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### 論文へのリンク
[[arXiv:2008.09269] Beyond Fixed Grid: Learning Geometric Image Representation with a Deformable Grid](https://arxiv.org/abs/2008.09269)
### 著者・所属機関
Jun Gao, Zian Wang, Jinchen Xu…
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Thank you so much for providing the dataset.
I want to ask is there any convenient way to resize the image but still keeping the superpixel information. Just like what you have done in your paper, you…
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Hello,
I recently used your tool. Your work is really fancy! I have one question: do you provide an alternative option that can detect the tumor region by the original spots instead of superpixel?…
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## Describe the bug
Right now one has to supply a boundary probability map even if one does not plan to use it for superpixel generation (superpixels generated outside ilastik) and calculating …
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作者您好，很抱歉打扰，我现在也正在查看论文ESCNet: An End-to-End Superpixel-Enhanced Change Detection Network for Very-High-Resolution Remote Sensing Images，请问您train.py已经实现了吗？
yjssa updated
2 years ago
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```
int ratio = 0.99f;
Ptr lsc;
lsc = createSuperpixelLSC(imhsv, 10, ratio);
```
Changing the ratio value does not change the segmentation results (except for ratio = 1.0)
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could you provide the code to make train datasets? thanks.
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Dense prediction for coral image semantic segmentation
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Thanks for sharing this cool project! I was confused by how you segment 2D image using VFMs:
> As a result, SAM is able to segment images, with either point, box, or mask prompts, across different…
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How to run it?