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I've installed TinyTeX by chocolatey `choco install manim-latex.` It is a dedicated package for Manim based on TinyTeX which contains all the required packages that Manim interacts with.
After instal…
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Retina CLI is a command line client to use [Retina](https://www.screenretina.com/) — client for visual recognition of medical reports using artifical intelligence.
**Usage:**
- `$ retina detect --…
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Hi there, I am amazed by your works!
When I try to use degradation.py to degradate my fundus image, it seems like it didn't work cus it need corresponding mask of fundus image?
Any helps will …
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Hello, I see that you mentioned providing HQG pretraining and training models for the CCM and Fundus datasets. Could you please upload the pretrained and training models for the colonoscopy dataset as…
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Datasets. REFUGE dataset [6] is arranged for the segmentation of optic
disc and cup, which consists of 400 training images and 400 validation images.
Orlando, J.I., et al.: Refuge challenge: a uni…
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Hi
I have successfully run the train file, but found that the total_loss is negative, I guess there might be a problem with the processing of the prepare_dataset.py file. Could you please provide m…
300id updated
6 months ago
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One way to test Fundus would be to execute a few example projects ourselves and see if Fundus is up to the task :)
Here is an idea for an example project: **Make a corpus of funny German text**
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Hello,
I am currently working on **deploying an nnUNetv2 model** and would appreciate some guidance on the best practices for doing so. Below is the inference code I am using. Could you please prov…
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X-ray image, CT image, MRI and color fundus photographs (https://www.nature.com/articles/s41746-019-0172-3#data-availability)
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Hi Quande,
Thanks for sharing this exciting research work! Here I want to learn more details about the implementation of the prostate task. It seems the main scripts (including train_ELCFS.py, test…