ScoNet_V1

datasets/Scoliosis1K/README.md

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+# 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
+```