OpenGait/datasets/SUSTech1K/README.md

Tutorial for SUSTech1K

Download the SUSTech1K dataset

Download the dataset from the link. decompress these two file by following command:

unzip -P password SUSTech1K-pkl.zip   | xargs -n1 tar xzvf

password should be obtained by signing agreement and sending to email (shencf2019@mail.sustech.edu.cn)

Train the dataset

Modify the dataset_root in configs/lidargait/lidargait_sustech1k.yaml, and then run this command:

CUDA_VISIBLE_DEVICES=0,1,2,3 python -m torch.distributed.launch --nproc_per_node=4 opengait/main.py --cfgs configs/lidargait/lidargait_sustech1k.yaml --phase train

Process from RAW dataset

Preprocess the dataset (Optional)

Download the raw dataset from the official link. You will get two compressed files, i.e. DATASET_DOWNLOAD.md5, SUSTeck1K-RAW.zip, and SUSTeck1K-pkl.zip. We recommend using our provided pickle files for convenience, or process raw dataset into pickle by this command:

python datasets/SUSTech1K/pretreatment_SUSTech1K.py -i SUSTech1K-Released-2023 -o SUSTech1K-pkl -n 8

Projecting PointCloud into Depth image (Optional)

You can use our processed depth images, or you can process via the command:

python datasets/SUSTech1K/point2depth.py -i SUSTech1K-Released-2023/ -o SUSTech1K-Released-2023/ -n 8

We recommend using our provided depth images for convenience.