Heat map issues

[is8xia]

hello
Thanks for sharing your source code!
On my side, I would like to ask you how the heat map in your Figure 7 is realized?

[XinzheGeng]

@is8xia
Please refer to this repo: https://github.com/jacobgil/pytorch-grad-cam
tutorial: https://jacobgil.github.io/pytorch-gradcam-book/Class%20Activation%20Maps%20for%20Semantic%20Segmentation.html#tutorial-class-activation-maps-for-semantic-segmentation

[is8xia]

@XinzheGeng
Thank you for your reply.
But there is a problem, in change detection the input image is two, how do you go about getting the heat map via grad_cam?
Can you provide an idea or source code?

[XinzheGeng]

@is8xia
You can try to modify the code of the network: Merge the bitemporal images into the network, and modify the code of forward() as follow.
x1, x2 = torch.unsqueeze(x1[0], dim=0), torch.unsqueeze(x1[1], dim=0)

[is8xia]

@XinzheGeng
Thank you, I have achieved it

[bobo59]

谢谢你，我做到了

你好，请问是否可以分享你完成的代码。

[adleess]

hello
When i using grad-cam, there will be an error:' grad can be implicitly created only for scalar outputs', I don't know if you have encountered this problem when using it, and I would like to ask you how to realize the visualization.

[is8xia]

@bobo59 Change the input to the grad source code. Change the input to a splice of two images and separate the spliced images in the network.
input_tensor = [torch.unsqueeze(imgA_tensor, dim=0), torch.unsqueeze(imgB_tensor, dim=0)]

[is8xia]

Check if the output of your network is a tensor or a tuple, the output of the network needed for grad_cam should be a single tensor.

你好， 当我使用grad-cam时，会出现错误：'grad can beimplicitly create only for scalaroutputs'，不知道你在使用的时候是否遇到过这个问题，想请教一下你如何解决实现可视化。

[adleess]

Check if the output of your network is a tensor or a tuple, the output of the network needed for grad_cam should be a single tensor.

你好， 当我使用grad-cam时，会出现错误：'grad can beimplicitly create only for scalaroutputs'，不知道你在使用的时候是否遇到过这个问题，想请教一下你如何解决实现可视化。

Thank you for your help, I've solved the problem