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Unable to complete Test #6
Comments
Wait..I have an 8gb AMD Radeon RX590 GPU (ie. not CUDA). Am I SOOL? |
I don't understand how this wrapper is supposed to give me an IP to use for ar-cutpaste. |
You need an Nvidia card to be able to use the GPU acceleration. |
When you say my IP, you mean my PC's not my Photoshop server's right? Is there a CUDA equivalent for AMD? I have a powerful GPU so I don't see why mine wouldn't suffice. |
the reason yours wont suffice is because CUDA is a proprietary, close-source, Nvdia project. It has nothing too do with the power of your GPU. For more information: https://en.wikipedia.org/wiki/CUDA There is a theoretical possibility for OpenCL working on your GPU, which seems to be well outside the scope of this project, so I would direct you to pytorch/pytorch#488 (as this implementation of BAS-Net is powered by PyTorch) |
@CapCap, thanks for the reply. I'm a bit confused about how @cyrildiagne is able to demo the plugin on his Macbook Pro then since those run on AMD GPUs. You also bring up another issue I was having trying to install pytorch as instructed in Option 1 of Build from source. PIP doesn't seem to support torch==0.4.1 and therefore, I can't install that. |
@mjsevilla He's only running the photoshop server on his macbook, he's running BasNet in the cloud. You will have a much easier time running this on ubuntu in the cloud: directly running ML on OSX is generally a huge pain. |
@CapCap, ok I'm on the same page now. Is this why there's a Docker option? I apologize, I haven't programmed since college so I feel like I'm re-learning all of this. |
docker makes everything easier in general: no need to worry about mismatched binaries, libraries, drivers, etc |
So in theory, I should be able to get this working on my machine if I use docker.. |
... and you had a Nvidia GPU, yes |
And here I thought I went the right route going full-AMD on my PC build, lol. Thanks for your help. |
Input:
PS C:\Users\micha\OneDrive\Documents\basnet-http-master>
docker run --rm -p 8080:80 gcr.io/cyrildiagne-ml/basnet-http
Output:
Saved file tree to doc-filelist.js
Copied JS to doc-script.js
Compiled CSS to doc-style.css
Input:
PS C:\Users\micha\OneDrive\Documents\basnet-http-master>
curl -F "data=@test.jpg" http://localhost:8080 -o result.png
Output:
The text was updated successfully, but these errors were encountered: