# Tutorial for [Scoliosis1K](https://zhouzi180.github.io/Scoliosis1K)

## Download the Scoliosis1K dataset

Download the dataset from the [link](https://zhouzi180.github.io/Scoliosis1K).

decompress these two file by following command:

```shell

unzip -P password Scoliosis1K-pkl.zip   | xargs -n1 tar xzvf

```

password should be obtained by signing [agreement](https://zhouzi180.github.io/Scoliosis1K/static/resources/Scoliosis1KAgreement.pdf) and sending to email (12331257@mail.sustech.edu.cn)

Then you will get Scoliosis1K formatted as:

```

    DATASET_ROOT/

        00000 (subject)/

            positive (category)/

                    000-180 (view)/

                        000.pkl (contains all frames)

        ......

```

## Train the dataset

Modify the `dataset_root` in `configs/sconet/sconet_scoliosis1k.yaml`, and then run this command:

```shell

CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node=4 opengait/main.py --cfgs configs/sconet/sconet_scoliosis1k.yaml --phase train

```

## Process from RAW dataset

### Preprocess the dataset (Optional)

Download the raw dataset from the [official link](https://zhouzi180.github.io/Scoliosis1K). You will get two compressed files, i.e. `Scoliosis1K-raw.zip`, and `Scoliosis1K-pkl.zip`.

We recommend using our provided pickle files for convenience, or process raw dataset into pickle by this command:

```shell

python datasets/pretreatment.py --input_path Scoliosis1K_raw --output_path Scoliosis1K-pkl

```