PINet_PG

Code for our PG paper Human Pose Transfer by Adaptive Hierarchical Deformation

This is Pytorch implementation for pose transfer on DeepFashion dataset. The code is extramly borrowed from Pose Transfer. Thanks for their work!

Requirement

• Python 3
  
• pytorch 1.2
  
• torchvision
  
• numpy
  
• scipy
  
• scikit-image
  
• pillow
  
• pandas
  
• tqdm
  
• dominate
  

Data

Data preparation for images and keypoints can follow Pose Transfer Parsing data can be found from baidu, password:abcd

Test

You can directly download our test results from baidu (fetch code: abcd).
Pre-trained checkpoint can be found from baidu (fetch code: abcd) and put it in the folder (-->checkpoints-->fashion_PInet_PG).

Test by yourself
python test.py --dataroot ./fashion_data/ --name fashion_PInet_PG --model PInet --phase test --dataset_mode keypoint --norm instance --batchSize 1 --resize_or_crop no --gpu_ids 0 --BP_input_nc 18 --no_flip --which_model_netG PInet --checkpoints_dir ./checkpoints --pairLst ./fashion_data/fasion-resize-pairs-test.csv --which_epoch latest --results_dir ./results