMAGENET'], 'FasterRCNN_ResNet101_vd_fpn': ['COCO', 'IMAGENET'], 'FasterRCNN_ResNet50_vd_ssld_fpn': ['COCO', 'IMAGENET'], 'FasterRCNN_HRNet_W18_fpn': ['COCO', 'IMAGENET'], 'PPYOLO_ResNet50_vd_dcn': ['COCO', 'IMAGENET'], 'PPYOLO_ResNet18_vd': ['COCO', 'IMAGENET'], 'PPYOLO_MobileNetV3_large': ['COCO', 'IMAGENET'], 'PPYOLO_MobileNetV3_small': ['COCO', 'IMAGENET'], 'PPYOLOv2_ResNet50_vd_dcn': ['COCO', 'IMAGENET'], 'PPYOLOv2_ResNet101_vd_dcn': ['COCO', 'IMAGENET'], 'PPYOLOTiny_MobileNetV3': ['COCO', 'IMAGENET'], 'MaskRCNN_ResNet50': ['COCO', 'IMAGENET'], 'MaskRCNN_ResNet50_fpn': ['COCO', 'IMAGENET'], 'MaskRCNN_ResNet50_vd_fpn': ['COCO', 'IMAGENET'], 'MaskRCNN_ResNet50_vd_ssld_fpn': ['COCO', 'IMAGENET'], 'MaskRCNN_ResNet101_fpn': ['COCO', 'IMAGENET'], 'MaskRCNN_ResNet101_vd_fpn': ['COCO', 'IMAGENET'] } cityscapes_weights = { 'UNet_CITYSCAPES': 'https://bj.bcebos.com/paddleseg/dygraph/cityscapes/unet_cityscapes_1024x512_160k/model.pdparams', 'DeepLabV3P_ResNet50_vd_CITYSCAPES': 'https://bj.bcebos.com/paddleseg/dygraph/cityscapes/deeplabv3p_resnet50_os8_cityscapes_1024x512_80k/model.pdparams', 'DeepLabV3P_ResNet101_vd_CITYSCAPES': 'https://bj.bcebos.com/paddleseg/dygraph/cityscapes/deeplabv3p_resnet101_os8_cityscapes_769x769_80k/model.pdparams', 'HRNet_HRNet_W18_CITYSCAPES': 'https://bj.bcebos.com/paddleseg/dygraph/cityscapes/fcn_hrnetw18_cityscapes_1024x512_80k/model.pdparams', 'HRNet_HRNet_W48_CITYSCAPES': 'https://bj.bcebos.com/paddleseg/dygraph/cityscapes/fcn_hrnetw48_cityscapes_1024x512_80k/model.pdparams', 'BiSeNetV2_CITYSCAPES': 'https://bj.bcebos.com/paddleseg/dygraph/cityscapes/bisenet_cityscapes_1024x1024_160k/model.pdparams', 'FastSCNN_CITYSCAPES': 'https://bj.bcebos.com/paddleseg/dygraph/cityscapes/fastscnn_cityscapes_1024x1024_160k/model.pdparams' } imagenet_weights = { 'PPLCNet_x0_25_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_25_pretrained.pdparams', 'PPLCNet_x0_35_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_35_pretrained.pdparams', 'PPLCNet_x0_5_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_5_pretrained.pdparams', 'PPLCNet_x0_75_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_75_pretrained.pdparams', 'PPLCNet_x1_0_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x1_0_pretrained.pdparams', 'PPLCNet_x1_5_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x1_5_pretrained.pdparams', 'PPLCNet_x2_0_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x2_0_pretrained.pdparams', 'PPLCNet_x2_5_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x2_5_pretrained.pdparams', 'PPLCNet_x0_5_ssld_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x0_5_ssld_pretrained.pdparams', 'PPLCNet_x1_0_ssld_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x1_0_ssld_pretrained.pdparams', 'PPLCNet_x2_5_ssld_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/PPLCNet_x2_5_ssld_pretrained.pdparams', 'ResNet18_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet18_pretrained.pdparams', 'ResNet34_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet34_pretrained.pdparams', 'ResNet50_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet50_pretrained.pdparams', 'ResNet101_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet101_pretrained.pdparams', 'ResNet152_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet152_pretrained.pdparams', 'ResNet18_vd_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet18_vd_pretrained.pdparams', 'ResNet34_vd_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet34_vd_pretrained.pdparams', 'ResNet50_vd_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet50_vd_pretrained.pdparams', 'ResNet50_vd_ssld_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet50_vd_ssld_pretrained.pdparams', 'ResNet101_vd_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet101_vd_pretrained.pdparams', 'ResNet101_vd_ssld_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet101_vd_ssld_pretrained.pdparams', 'ResNet152_vd_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet152_vd_pretrained.pdparams', 'ResNet200_vd_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/ResNet200_vd_pretrained.pdparams', 'MobileNetV1_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV1_pretrained.pdparams', 'MobileNetV1_x0_25_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV1_x0_25_pretrained.pdparams', 'MobileNetV1_x0_5_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV1_x0_5_pretrained.pdparams', 'MobileNetV1_x0_75_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV1_x0_75_pretrained.pdparams', 'MobileNetV2_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV2_pretrained.pdparams', 'MobileNetV2_x0_25_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV2_x0_25_pretrained.pdparams', 'MobileNetV2_x0_5_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV2_x0_5_pretrained.pdparams', 'MobileNetV2_x0_75_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV2_x0_75_pretrained.pdparams', 'MobileNetV2_x1_5_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV2_x1_5_pretrained.pdparams', 'MobileNetV2_x2_0_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/MobileNetV2_x2_0_pretrained.pdparams', 'MobileNetV3_small_x0_35_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_small_x0_35_pretrained.pdparams', 'MobileNetV3_small_x0_35_ssld_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_small_x0_35_ssld_pretrained.pdparams', 'MobileNetV3_small_x0_5_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_small_x0_5_pretrained.pdparams', 'MobileNetV3_small_x0_75_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_small_x0_75_pretrained.pdparams', 'MobileNetV3_small_x1_0_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_small_x1_0_pretrained.pdparams', 'MobileNetV3_small_x1_0_ssld_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_small_x1_0_ssld_pretrained.pdparams', 'MobileNetV3_small_x1_25_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_small_x1_25_pretrained.pdparams', 'MobileNetV3_large_x0_35_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_large_x0_35_pretrained.pdparams', 'MobileNetV3_large_x0_5_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_large_x0_5_pretrained.pdparams', 'MobileNetV3_large_x0_75_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_large_x0_75_pretrained.pdparams', 'MobileNetV3_large_x1_0_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_large_x1_0_pretrained.pdparams', 'MobileNetV3_large_x1_25_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_large_x1_25_pretrained.pdparams', 'MobileNetV3_large_x1_0_ssld_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/MobileNetV3_large_x1_0_ssld_pretrained.pdparams', 'AlexNet_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/AlexNet_pretrained.pdparams', 'DarkNet53_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/DarkNet53_pretrained.pdparams', 'DenseNet121_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/DenseNet121_pretrained.pdparams', 'DenseNet161_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/DenseNet161_pretrained.pdparams', 'DenseNet169_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/DenseNet169_pretrained.pdparams', 'DenseNet201_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/DenseNet201_pretrained.pdparams', 'DenseNet264_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/DenseNet264_pretrained.pdparams', 'HRNet_W18_C_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/HRNet_W18_C_pretrained.pdparams', 'HRNet_W30_C_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/HRNet_W30_C_pretrained.pdparams', 'HRNet_W32_C_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/HRNet_W32_C_pretrained.pdparams', 'HRNet_W40_C_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/HRNet_W40_C_pretrained.pdparams', 'HRNet_W44_C_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/HRNet_W44_C_pretrained.pdparams', 'HRNet_W48_C_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/HRNet_W48_C_pretrained.pdparams', 'HRNet_W64_C_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/legendary_models/HRNet_W64_C_pretrained.pdparams', 'Xception41_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/Xception41_pretrained.pdparams', 'Xception65_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/Xception65_pretrained.pdparams', 'Xception71_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/Xception71_pretrained.pdparams', 'ShuffleNetV2_x0_25_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ShuffleNetV2_x0_25_pretrained.pdparams', 'ShuffleNetV2_x0_33_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ShuffleNetV2_x0_33_pretrained.pdparams', 'ShuffleNetV2_x0_5_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ShuffleNetV2_x0_5_pretrained.pdparams', 'ShuffleNetV2_x1_0_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ShuffleNetV2_x1_0_pretrained.pdparams', 'ShuffleNetV2_x1_5_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ShuffleNetV2_x1_5_pretrained.pdparams', 'ShuffleNetV2_x2_0_IMAGENET': 'https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/ShuffleNetV2_x2_0_pretrained.pdparams', 'PicoDet_ESNet_s_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ESNet_x0_75_pretrained.pdparams', 'PicoDet_ESNet_m_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ESNet_x1_0_pretrained.pdparams', 'PicoDet_ESNet_l_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ESNet_x1_25_pretrained.pdparams', 'PicoDet_LCNet_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/LCNet_x1_5_pretrained.pdparams', 'PicoDet_MobileNetV3_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x1_0_ssld_pretrained.pdparams', 'PicoDet_ResNet18_vd_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet18_vd_pretrained.pdparams', 'FasterRCNN_ResNet50_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams', 'FasterRCNN_ResNet50_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams', 'FasterRCNN_ResNet50_vd_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams', 'FasterRCNN_ResNet50_vd_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams', 'FasterRCNN_ResNet50_vd_ssld_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_v2_pretrained.pdparams', 'FasterRCNN_ResNet34_vd_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet34_vd_pretrained.pdparams', 'FasterRCNN_ResNet34_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet34_pretrained.pdparams', 'FasterRCNN_ResNet101_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_pretrained.pdparams', 'FasterRCNN_ResNet101_vd_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_vd_pretrained.pdparams', 'FasterRCNN_HRNet_W18_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/HRNet_W18_C_pretrained.pdparams', 'YOLOv3_ResNet50_vd_dcn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_pretrained.pdparams', 'YOLOv3_ResNet34_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet34_pretrained.pdparams', 'YOLOv3_MobileNetV1_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV1_pretrained.pdparams', 'YOLOv3_MobileNetV1_ssld_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV1_ssld_pretrained.pdparams', 'YOLOv3_MobileNetV3_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x1_0_ssld_pretrained.pdparams', 'YOLOv3_MobileNetV3_ssld_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x1_0_ssld_pretrained.pdparams', 'YOLOv3_DarkNet53_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/DarkNet53_pretrained.pdparams', 'PPYOLO_ResNet50_vd_dcn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_pretrained.pdparams', 'PPYOLO_ResNet18_vd_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet18_vd_pretrained.pdparams', 'PPYOLO_MobileNetV3_large_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x1_0_ssld_pretrained.pdparams', 'PPYOLO_MobileNetV3_small_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_small_x1_0_ssld_pretrained.pdparams', 'PPYOLOv2_ResNet50_vd_dcn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_pretrained.pdparams', 'PPYOLOv2_ResNet101_vd_dcn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_vd_ssld_pretrained.pdparams', 'PPYOLOTiny_MobileNetV3_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV3_large_x0_5_pretrained.pdparams', 'MaskRCNN_ResNet50_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams', 'MaskRCNN_ResNet50_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_cos_pretrained.pdparams', 'MaskRCNN_ResNet50_vd_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams', 'MaskRCNN_ResNet50_vd_ssld_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_v2_pretrained.pdparams', 'MaskRCNN_ResNet101_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_pretrained.pdparams', 'MaskRCNN_ResNet101_vd_fpn_IMAGENET': 'https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_vd_pretrained.pdparams', 'DeepLabV3P_ResNet50_vd_IMAGENET': 'https://bj.bcebos.com/paddleseg/dygraph/resnet50_vd_ssld_v2.tar.gz', 'DeepLabV3P_ResNet101_vd_IMAGENET': 'https://bj.bcebos.com/paddleseg/dygraph/resnet101_vd_ssld.tar.gz' } pascalvoc_weights = { 'DeepLabV3P_ResNet50_vd_PascalVOC': 'https://bj.bcebos.com/paddleseg/dygraph/pascal_voc12/deeplabv3p_resnet50_os8_voc12aug_512x512_40k/model.pdparams', 'DeepLabV3P_ResNet101_vd_PascalVOC': 'https://bj.bcebos.com/paddleseg/dygraph/pascal_voc12/deeplabv3p_resnet101_os8_voc12aug_512x512_40k/model.pdparams', 'HRNet_HRNet_W18_PascalVOC': 'https://bj.bcebos.com/paddleseg/dygraph/pascal_voc12/fcn_hrnetw18_voc12aug_512x512_40k/model.pdparams', 'HRNet_HRNet_W48_PascalVOC': 'https://bj.bcebos.com/paddleseg/dygraph/pascal_voc12/fcn_hrnetw48_voc12aug_512x512_40k/model.pdparams', 'YOLOv3_MobileNetV1_PascalVOC': 'https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams', 'YOLOv3_MobileNetV1_ssld_PascalVOC': 'https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_voc.pdparams', 'YOLOv3_MobileNetV3_PascalVOC': 'https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_voc.pdparams', 'YOLOv3_MobileNetV3_ssld_PascalVOC': 'https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_ssld_270e_voc.pdparams' } coco_weights = { 'PicoDet_ESNet_s_COCO': 'https://paddledet.bj.bcebos.com/models/picodet_s_416_coco.pdparams', 'PicoDet_ESNet_m_COCO': 'https://paddledet.bj.bcebos.com/models/picodet_m_416_coco.pdparams', 'PicoDet_ESNet_l_COCO': 'https://paddledet.bj.bcebos.com/models/picodet_l_640_coco.pdparams', 'PicoDet_LCNet_COCO': 'https://paddledet.bj.bcebos.com/models/picodet_lcnet_1_5x_416_coco.pdparams', 'PicoDet_MobileNetV3_COCO': 'https://paddledet.bj.bcebos.com/models/picodet_mobilenetv3_large_1x_416_coco.pdparams', 'YOLOv3_MobileNetV1_COCO': 'https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams', 'YOLOv3_MobileNetV1_ssld_COCO': 'https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_ssld_270e_coco.pdparams', 'YOLOv3_DarkNet53_COCO': 'https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams', 'YOLOv3_ResNet50_vd_dcn_COCO': 'https://paddledet.bj.bcebos.com/models/yolov3_r50vd_dcn_270e_coco.pdparams', 'YOLOv3_ResNet34_COCO': 'https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams', 'YOLOv3_MobileNetV3_COCO': 'https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams', 'FasterRCNN_ResNet50_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_fpn_2x_coco.pdparams', 'FasterRCNN_ResNet50_COCO': 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_1x_coco.pdparams', 'FasterRCNN_ResNet50_vd_COCO': 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_1x_coco.pdparams', 'FasterRCNN_ResNet50_vd_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_fpn_2x_coco.pdparams', 'FasterRCNN_ResNet50_vd_ssld_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r50_vd_ssld_fpn_2x_coco.pdparams', 'FasterRCNN_ResNet34_vd_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_vd_fpn_1x_coco.pdparams', 'FasterRCNN_ResNet34_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r34_fpn_1x_coco.pdparams', 'FasterRCNN_ResNet101_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_fpn_2x_coco.pdparams', 'FasterRCNN_ResNet101_vd_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/faster_rcnn_r101_vd_fpn_1x_coco.pdparams', 'FasterRCNN_HRNet_W18_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/faster_rcnn_hrnetv2p_w18_2x_coco.pdparams', 'PPYOLO_ResNet50_vd_dcn_COCO': 'https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_2x_coco.pdparams', 'PPYOLO_ResNet18_vd_COCO': 'https://paddledet.bj.bcebos.com/models/ppyolo_r18vd_coco.pdparams', 'PPYOLO_MobileNetV3_large_COCO': 'https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams', 'PPYOLO_MobileNetV3_small_COCO': 'https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_small_coco.pdparams', 'PPYOLOv2_ResNet50_vd_dcn_COCO': 'https://paddledet.bj.bcebos.com/models/ppyolov2_r50vd_dcn_365e_coco.pdparams', 'PPYOLOv2_ResNet101_vd_dcn_COCO': 'https://paddledet.bj.bcebos.com/models/ppyolov2_r101vd_dcn_365e_coco.pdparams', 'PPYOLOTiny_MobileNetV3_COCO': 'https://paddledet.bj.bcebos.com/models/ppyolo_tiny_650e_coco.pdparams', 'MaskRCNN_ResNet50_COCO': 'https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_2x_coco.pdparams', 'MaskRCNN_ResNet50_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_2x_coco.pdparams', 'MaskRCNN_ResNet50_vd_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_2x_coco.pdparams', 'MaskRCNN_ResNet50_vd_ssld_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_vd_fpn_ssld_2x_coco.pdparams', 'MaskRCNN_ResNet101_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/mask_rcnn_r101_fpn_1x_coco.pdparams', 'MaskRCNN_ResNet101_vd_fpn_COCO': 'https://paddledet.bj.bcebos.com/models/mask_rcnn_r101_vd_fpn_1x_coco.pdparams' } def get_pretrain_weights(flag, class_name, save_dir, backbone_name=None): if flag is None: return None elif osp.isdir(flag): return flag elif osp.isfile(flag): return flag # TODO: check flag new_save_dir = save_dir if backbone_name is not None: weights_key = "{}_{}_{}".format(class_name, backbone_name, flag) else: weights_key = "{}_{}".format(class_name, flag) if flag == 'CITYSCAPES': url = cityscapes_weights[weights_key] elif flag == 'IMAGENET': url = imagenet_weights[weights_key] elif flag == 'PascalVOC': url = pascalvoc_weights[weights_key] elif flag == 'COCO': url = coco_weights[weights_key] else: raise ValueError('Given pretrained weights {} is undefined.'.format( flag)) fname = download_and_decompress(url, path=new_save_dir) if osp.isdir(fname): fname = glob.glob(osp.join(fname, '*.pdparams'))[0] return fname def load_pretrain_weights(model, pretrain_weights=None, model_name=None): if pretrain_weights is not None: logging.info( 'Loading pretrained model from {}'.format(pretrain_weights), use_color=True) if os.path.exists(pretrain_weights): param_state_dict = paddle.load(pretrain_weights) model_state_dict = model.state_dict() # HACK: Fit for faster rcnn. Pretrain weights contain prefix of 'backbone' # while res5 module is located in bbox_head.head. Replace the prefix of # res5 with 'bbox_head.head' to load pretrain weights correctly. for k in param_state_dict.keys(): if 'backbone.res5' in k: new_k = k.replace('backbone', 'bbox_head.head') if new_k in model_state_dict: value = param_state_dict.pop(k) param_state_dict[new_k] = value num_params_loaded = 0 for k in model_state_dict: if k not in param_state_dict: logging.warning("{} is not in pretrained model".format(k)) elif list(param_state_dict[k].shape) != list(model_state_dict[k] .shape): logging.warning( "[SKIP] Shape of pretrained params {} doesn't match.(Pretrained: {}, Actual: {})" .format(k, param_state_dict[k].shape, model_state_dict[ k].shape)) else: model_state_dict[k] = param_state_dict[k] num_params_loaded += 1 model.set_state_dict(model_state_dict) logging.info("There are {}/{} variables loaded into {}.".format( num_params_loaded, len(model_state_dict), model_name)) else: raise ValueError('The pretrained model directory is not Found: {}'. format(pretrain_weights)) else: logging.info( 'No pretrained model to load, {} will be trained from scratch.'. format(model_name)) def load_optimizer(optimizer, state_dict_path): logging.info("Loading optimizer from {}".format(state_dict_path)) optim_state_dict = paddle.load(state_dict_path) for key in optimizer.state_dict().keys(): if key not in optim_state_dict.keys(): optim_state_dict[key] = optimizer.state_dict()[key] if 'last_epoch' in optim_state_dict: optim_state_dict.pop('last_epoch') optimizer.set_state_dict(optim_state_dict) def load_checkpoint(model, optimizer, model_name, checkpoint): logging.info("Loading checkpoint from {}".format(checkpoint)) load_pretrain_weights( model, pretrain_weights=osp.join(checkpoint, 'model.pdparams'), model_name=model_name) load_optimizer( optimizer, state_dict_path=osp.join(checkpoint, "model.pdopt"))