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# De-Fake
It is the code for the paper: DE-FAKE: Detection and Attribution of Fake Images Generated by Text-to-Image Generation Models.
### Environment
You first need to build the environment by:
```
conda env create -f environment.yaml
conda activate defake
```
### Infer
For the usage, You can download our model on
https://drive.google.com/file/d/1qI7x5iodaCFq0S61LKw4wWjql7cYou_4/view?usp=sharing
and
https://drive.google.com/file/d/1SuenxJP10VwArC6zW0SHMUGObMRqQhBD/view?usp=sharing
for the encoder and classifier.
Then test on
```
python test.py --image_path XXX
```
### Train
If you want to train the detector yourself, please enter the correct file path in train.py.
Then
```
python train.py
```
### License
DeFake is licensed under the term of thr MIT license. See LICENSE for more details.
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