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The pytorch implemention of EGCTNet for change detection task
作者您好,您的论文和代码工作相当出色,当我在调试代码过程中遇到了问题,需要您的指点,希望您能回复我的问题,非常感谢
Traceback (most recent call last):
File "/home/huangbo/CD_Code/2022-RS-EGCTNet/EGCTNet_pytorch-main/main_cd.py", line 83, in
train(args)
File "/home/huangbo/CD_Code/2022-RS-EGCTNet/EGCTNet_pytorch-main/main_cd.py", line 14, in train
model.train_models()
File "/home/huangbo/CD_Code/2022-RS-EGCTNet/EGCTNet_pytorch-main/models/trainer.py", line 342, in train_models
self._backward_G()
File "/home/huangbo/CD_Code/2022-RS-EGCTNet/EGCTNet_pytorch-main/models/trainer.py", line 315, in _backward_G
self.G_loss = self._pxl_loss(self.G_pred[-1], gt, self.G_pred[-2], gt_edge)
File "/home/huangbo/anaconda3/envs/pytorch1.8/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/home/huangbo/CD_Code/2022-RS-EGCTNet/EGCTNet_pytorch-main/models/losses.py", line 278, in forward
loss_c = cross_entropy(inputs, target)
File "/home/huangbo/CD_Code/2022-RS-EGCTNet/EGCTNet_pytorch-main/models/losses.py", line 19, in cross_entropy
input = F.interpolate(input, size=target.shape[1:], mode='bilinear',align_corners=True)
File "/home/huangbo/anaconda3/envs/pytorch1.8/lib/python3.8/site-packages/torch/nn/functional.py", line 3472, in interpolate
raise ValueError(
ValueError: size shape must match input shape. Input is 2D, size is 4
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