These are awesome. Do you think I could get a zip file with these images? I just grabbed 200 images for a set but don't want to do it again for another set.
Here's a little experiment. I made a video by changing the input to the generator slightly over each frame. The result is some kind of AI lava lamp: https://gfycat.com/FluidFlawlessIndianjackal
I can't take full credit of the source code. It's based on this implementation on github: https://github.com/moxiegushi/pokeGAN. I added things like gradient penalty for improved training, changed the architecture to handle the different input/output, added dropout, improved output processing etc.
I don't mind sharing it. Just give me a few days to find some hyperparameters that give the nicest results. I only have access to the GTX 1070 during the weekends unfortunately. The GTX 680 doesn't have enough memory...
Here's the latest batch with lower dropout rate: https://imgur.com/a/G0yFY
Are you in touch with the people running @roborosewater? Do you know if it's still actively being worked on?
Hi everyone, this is my first time posting here. It looks like I've had the same idea as you using GANs for the roborosewater card generator. Honestly I'm not up to date on what the status of this is but maybe this is of use.
Training took about 24h on a GTX 1070. They all have a resolution of 400x300 which is close to the aspect ratio of the actual artwork. I used a high dropout rate meaning that the generator didn't overfit. So none of the results should look similar to any existing cards. The one drawback being that most of them won't make any sense at all.
I'll try a slightly different network architecture with a lower dropout rate next. Just to see what that would look like.
Let me know if anyone is interested in them. I can send you the model to generate more, or just upload as many pictures as you want.
Sure, 3000+ images fresh from the oven: https://www.dropbox.com/s/udj71rp2y56tu47/output.zip?dl=0
Here's a little experiment. I made a video by changing the input to the generator slightly over each frame. The result is some kind of AI lava lamp: https://gfycat.com/FluidFlawlessIndianjackal
I can't take full credit of the source code. It's based on this implementation on github: https://github.com/moxiegushi/pokeGAN. I added things like gradient penalty for improved training, changed the architecture to handle the different input/output, added dropout, improved output processing etc.
I don't mind sharing it. Just give me a few days to find some hyperparameters that give the nicest results. I only have access to the GTX 1070 during the weekends unfortunately. The GTX 680 doesn't have enough memory...
Here's the latest batch with lower dropout rate: https://imgur.com/a/G0yFY
Are you in touch with the people running @roborosewater? Do you know if it's still actively being worked on?
Here are some more pictures: https://imgur.com/a/o0mWf
Training took about 24h on a GTX 1070. They all have a resolution of 400x300 which is close to the aspect ratio of the actual artwork. I used a high dropout rate meaning that the generator didn't overfit. So none of the results should look similar to any existing cards. The one drawback being that most of them won't make any sense at all.
I'll try a slightly different network architecture with a lower dropout rate next. Just to see what that would look like.
Let me know if anyone is interested in them. I can send you the model to generate more, or just upload as many pictures as you want.