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When I look into MnistSuperpixels dataset, each graph has exactly 75 nodes.
When I convert MNIST to superpixels by myself using ToSLIC transform from pytorch geometric, I get exactly 81 nodes for e…
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@phoenixnn - In the Segs file that you provided, the images have information in the form of candidates.superpixel and candidates.label. What exactly is that? Can you please provide the code to get tha…
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The superpixel algorithm is required.
I can do it manual, from .raw_image, but other postprocess steps is problematic.
This not for speed, but for the processing oversampling image.
Add it suppo…
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On line 95, read the file into PIL.Image.
Is the WSI(svs or tiff) already converted to jpg(or png) before loading?
I don't understand this part very well and would appreciate some clarification.
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SNIC is a fast algorithm for creating superpixels (essentially, pixel groupings that minimize the variance of underlying pixel values). This is very useful for classification and for vectorization. Cl…
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Multicut in headless mode expects to get all 4 inputs from the data-selection applet:
raw data, probabilities, superpixels and groundtruth.
However, this does not make sense, because we want to use …
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I used to use scanpy python package for down-stream analysis.
I wonder how the predicted gene expressions can be analyzed in Anndata (Scanpy).
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Thank you so much for your code.
I don't understand this line: sub = self.segments[i:i + 2, j:j + 2]
Could you please explain how to judge if the two superpixels share a common boundary?
`
def ge…
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作者您好,我对您的GraphFPN 非常感兴趣,想将其用于目标检测 `,但是在阅读源码过程中遇到一些问题,我在mmdet版本的GraphFPN代码中看到有fpn,fpnv1,fpnv2以及fpnv3.请问这四个有什么区别吗。
![GraphFPN](https://user-images.githubusercontent.com/45568217/161707987-767833b9-bc0a…
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The tests should demonstrate that for many different configurations of superpixels, it still works correctly.