mnistMuddle
handwritten-multi-digit-number-recognition
| mnistMuddle | handwritten-multi-digit-number-recognition | |
|---|---|---|
| 2 | 1 | |
| 3 | 21 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 3 years ago | over 2 years 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
handwritten-multi-digit-number-recognition
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I made a handwritten number recognizer
Github repo: https://github.com/kingyiusuen/handwritten-multi-digit-number-recognition
What are some alternatives?
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