Awesome
Environment Setup
conda create -n SCT python=3.8
conda activate SCT
pip install -r requirements.txt
Data Preparation
1. Visual Task Adaptation Benchmark (VTAB)
-
Images
Please refer to VTAB-source to download the datasets.
2. Few-Shot and Domain Generation
-
Images
Please refer to DATASETS.md to download the datasets.
-
Train/Val/Test splits
Please refer to files under
data/XXX/XXX/annotations
for the detail information.
Quick Start For SCT
We use the VTAB experiments as examples.
1. Downloading the Pre-trained Model
Model | Link |
---|---|
ViT-B/16 | link |
ViT-L/16 | link |
ViT-H/14 | link |
Swin-B | link |
mkdir released_models
wget https://storage.googleapis.com/vit_models/imagenet21k/ViT-B_16.npz
wget https://github.com/SwinTransformer/storage/releases/download/v1.0.0/swin_base_patch4_window7_224_22k.pth
2. Training
sh run_model_sct.sh
Acknowledgement
Part of the code is borrowed from timm.