data_path = "./samples/WHU/train"  
epochs=110, batch_size=4, lr=0.0001, ModelName='DPN_Inria', is_Transfer= True  
BFENet.load_state_dict(torch.load('Pretrain_BFE_'+ModelName+'_model_epoch75_mIoU_89.657089.pth', map_location=device))  

BFENet.load_state_dict(torch.load('BestmIoU_BFE_DPN_epoch91_mIoU_91.864527.pth', map_location=device))
BCDNet.load_state_dict(torch.load('BestmIoU_BCD_DPN_epoch91_mIoU_91.864527.pth', map_location=device))
tests1_path = glob.glob('./samples/WHU/test/image1/*.tif')  
tests2_path = glob.glob('./samples/WHU/test/image2/*.tif')  
label_path = glob.glob('./samples/WHU/test/label/*.tif')  

@article{liu2021building,  
  title={Building Change Detection for VHR Remote Sensing Images via Local-Global Pyramid Network and Cross-Task Transfer Learning Strategy},  
  author={Liu, Tongfei and Gong, Maoguo and Lu, Di and Zhang, Qingfu and Zheng, Hanhong and Jiang, Fenlong and Zhang, Mingyang},  
  journal={IEEE Transactions on Geoscience and Remote Sensing},  
  year={2021},  
  pages={1-17},  
  doi={10.1109/TGRS.2021.3130940},  
  publisher={IEEE}  
}  

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