mnistMuddle
deepsvg
| mnistMuddle | deepsvg | |
|---|---|---|
| 2 | 2 | |
| 3 | 885 | |
| - | - | |
| 0.0 | 4.0 | |
| almost 3 years ago | 16 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| - | MIT License |
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mnistMuddle
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Basic Auto Encoder project - Generating poorly written digits [PyTorch]
yes, you are thinking in the right direction. I'm passing the input image to get the latent vector and then decoding it. For each of the 10 classes, I've also computed the average latent vector to represent that label cluster. Check this code here - LINK
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[P] Basic Auto Encoder project - Generating poorly written digits (PyTorch)
Hi, looking for your thoughts and feedback I created this side project to play with latent domain. The aim was to transform an input image to something that looks somewhere between 2 digits. The repository below will give you a practical exposure to Auto Encoders, Latent Domain, PyTorch, Hosting on Streamlit. GitHub Repository - LINK
deepsvg
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[D] MNIST-like dataset in SVG format
I'd like to start experimenting with image classification in SVG format. I've found the deepsvg library that seems to have a solid basis on how to handle SVG files. Unfortunately it doesn't seem there's a large body of resesarch in the area and I am struggling to find a MNIST-like datset in SVG format.
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if Midjourney could "write" I would pay 100 dollar subscription. I mean look at these logos, and they aren't even the best one so far, just what I tried out yesterday. When the words would be what you wanted it would have such a big value.
Cursory google search: https://github.com/alexandre01/deepsvg
What are some alternatives?
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