O-CNN | This repository contains the code of our O-CNN paper | Machine Learning library

by wang-ps C++ Version: v1.0 License: No License

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kandi X-RAY | O-CNN Summary

O-CNN is a C++ library typically used in Artificial Intelligence, Machine Learning applications. O-CNN has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

This repository contains the code of our O-CNN paper.

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O-CNN has a low active ecosystem.

It has 31 star(s) with 17 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 4 have been closed. On average issues are closed in 4 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of O-CNN is v1.0

Quality

O-CNN has 0 bugs and 0 code smells.

Security

O-CNN has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

O-CNN code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

O-CNN 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.

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O-CNN releases are available to install and integrate.

Installation instructions are not available. Examples and code snippets are available.

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O-CNN Key Features

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O-CNN Examples and Code Snippets

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Community Discussions

Trending Discussions on O-CNN

Output Image Using keras - how to specify shape for output layer. Input Image and Output Image Dimensions are(210,210,3)

python MNIST dataset "no attribute train_images"

QUESTION

Output Image Using keras - how to specify shape for output layer. Input Image and Output Image Dimensions are(210,210,3)

Asked 2020-Aug-29 at 04:12

I am new to Keras. I am trying to feed a color inverted image into a neural network and then predict the real image. So that my x becomes the inverted image and y becomes the real image. But I am not knowing how to get an output image with keras.

Here is my code.

...

ANSWER

Answered 2020-Aug-24 at 13:22

This is not a classification or regression problem. Thus, the type of neural network that you are using (Convolutional) is not suitable for this problem.

I think neural style transfer would be more appropriate. In this case Generative Adversarial Network (GAN) should be used.
You can read example about it here: https://www.tensorflow.org/tutorials/generative/dcgan

Source https://stackoverflow.com/questions/63561570

QUESTION

python MNIST dataset "no attribute train_images"

Asked 2020-Feb-06 at 22:09

I'm using python3.7 and trying to use MNIST train data images. Instead of using PyTorch, tf, kears framwork which help to use dataset easily, I tried using mnist module directly.

I was following a tutorial for CNN, there was

...

ANSWER

Answered 2020-Feb-06 at 22:09

Actually, you just need to follow the instruction on the Github page of MNIST (link). After installing the lib with pip install python-mnist, you should clone the repo and execute a script to download the mnist data:

Source https://stackoverflow.com/questions/60103428

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

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