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The checkpoint saved by train_cvpr.py can be updated by `update_ckpt.py` to remove the additional `module` key due to multi-gpu training.
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# Inference
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You can directly download the [docker file](https://drive.google.com/file/d/1r2KvHP_30nHR3LU7NJEdscVnlZ2hTtcd/view?usp=sharing) for the challenge baseline.
@@ -35,6 +37,6 @@ We provide a Dockerfile to satisfy the challenge format. For more details, refer
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docker build -t vista3d:latest .
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docker save -o vista3d.tar.gz vista3d:latest
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```
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You can also directly run `predict.sh`. Download the finetuned checkpoint and modify the `--model=/your_downloaded_checkpoint'.
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You can also directly run `predict.sh`. Download the finetuned checkpoint and modify the `--model=/your_downloaded_checkpoint`. Change `save_data=True` in `infer_cvpr.py` to save predictions to nifti files for visualization.
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