data-efficient-gans icon indicating copy to clipboard operation
data-efficient-gans copied to clipboard

[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training

Results 26 data-efficient-gans issues
Sort by recently updated
recently updated
newest added

train_set: ![image](https://user-images.githubusercontent.com/39071957/174749833-f02645a7-46ba-4e2d-82c2-aeda99dfeec9.png) generated images: ![image](https://user-images.githubusercontent.com/39071957/174749451-b533a298-7fa7-4f12-8e42-038acf91e339.png) @click.option('--outdir',default='/work/ai_lab/miner/data-efficient-gans/output', help='Where to save the results', required=True, metavar='DIR') @click.option('--gpus',default=2, help='Number of GPUs to use [default: 1]', type=int, metavar='INT') @click.option('--snap',default=10, help='Snapshot interval [default: 50 ticks]', type=int,...

op.h exists nowhere in my python environment.. where do I get it? (tf115py37) c:\Programming\PythonNotebooks\DataEfficientGans\data-efficient-gans\DiffAugment-stylegan2>python run_low_shot.py --dataset=100-shot-obama --resolution=64 2020-12-20 02:40:10.999131: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library cudart64_100.dll Local submit - run_dir:...

I'm trying to create a new model by myself by using the following command: ``` shell python train.py --outdir=training-runs --data=https://data-efficient-gans.mit.edu/datasets/100-shot-obama.zip --gpus=1 ``` And I ran into the Error: return _VF.meshgrid(tensors,...

For example, in Figure 5 (b), you plot the D's accuracy on T(x), T(G(z)), and G(z), I wonder how this metric was calculated. After each update of discriminator or after...

Hello, I have trained using a 100 set of grayscale images, now I am stuck in the generate.py because it is all set for generating RGB images. I get this...

Hi, I read the paper and it very sounds. I have been trying NVIDIA StyleGanV2-ADA for weeks without success. It simply did not converge and generated images were full of...

Hi, is there a way to train using a dataset of images with shape that is not a power of 2? Such as 400x400 or even 420x400? Thank you Davide

Hi, I'd like to generate plots of Nearest neighbors in pixel space like Figure 16 from your paper. Could you guide if this method was included in this repository please?...