First, clone the repository to a desired location.
Conda Environment
The following commands will create a local Anaconda environment with the necessary packages installed.
conda create -n shaf -y python=3.8
conda activate shaf
pip install -r requirements.txt
Datasets
Experiments are conducted on two standard datasets -- Fashion-IQ and SHOES, please see their repositories for download instructions.
Training
model for training
# Optional: comet experiment logging --api-key and --workspace
python src/combiner_train.py --dataset
dataset_name
--projection-dim
2048
--hidden-dim
4096
--num-epochs
200
--clip-model-name
RN50x4
--combiner-lr
2e-5
--batch-size
512
--clip-bs
32
--transform
targetpad
--target-ratio
1.25
--validation-frequency
1
License
MIT License applied. In line with licenses from CLIP4Cir and FashionCLIP.
Our implementation is based on CLIP4Cir