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@@ -36,7 +36,7 @@ This model has been pushed to the Hub using the [PytorchModelHubMixin](https://h
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  ```
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  4. In the current working directory, find the `example_input_file` folder.
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  Select an arbitrary `.h5` file in this folder and drag it into the `Gradio` interface for model inference.
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- 5. Waiting for about 1min~2min30s, the model inference is completed and the segmentation result and 3D rendering visualization will be produced.
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  Both the original image and the segmentation result are saved in `.nii.gz` format in the `output` folder of the same directory.
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  6. Since `Gradio` performs 1/2 downsampling on the 3D segmentation visualization, the segmentation accuracy is degraded.
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  Users can drag the `.nii.gz` format files in the `output` folder into the `ITK-SNAP` software to view the accurate segmentation visualization.
 
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  ```
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  4. In the current working directory, find the `example_input_file` folder.
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  Select an arbitrary `.h5` file in this folder and drag it into the `Gradio` interface for model inference.
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+ 5. Waiting for about 1min~2min30s, the model inference is completed and the segmentation result and 3D rendering visualization will be produced.
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  Both the original image and the segmentation result are saved in `.nii.gz` format in the `output` folder of the same directory.
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  6. Since `Gradio` performs 1/2 downsampling on the 3D segmentation visualization, the segmentation accuracy is degraded.
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  Users can drag the `.nii.gz` format files in the `output` folder into the `ITK-SNAP` software to view the accurate segmentation visualization.