cbof | Features Pooling for Deep Convolutional Neural Networks | Machine Learning library

by passalis Python Version: Current License: No License

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

kandi X-RAY | cbof Summary

cbof is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. cbof has no bugs, it has no vulnerabilities and it has low support. However cbof build file is not available. You can download it from GitHub.

Bag-of-Features Pooling for Deep Convolutional Neural Networks

Support

Quality

Security

License

Reuse

Support

cbof has a low active ecosystem.

It has 26 star(s) with 11 fork(s). There are 4 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 304 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of cbof is current.

Quality

cbof has 0 bugs and 0 code smells.

Security

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

cbof code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

cbof 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

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

cbof has no build file. You will be need to create the build yourself to build the component from source.

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

cbof saves you 231 person hours of effort in developing the same functionality from scratch.

It has 563 lines of code, 34 functions and 14 files.

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

Top functions reviewed by kandi - BETA

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

Runs the MNIST dataset
Train the model
Evaluate the model
Resize numpy arrays
Calculate the output for a given input
Compute the pairwise distance between two features
Compute the symbolic link probability matrix
Compute symbolic distance matrix

Get all kandi verified functions for this library.

cbof Key Features

No Key Features are available at this moment for cbof.

cbof Examples and Code Snippets

No Code Snippets are available at this moment for cbof.

Community Discussions

Trending Discussions on cbof

vba code to insert row and data in ascending order

QUESTION

vba code to insert row and data in ascending order

Asked 2017-Mar-04 at 09:45

I'm still quite new to VBA and I'm basically self taught. I've developed a spreadsheet for work and I need to alter my code to insert a new row where the data needs to go in ascending order. This is the code I am using currently to have the user form insert the data into the appropriate cells with the information that pertains to each column:

...

ANSWER

Answered 2017-Mar-04 at 03:04

I understand that you data was initially sorted by the part number, and you want each insertion to fit at the appropriate row to keep the sorting valid. You might try this:

Source https://stackoverflow.com/questions/42590124

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

Vulnerabilities

No vulnerabilities reported

Install cbof

You can download it from GitHub.
You can use cbof 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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