pytorch-vgg | Some scripts to convert the VGG-16 and VGG-19 models | Machine Learning library

by jcjohnson Python Version: Current License: MIT

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kandi X-RAY | pytorch-vgg Summary

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

Some scripts to convert the VGG-16 and VGG-19 models [1] from Caffe to PyTorch.

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pytorch-vgg has a low active ecosystem.

It has 215 star(s) with 33 fork(s). There are 7 watchers for this library.

It had no major release in the last 6 months.

There are 8 open issues and 0 have been closed. On average issues are closed in 957 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pytorch-vgg is current.

Quality

pytorch-vgg has 0 bugs and 0 code smells.

Security

pytorch-vgg has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pytorch-vgg code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pytorch-vgg is licensed under the MIT License. This license is Permissive.

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

Reuse

pytorch-vgg releases are not available. You will need to build from source code and install.

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

pytorch-vgg saves you 28 person hours of effort in developing the same functionality from scratch.

It has 77 lines of code, 0 functions and 2 files.

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

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pytorch-vgg Key Features

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pytorch-vgg Examples and Code Snippets

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Community Discussions

Trending Discussions on pytorch-vgg

How to do Class Activation Mapping in pytorch vgg16 model?

QUESTION

How to do Class Activation Mapping in pytorch vgg16 model?

Asked 2020-Jun-21 at 10:01

I wrote a pretrained vgg16 model for image classification and its layers are

...

ANSWER

Answered 2020-Jun-21 at 10:01

This particular model isn't suitable for the simple approach you've pointed out. The CAM you refer to are extracted from models that have only one linear layer at the end, preceeded by a global average pooling layer, like this

Source https://stackoverflow.com/questions/62494963

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

Vulnerabilities

No vulnerabilities reported

Install pytorch-vgg

You can download it from GitHub.
You can use pytorch-vgg 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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