The ${ROOT}
is described as below.
${ROOT}
|-- common
|-- data
|-- demo
|-- main
|-- output
common
contains kernel codes for ClothWild.data
contains required data and soft links to images and annotations directories.demo
contains demo codes.main
contains high-level codes for training or testing the network.output
contains log, trained models, visualized outputs, and test result.
You need to follow directory structure of the data
as below.
${ROOT}
|-- data
| |-- base_data
| | |-- human_models
| | | |-- SMPL_FEMALE.pkl
| | | |-- SMPL_MALE.pkl
| | | |-- SMPL_NEUTRAL.pkl
| | |-- smplicit
| | | |-- checkpoints
| | | | |-- hair.pth
| | | | |-- pants.pth
| | | | |-- shoes.pth
| | | | |-- skirts.pth
| | | | |-- upperclothes.pth
| | | |-- clusters
| | | | |-- clusters_hairs.npy
| | | | |-- clusters_lowerbody.npy
| | | | |-- clusters_shoes.npy
| | | | |-- indexs_clusters_tshirt_smpl.npy
| |-- preprocessed_data
| | |-- densepose
| | |-- gender
| | |-- parse
| | |-- smpl_param
| |-- ...
base_data/human_model_files
containssmpl
3D model files. Download the files from [smpl].base_data/smplicit
contains 3D cloth generative model (SMPLicit
) files. Download the files from [smplicit].preprocessed_data
is required for training and testing stages. Download it from [preprocessed_data].
${ROOT}
|-- data
| |-- ...
| |-- DeepFashion2
| | |-- data
| | | |-- train
| | | |-- DeepFashion2_train.json
| |-- MSCOCO
| | |-- images
| | | |-- train2017
| | | |-- val2017
| | |-- parses
| | |-- annotations
| | | |-- coco_wholebody_train_v1.0.json
| | | |-- coco_wholebody_val_v1.0.json
| | | |-- coco_dp_train.json
| | | |-- coco_dp_val.json
| |-- PW3D
| | |-- data
| | | |-- imageFiles
| | | |-- sequenceFiles
| | | |-- 3DPW_test.json
- Download DeepFashion2 parsed data [data] [annot]
- Download MSCOCO data, parses (LIP dataset), and densepose [data] [parses] [densepose]
- Download 3DPW parsed data [data] [annot]
- All annotation files follow MSCOCO format. If you want to add your own dataset, you have to convert it to MSCOCO format.
${ROOT}
|-- output
| |-- log
| |-- model_dump
| |-- result
| |-- vis
- Creating
output
folder as soft link form is recommended instead of folder form because it would take large storage capacity. log
folder contains training log file.model_dump
folder contains saved checkpoints for each epoch.result
folder contains final estimation files generated in the testing stage.vis
folder contains visualized results.