https://github.com/matsunagalab/colabbtr

End-to-end differentiable blind tip reconstruction on Colab implemented with PyTorch
https://github.com/matsunagalab/colabbtr

afm atomic-force-microscopy blind-tip-reconstruction differentiable-programming

Last synced: 1 day ago
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End-to-end differentiable blind tip reconstruction on Colab implemented with PyTorch

• Host: GitHub
• URL: https://github.com/matsunagalab/colabbtr
• Owner: matsunagalab
• License: mit
• Created: 2024-01-17T08:29:26.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-11-15T06:23:09.000Z (5 days ago)
• Last Synced: 2024-11-15T07:23:46.938Z (5 days ago)
• Topics: afm, atomic-force-microscopy, blind-tip-reconstruction, differentiable-programming
• Language: Jupyter Notebook
• Homepage:
• Size: 15.8 MB
• Stars: 2
• Watchers: 1
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# ColabBTR

End-to-end differentiable blind tip reconstruction on Colab implemented by PyTorch

## Colab notebook

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/matsunagalab/ColabBTR/blob/main/ColabBTR.ipynb)

Example pseudo-AFM file is given in `data/`. Please try it if you do not have any AFM data for analysis.

## Module installation

Requires `PyTorch` and `tqdm`. 

If you need the module, install it directly from GitHub:

```

pip install git+https://github.com/matsunagalab/ColabBTR

```

###