SAW-GAN

SAW-GAN: Multi-Granularity Text Fusion Generative Adversarial Networks for Text-to-Image Generation

Dependencies

• python 3.9
• pytorch 1.9
• Install CLIP

In addition, please add the project folder to PYTHONPATH and pip install the following packages:

• python-dateutil
• easydict
• pandas
• torchfile
• nltk
• scikit-image

Data

1. Download the preprocessed metadata for birds coco and extract them to data/
2. Download the birds image data. Extract them to data/birds/
3. Download coco2014 dataset and extract the images to data/coco/images/

Training

cd SAW-GAN/code/

• Train SAW-GAN model:
  • For bird dataset: bash scripts/train.sh ./cfg/bird.yml
  • For coco dataset: bash scripts/train.sh ./cfg/coco.yml

Pretrained Model

• [SAW-GAN for bird] Download and save it to ./code/saved_models/pretrained/
• [SAW-GAN for coco] Download and save it to ./code/saved_models/pretrained/

Validation

 cd SAW-GAN/code/

set pretrained_model in test.sh

• For bird dataset: bash scripts/test.sh ./cfg/bird.yml
• For COCO dataset: bash scripts/test.sh ./cfg/coco.yml