Datasets:
YongchengYAO
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update doc
Browse files- doc/dataset_skm-tea.md +20 -20
doc/dataset_skm-tea.md
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@@ -16,13 +16,13 @@ This tutorial is about:
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```
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# Files from SKM-TEA source
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├── v1-release
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```
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```
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├── Masks
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├── MTR_001.nii.gz
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├── ...
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```
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## How to preprocess data?
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⚠️ DO NOT change file or folder names. See why here
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1. Go to the parent folder of `dicoms`, install [`dcm2niix`](https://github.com/rordenlab/dcm2niix), add processing script
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# local file structure
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├── [your folder]
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├── Masks
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```
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```bash
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# local file structure
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├── [your folder]
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├── Masks
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```
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2. Put these folders into `SKM-TEA-nii` and upload the **compressed** file to your HF dataset repo
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```
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# DO NOT use other folder names
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├── SKM-TEA-nii
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```
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Your HF repo should contain `SKM-TEA-nii.zip`
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```
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# Files from SKM-TEA source
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├── v1-release
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├── dicoms
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├── MTR_001.tar.gz
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├── ...
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├── segmentation_masks
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├── raw-data-track
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├── MTR_001.nii.gz
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├── ...
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```
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```
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├── Masks
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├── MTR_001.nii.gz
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├── ...
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├── dicoms
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├── MTR_001.tar.gz
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├── ...
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```
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## How to preprocess data?
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⚠️ DO NOT change file or folder names. See why [here](https://huggingface.co/datasets/YongchengYAO/MedVision/blob/main/src/medvision_ds/datasets/SKM_TEA/download.py).
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1. Go to the parent folder of `dicoms`, install [`dcm2niix`](https://github.com/rordenlab/dcm2niix), add processing script
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# local file structure
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├── [your folder]
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├── Masks
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├── dicoms
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├── prepare-skm-tea.sh # <-- add this
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```
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```bash
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# local file structure
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├── [your folder]
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├── Masks
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├── dicoms
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├── Images-E1
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├── Images-E2
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├── prepare-skm-tea.sh
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```
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2. Put these folders into `SKM-TEA-nii` and upload the **compressed** file to your HF dataset repo
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```
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# DO NOT use other folder names
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├── SKM-TEA-nii
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├── Images-E1
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├── Images-E2
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├── Masks
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```
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Your HF repo should contain `SKM-TEA-nii.zip`
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