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# 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"))