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Inference on StyleGAN-generated images
I'm trying to use AutoGAN to detect StyleGAN-generated facial images.
- Do you have any examples of how to run the detector in any random image?
- Are any of the models in the Google Drive pre-trained with facial images?
Thanks!
Syntax error in code/run_test.py; missing close square bracket
The file code/run_test.py has a syntax error and is missing a close square bracket:
elif args.dataset == 'AutoGAN':
datasets = ['horse_auto', 'zebra_auto', 'summer_auto', 'winter_auto', 'apple_auto', 'orange_auto', 'facades_auto', 'cityscapes_auto', 'satellite_auto', 'ukiyoe_auto', 'vangogh_auto', 'cezanne_auto', 'monet_auto', 'photo_auto',
else:
How is this line supposed to end? For now I've just ended it after the final comma.
There is no autogan folder..
Pretrained models do not contain checkpoint file
The pretrained model obtained from
https://drive.google.com/open?id=1IZZ5QCLbzAmrPDHh7EdOigPCdz46zPc6
does not have any file that matches the path {}{}/checkpoint_{}.pth
. Each of the folders has the format
/tmp/autogan_model/monet_autogan
/tmp/autogan_model/monet_autogan/latest_net_G.pth
/tmp/autogan_model/monet_autogan/latest_net_D_A.pth
/tmp/autogan_model/monet_autogan/test_opt.txt
/tmp/autogan_model/monet_autogan/train_opt.txt
Are there pretrained checkpoints for running the detector?
About the place of pretrained CycleGAN
Thanks for your work.
I noticed that there are 18 pretrained model to make the dataset.
And the script to download the models have failed. So I want to know if I should put them to the "autogan/scripts" and then run the "run_test.py"?
I got the error when I try to "python run_test.py --dataset Cyclegan" :
NameErroe: "parser" is not defined
Hello, can you release your trained GAN-Detection model parameters?
Hello, can you release your trained GAN-Detection model parameters?
No such file or directory: './datasets/horse_train.pt'
Hi, I got the error when I try to train the classifier
$ python run_training.py --dataset=CycleGAN --feature=fft --gpu-id=0
Test Parameter: --feature=fft
python GAN_Detection_Train.py --training-set horse --model=resnet --test-set=transposed_conv --data_augment --batch-size=16 --test-batch-size=16 --feature=fft --gpu-id 0 --model-dir ./model_resnet/ --log-dir ./resnet_log/ --enable-logging=False --epochs 20
Wait for process end
/home/lab/miniconda3/envs/AutoGAN/lib/python3.8/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and will be removed in 0.15, please use 'weights' instead.
warnings.warn(
/home/lab/miniconda3/envs/AutoGAN/lib/python3.8/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or None
for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing weights=ResNet34_Weights.IMAGENET1K_V1
. You can also use weights=ResNet34_Weights.DEFAULT
to get the most up-to-date weights.
warnings.warn(msg)
Caching data ./datasets/horse_train.pt
Traceback (most recent call last):
File "GAN_Detection_Train.py", line 434, in
train_loader, test_loaders = create_loaders()
File "GAN_Detection_Train.py", line 261, in create_loaders
GANDataset(train=True,
File "GAN_Detection_Train.py", line 169, in init
super(GANDataset, self).init(train=train, *arg, **kw)
File "/home/lab/Downloads/AutoGAN/code/cycleGAN_dataset.py", line 68, in init
self.cache_data(data_file, name, check_cached)
File "/home/lab/Downloads/AutoGAN/code/cycleGAN_dataset.py", line 103, in cache_data
with open(data_file, 'wb') as f:
FileNotFoundError: [Errno 2] No such file or directory: './datasets/horse_train.pt'
Thanks for your work,
Robert
conda environment fails
Hello,
When installing the conda env it fails (for e.g. intel package is not found, conflicts etc).
Do you have another yml file?
Maybe a docker image - or some enviroment details you have - like linux version, python version, conda version.
Adrian
Hello, can you give me the original picture of of these two face images
Q
Excuse me, will the code of your paper be published on github?
I am looking forward to it, thank you.
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