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- [x] Check that you are up-to-date with the master branch of keras-vis. You can update with:
pip install git+git://github.com/raghakot/keras-vis.git --upgrade --no-deps
- [x] If running on Tensor…
ghost updated
6 years ago
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https://github.com/pytorch/captum/blob/43acfcd320c44e8e469bf5276af9d55cf62145aa/captum/attr/_core/guided_grad_cam.py#L211
If I understand corretly, the parameter here should be:
inputs[i].shape[1…
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#9 で構築したモデルがどの部分に注目してレア度を判断しているのかを可視化する。
カードの縁の部分を注目していることがちゃんとわかればいい感じ。
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there is an example of gradcam with guided backprop modifier. but in the literature guided gradcam means something else: guided backprop multiplied by gradcam
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visualize_cam output array shape is not the same of input array shape. It gives me (224,3,3) as an output for (224,224,3) input shape. Any help ? Thanks in advanced.
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Thanks for your great work!
I want to visualize the grad-CAM figure for my 3D data image. However, I met some problem at this line:
` grads = visualize_cam(model, layer_idx, filter_indices=20…
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# 論文リンク
https://arxiv.org/abs/2001.01037
# 公開日(yyyy/mm/dd)
2020/01/04
# 概要
Attenstion を用いた image captioning に合わせて開発した
> variants of layer-wise
relevance backpropagation (LRP) and gradient…
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- [v] Check that you are up-to-date with the master branch of keras-vis. You can update with:
pip install git+git://github.com/raghakot/keras-vis.git --upgrade --no-deps
- [v] If running on Tensor…
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Hi,
I am trying to use your toolkit in Google Colaboratory starting from the example [Attention on ResNet50 (Saliency and grad-CAM)](https://github.com/raghakot/keras-vis/blob/master/examples/resnet/…