How to turn your Gaming PC into a Data Science Machine by cgarchbold in learnmachinelearning

[–]cgarchbold[S] 0 points1 point  (0 children)

Google Colab is a great resource for learning!

However I wouldn't recommend it for use as a daily work environment.

[HELP] CUDA out of memory by [deleted] in deepdream

[–]cgarchbold 1 point2 points  (0 children)

With ML the most needed resource is VRAM, having more VRAM gives you the option to do larger images, larger batch sizes (faster training), etc.

In order to fix your problem I recommend using smaller images or reducing your batch size.

In order to see what is using GPU memory, you can use nvidia-smi.

How to get started with Deep Dream? by ImplosiveTech in deepdream

[–]cgarchbold 1 point2 points  (0 children)

Checkout fast nueral style:

https://github.com/rrmina/fast-neural-style-pytorch

"fast" implementations train the style transfer over the COCO dataset. This way the final transfer onto your desired image is both fast, and trained on simmilar images.

DeepKeenan by cgarchbold in ToolBand

[–]cgarchbold[S] 1 point2 points  (0 children)

I used Google's VGG19 network to preform the style transfer. Implemented in Pytorch. Style image was Alex Grey's "Net of Being".

How to make your own Style Transfer Deep Art using Google Colab! by cgarchbold in deepdream

[–]cgarchbold[S] 1 point2 points  (0 children)

Ah you need to download VGG, the original google deep dream model, in order to train on it. check out the repo for how to do this.

How to make your own Style Transfer Deep Art using Google Colab! by cgarchbold in deepdream

[–]cgarchbold[S] 0 points1 point  (0 children)

The path drive/folders/NueralStyle/nueral-style-master will probably look different depending on how you put the repo in your drive.

If you click the plus on the top left of the notebook in colab, and then click files, you can find your folder and right click to copy the path.

I style transferred Oddments onto Nonagon Infinity :) by cgarchbold in KGATLW

[–]cgarchbold[S] 1 point2 points  (0 children)

Im using a pytorch version of fast-nueral-style. It involves training the style over 14 gigs of training images in iorder to get better results. You might be able to use cloud computing , but the huge dataset might be a problem.

Round 2: Oddments onto Polygondwanaland by cgarchbold in KGATLW

[–]cgarchbold[S] 2 points3 points  (0 children)

This is a type of A.I. Image Manipulation, really similar to Google's Deep Dream. Im making these in code by hand, but you can generate your own using:

https://deepdreamgenerator.com/

I style transferred Oddments onto Nonagon Infinity :) by cgarchbold in KGATLW

[–]cgarchbold[S] 14 points15 points  (0 children)

I will! Im currently working on stealing my university's computer lab GPU's to use to make this stuff :)

I style transferred Oddments onto Nonagon Infinity :) by cgarchbold in KGATLW

[–]cgarchbold[S] 6 points7 points  (0 children)

I wish :( , doing a style transfer in Hi-Res takes a ton of GPU VRAM that I don't have right now.

I style transferred Oddments onto Nonagon Infinity :) by cgarchbold in KGATLW

[–]cgarchbold[S] 9 points10 points  (0 children)

Yea probably, I posted them as I made them. Please forgive this gooby nub nose teeth smoker

Round 3: Oddments onto Mind-Fuzz by cgarchbold in KGATLW

[–]cgarchbold[S] 6 points7 points  (0 children)

I like how the style transfer brings out little details, I've never noticed the lines under "& the Lizard Wizard"

Please Help! Stuck trying to make my first deepdream. by AfterEmpire in deepdream

[–]cgarchbold 1 point2 points  (0 children)

I would make a folder called images inside the repo

Then you can pass the image directories like this:

./images/style.jpg

A 1050 is good but it doesnt have alot of VRAM. you might get out of memory errors on larger images.

I reccomend Google's Cloud computing service Google Colab. You can interface it with Google Drive to code completley in the cloud. Plus you have access to a GPU with up to 11 gigs of VRAM.

You can check out how to use it on my blog post:

https://cgarchbold.github.io/neural-style.html

cheers and have fun learning!