AER-CNN-KERAS | Convolutional Neural Network based implementation | Machine Learning library

by Shahnawax Python Version: Current License: No License

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

kandi X-RAY | AER-CNN-KERAS Summary

AER-CNN-KERAS is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras, Neural Network applications. AER-CNN-KERAS has no bugs, it has no vulnerabilities and it has low support. However AER-CNN-KERAS build file is not available. You can download it from GitHub.

Convolutional Neural Network based implementation of Audio Event Recognition in KERAS

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Support

AER-CNN-KERAS has a low active ecosystem.

It has 12 star(s) with 9 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 812 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of AER-CNN-KERAS is current.

Quality

AER-CNN-KERAS has no bugs reported.

Security

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

License

AER-CNN-KERAS 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

AER-CNN-KERAS releases are not available. You will need to build from source code and install.

AER-CNN-KERAS has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

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

Builds the training dataset
Sum the total number of training files
Shuffle the given paths
Encode a class
Return a numpy array of sample sizes
Returns a list of the names of the class names
Construct a CNN model
Prints the accuracy of each class
Rename files in a folder
Compute the confusion matrix for the given GT and PR
Calculate the class id for each class
Return a list of the names of the class names

Get all kandi verified functions for this library.

AER-CNN-KERAS Key Features

No Key Features are available at this moment for AER-CNN-KERAS.

AER-CNN-KERAS Examples and Code Snippets

No Code Snippets are available at this moment for AER-CNN-KERAS.

Community Discussions

Trending Discussions on AER-CNN-KERAS

.wk file from NNIE_Mapper not valid when running for runtime

QUESTION

.wk file from NNIE_Mapper not valid when running for runtime

Asked 2020-Mar-13 at 05:22

First, some background:

There are 2 ML models:

With 50 output nodes
With 5 output nodes

Both are first trained using https://github.com/dwayo-gh/AER-CNN-KERAS, and converted to caffemodel using https://github.com/uhfband/keras2caffe.git.

The story of the model with 50 output nodes: Using RuyiStudio on Windows10 environment, I converted prototxt + weights to .wk file. The size of the resulting .wk file is 594112bytes.

Then I modified HiSVP SDK's "sample_runtime" example to run this new .wk file (source below). Functional simulation worked fine! It gave top 5 inference results for the input file.

The story of the model with 5 output nodes: Using RuyiStudio, again, on Win10 environment, I converted the files to .wk, changed the path in the runtime sources. Size of the resulting .wk file is 329776bytes. Following is the error I encountered:

...

ANSWER

Answered 2020-Mar-13 at 05:22

The .wk created was using NNIE_Mapper which produces a format not usable for runtime simulation.

Creating project with type "Runtime" in RuyiStudio, or using runtime_mapper under Linux produces a valid .wk and solves the problem!

Wish the error messages were better, but oh well!

Thanks OpenPIC community on Telegram!

Source https://stackoverflow.com/questions/60649662

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

Vulnerabilities

No vulnerabilities reported

Install AER-CNN-KERAS

You can download it from GitHub.
You can use AER-CNN-KERAS like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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