請問已經訓練出模型出來，該如何去測試模型分割是否理想？ about 3dunetcnn HOT 6 OPEN

You can generate predictions using predict.py and then create a notebook or script to load the images with nibabel/numpy and generate metrics against the ground truth.
Monai has some metrics you can use: https://docs.monai.io/en/stable/metrics.html

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抱歉我描述錯誤，其實我是想去測試資料集中其中一個nii檔，使用predict.py分割可以得到分割後的nii檔案或圖片。但我不太懂predict.py的參數
python D:\3DUnetCNN\unet3d\scripts\predict.py --output_directory test_seg --config_filename brats2020_config.json --model_filename brats2020_config\fold5\model_best.pth --group test\BraTS20_Training_048_t1.nii

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The filenames in the configuration file are split up into different "groups", typically: "training", "validation", and sometimes "test". If you are using the BRATS 2020 example, I think you should use "validation" as your group.
So the command should look like:
python D:\3DUnetCNN\unet3d\scripts\predict.py --output_directory test_seg --config_filename brats2020_config\fold5\config.json --model_filename brats2020_config\fold5\model_best.pth --group validation

Let me know if that works and I will add it to the tutorial.

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不好意思，我找不到brats2020_config\fold5\config.json這個檔案

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