sj-li / smis Goto Github PK

Semantically Multi-modal Image Synthesis(CVPR2020).
Zhen Zhu, Zhiliang Xu, Ansheng You, Xiang Bai

• torch>=1.0.0
• torchvision
• dominate
• dill
• scikit-image
• tqdm
• opencv-python

DeepFashion
Note: We provide an example of the DeepFashion dataset. That is slightly different from the DeepFashion used in our paper due to the impact of the COVID-19.

Cityscapes
The Cityscapes dataset can be downloaded at here

ADE20K
The ADE20K dataset can be downloaded at here

Download the tar of the pretrained models from the Google Drive Folder. Save it in checkpoints/ and unzip it. There are deepfashion.sh, cityscapes.sh and ade20k.sh in the scripts folder. Change the parameters like --dataroot and so on, then comment or uncomment some code to test/train model. And you can specify the --test_mask for SMIS test.

Our code is based on the popular SPADE