Image-Captioning-PyTorch | Image Chinese description + visual attention

by foamliu Python Version: v1.0 License: Apache-2.0

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

kandi X-RAY | Image-Captioning-PyTorch Summary

Image-Captioning-PyTorch is a Python library. Image-Captioning-PyTorch has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Image Chinese description + visual attention

Support

Quality

Security

License

Reuse

Support

Image-Captioning-PyTorch has a low active ecosystem.

It has 149 star(s) with 51 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

There are 3 open issues and 28 have been closed. On average issues are closed in 129 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Image-Captioning-PyTorch is v1.0

Quality

Image-Captioning-PyTorch has no bugs reported.

Security

Image-Captioning-PyTorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Image-Captioning-PyTorch is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Image-Captioning-PyTorch releases are available to install and integrate.

Build file is available. You can build the component from source.

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

Top functions reviewed by kandi - BETA

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

Validate the validation
Compute accuracy
Update the statistics
Train the model
Clip gradients of optimizer
Evaluate multiple images
A binary image search algorithm
Visualize the attention matrix
Create input files
Save a checkpoint
Verify that the model is fine tuning
Decrement learning rate
Extract data from a folder
Ensure folder exists

Get all kandi verified functions for this library.

Image-Captioning-PyTorch Key Features

No Key Features are available at this moment for Image-Captioning-PyTorch.

Image-Captioning-PyTorch Examples and Code Snippets

No Code Snippets are available at this moment for Image-Captioning-PyTorch.

Community Discussions

No Community Discussions are available at this moment for Image-Captioning-PyTorch.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install Image-Captioning-PyTorch

You can download it from GitHub.
You can use Image-Captioning-PyTorch 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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