Image-Super-Resolution | Implementation of Super Resolution CNN in Keras | Machine Learning library

by titu1994 Python Version: v0.1 License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | Image-Super-Resolution Summary

Image-Super-Resolution is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Keras applications. Image-Super-Resolution has no bugs, it has no vulnerabilities and it has medium support. However Image-Super-Resolution build file is not available. You can download it from GitHub.

Implementation of Image Super Resolution CNN in Keras from the paper Image Super-Resolution Using Deep Convolutional Networks. Also contains models that outperforms the above mentioned model, termed Expanded Super Resolution, Denoiseing Auto Encoder SRCNN which outperforms both of the above models and Deep Denoise SR, which with certain limitations, outperforms all of the above.

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Quality

Security

License

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Support

Image-Super-Resolution has a medium active ecosystem.

It has 809 star(s) with 271 fork(s). There are 37 watchers for this library.

It had no major release in the last 12 months.

There are 16 open issues and 27 have been closed. On average issues are closed in 27 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Image-Super-Resolution is v0.1

Quality

Image-Super-Resolution has 0 bugs and 0 code smells.

Security

Image-Super-Resolution has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Image-Super-Resolution code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Image-Super-Resolution does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

Image-Super-Resolution releases are available to install and integrate.

Image-Super-Resolution has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

Image-Super-Resolution saves you 4786 person hours of effort in developing the same functionality from scratch.

It has 10094 lines of code, 64 functions and 10 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed Image-Super-Resolution and discovered the below as its top functions. This is intended to give you an instant insight into Image-Super-Resolution implemented functionality, and help decide if they suit your requirements.

Scale image
Match image size
Create a model
Create a convolutional model
Residual residual block
Resize a block of image
Train the model
Compute the gram matrix
Convenience function to scale x
Transport of depth to scale
Scale the input into a dimension
Evaluate the model
Validate a super resolution model
Validate image against validation set
Calculates the PSR

Get all kandi verified functions for this library.

Image-Super-Resolution Key Features

No Key Features are available at this moment for Image-Super-Resolution.

Image-Super-Resolution Examples and Code Snippets

No Code Snippets are available at this moment for Image-Super-Resolution.

Community Discussions

Trending Discussions on Image-Super-Resolution

Github - how to download hdf5 file?

QUESTION

Github - how to download hdf5 file?

Asked 2019-Sep-25 at 05:55

How to download raw file in GitHub? I am trying to download a concrete (RAW) file. The GitHub reports size 16.7 MB (see screenshot bellow), when clicked to RAW it only displays text containing few bytes.

Screen

...

ANSWER

Answered 2019-Sep-24 at 10:35

Solution for this particular problem can be to download the files from this repository https://drive.google.com/drive/folders/1cJLPgGfEuFAQzBKbXQtSGXxLXssw1D9f

Anyway, if there is any way how to download HDF5 files from github, it would be very useful.

Source https://stackoverflow.com/questions/58078170

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Image-Super-Resolution

Supports Keras with Theano and Tensorflow backend. Due to recent report that Theano will no longer be updated, Tensorflow is the default backend for this project now. Requires Pillow, imageio, sklearn, scipy, keras 2.3.1, tensorflow 1.15.0.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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