Spaces:
Sleeping
Sleeping
| # 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. | |