Download.md

May 19, 2023 ยท View on GitHub

Download

  1. Create directories for pretrained models and datasets.

    export REPO_DIR=$PWD
mkdir -p $REPO_DIR/models  # pre-trained models
mkdir -p $REPO_DIR/datasets  # datasets

  2. Download pretrained backbone and model checkpoints from Google Drive

    The weights of pretrained backbones are provided from the previous project ROMP

    The resulting data structure should follow the hierarchy as below.

    ${REPO_DIR}  
|-- models  
|   |-- PointHMR_h36m.bin
|   |-- PointHMR_3dpw.bin
|   |-- pretrain_hrnet.pkl
|   |-- pretrain_resnet.pkl
|-- src 
|-- datasets 
|-- predictions 
|-- README.md 
|-- ... 
|-- ...

  3. Download SMPL and MANO models from their official websites

    To run our code smoothly, please visit the following websites to download SMPL and MANO models.

    • Download basicModel_neutral_lbs_10_207_0_v1.0.0.pkl from SMPLify, and place it at ${REPO_DIR}/src/modeling/data.
    • Download MANO_RIGHT.pkl from MANO, and place it at ${REPO_DIR}/src/modeling/data.

    Please put the downloaded files under the ${REPO_DIR}/src/modeling/data directory. The data structure should follow the hierarchy below.

    ${REPO_DIR}  
|-- src  
|   |-- modeling
|   |   |-- data
|   |   |   |-- basicModel_neutral_lbs_10_207_0_v1.0.0.pkl
|   |   |   |-- MANO_RIGHT.pkl
|-- models
|-- datasets
|-- predictions
|-- README.md 
|-- ... 
|-- ...

    Please check /src/modeling/data/README.md for further details.

  4. Download datasets and pseudo labels for training.

    We use the same data from the previous project METRO

    We recommend to download large files with AzCopy for faster speed. AzCopy executable tools can be downloaded here. Decompress the azcopy tar file and put the executable in any path.

    To download the annotation files, please use the following command.

    cd $REPO_DIR
path/to/azcopy copy 'https://datarelease.blob.core.windows.net/metro/datasets/filename.tar' /path/to/your/folder/filename.tar
tar xvf filename.tar

    filename.tar could be Tax-H36m-coco40k-Muco-UP-Mpii.tar, human3.6m.tar, coco_smpl.tar, muco.tar, up3d.tar, mpii.tar, 3dpw.tar, freihand.tar. Total file size is about 200 GB.

    The datasets and pseudo ground truth labels are provided by Pose2Mesh. We only reorganize the data format to better fit our training pipeline. We suggest to download the orignal image files from the offical dataset websites.

    The datasets directory structure should follow the below hierarchy.

    ${ROOT}  
|-- models 
|-- src
|-- datasets  
|   |-- Tax-H36m-coco40k-Muco-UP-Mpii  
|   |   |-- train.yaml 
|   |   |-- train.linelist.tsv  
|   |   |-- train.linelist.lineidx
|   |-- human3.6m  
|   |   |-- train.img.tsv 
|   |   |-- train.hw.tsv 
|   |   |-- train.linelist.tsv    
|   |   |-- smpl/train.label.smpl.p1.tsv
|   |   |-- smpl/train.linelist.smpl.p1.tsv
|   |   |-- valid.protocol2.yaml
|   |   |-- valid_protocol2/valid.img.tsv 
|   |   |-- valid_protocol2/valid.hw.tsv  
|   |   |-- valid_protocol2/valid.label.tsv
|   |   |-- valid_protocol2/valid.linelist.tsv
|   |-- coco_smpl  
|   |   |-- train.img.tsv  
|   |   |-- train.hw.tsv   
|   |   |-- smpl/train.label.tsv
|   |   |-- smpl/train.linelist.tsv
|   |-- muco  
|   |   |-- train.img.tsv  
|   |   |-- train.hw.tsv   
|   |   |-- train.label.tsv
|   |   |-- train.linelist.tsv
|   |-- up3d  
|   |   |-- trainval.img.tsv  
|   |   |-- trainval.hw.tsv   
|   |   |-- trainval.label.tsv
|   |   |-- trainval.linelist.tsv
|   |-- mpii  
|   |   |-- train.img.tsv  
|   |   |-- train.hw.tsv   
|   |   |-- train.label.tsv
|   |   |-- train.linelist.tsv
|   |-- 3dpw 
|   |   |-- train.img.tsv  
|   |   |-- train.hw.tsv   
|   |   |-- train.label.tsv
|   |   |-- train.linelist.tsv
|   |   |-- test_has_gender.yaml
|   |   |-- has_gender/test.img.tsv 
|   |   |-- has_gender/test.hw.tsv  
|   |   |-- has_gender/test.label.tsv
|   |   |-- has_gender/test.linelist.tsv
|   |-- freihand
|   |   |-- train.yaml
|   |   |-- train.img.tsv  
|   |   |-- train.hw.tsv   
|   |   |-- train.label.tsv
|   |   |-- train.linelist.tsv
|   |   |-- test.yaml
|   |   |-- test.img.tsv  
|   |   |-- test.hw.tsv   
|   |   |-- test.label.tsv
|   |   |-- test.linelist.tsv
|-- README.md 
|-- ... 
|-- ...