deep_multispectral_demosaicing | source code implementation

 by   dedale-fet Jupyter Notebook Version: Current License: No License

kandi X-RAY | deep_multispectral_demosaicing Summary

kandi X-RAY | deep_multispectral_demosaicing Summary

deep_multispectral_demosaicing is a Jupyter Notebook library. deep_multispectral_demosaicing has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

This is the source code implementation of demosaicinb multispectral images with 3x3 macropixels using deep learning. The network model used is inspired from [VDSR]. The network is trained on the public datasets from Tokyotech and on the CAVE MSI dataset, projected onto a 9-bands camera. To run demo_multispectral_demosaicing.ipynb, you need to have Python, Caffe2, and the spectral package installed.
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              deep_multispectral_demosaicing has a low active ecosystem.
              It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.
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              It had no major release in the last 6 months.
              There are 1 open issues and 0 have been closed. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of deep_multispectral_demosaicing is current.

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              deep_multispectral_demosaicing has no bugs reported.

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              deep_multispectral_demosaicing has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

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              deep_multispectral_demosaicing does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              deep_multispectral_demosaicing releases are not available. You will need to build from source code and install.

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            gh repo clone dedale-fet/deep_multispectral_demosaicing

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