pretrained-models.pytorch | Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, | Computer Vision library

by Cadene Python Version: Current License: BSD-3-Clause

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | pretrained-models.pytorch Summary

pretrained-models.pytorch is a Python library typically used in Artificial Intelligence, Computer Vision, Deep Learning, Pytorch applications. pretrained-models.pytorch has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can download it from GitHub.

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

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pretrained-models.pytorch has a medium active ecosystem.

It has 8768 star(s) with 1843 fork(s). There are 222 watchers for this library.

It had no major release in the last 6 months.

There are 82 open issues and 94 have been closed. On average issues are closed in 83 days. There are 14 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of pretrained-models.pytorch is current.

Quality

pretrained-models.pytorch has 0 bugs and 65 code smells.

Security

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

pretrained-models.pytorch code analysis shows 0 unresolved vulnerabilities.

There are 44 security hotspots that need review.

License

pretrained-models.pytorch is licensed under the BSD-3-Clause License. This license is Permissive.

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

Reuse

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

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

Installation instructions, examples and code snippets are available.

pretrained-models.pytorch saves you 3397 person hours of effort in developing the same functionality from scratch.

It has 7284 lines of code, 386 functions and 35 files.

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

Top functions reviewed by kandi - BETA

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

Downloads VOC 2007
Download url to destination
Update the sum
Constructs an inception model
Update the state_dict in the given dictionary
Load pretrained pretrained model
Forward the concatenation
Combine cell forward
Train model
Computes accuracy
Constructs a Densenet 161
Load a wide resnet
Constructs a Densenet121 model
Constructs a Densenet 19
Construct a ResNet - 18 model
Creates a frozen model
Alexnet model
Creates a model with squeezenet1
Create a BNInception model
Compute average precision
Validate the input tensor
Constructs an inception resnetv2 model
Loads the set of image classes
Create an inception model
Read object labels
Forward the convolution layer

Get all kandi verified functions for this library.

pretrained-models.pytorch Key Features

No Key Features are available at this moment for pretrained-models.pytorch.

pretrained-models.pytorch Examples and Code Snippets

EPIC-KITCHENS-55 action recognition models,Acknowledgements

Python

Lines of Code : 23

License : Non-SPDX (NOASSERTION)

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@InProceedings{wang2016_TemporalSegmentNetworks,
    title={Temporal Segment Networks: Towards Good Practices for Deep Action Recognition},
    author={Limin Wang and Yuanjun Xiong and Zhe Wang and Yu Qiao and Dahua Lin and
            Xiaoou Tang an

Visual classification on cassava disease dataset of Kaggle

Python

Lines of Code : 18

License : No License

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${ROOT}
├── cassava
| ├── train
| | ├── cbb
| | ├── cbsd
| | ├── cgm
| | ├── cmd
| | ├── healthy
| ├── test
| | ├── 0
| ├── extraimages
| | ├── 0
├── dataloaders
├── networks
├── utils
├── config.py
├── main.py
└── README.md

Training,Training VOC

Python

Lines of Code : 1

License : Strong Copyleft (GPL-3.0)

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python tools/train.py

Community Discussions

Trending Discussions on pretrained-models.pytorch

How to use PNASNet5 as encoder in Unet in pytorch

QUESTION

How to use PNASNet5 as encoder in Unet in pytorch

Asked 2018-Sep-11 at 19:05

I want use PNASNet5Large as encoder for my Unet here is my wrong aproach for the PNASNet5Large but working for resnet:

...

ANSWER

Answered 2018-Sep-11 at 18:46

So you want to use PNASNetLarge instead o ResNets as encoder in your UNet architecture. Let's see how ResNets are used. In your __init__:

Source https://stackoverflow.com/questions/52235520

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

Vulnerabilities

No vulnerabilities reported

Install pretrained-models.pytorch

python3 with anaconda
pytorch with/out CUDA
pip install pretrainedmodels
git clone https://github.com/Cadene/pretrained-models.pytorch.git
cd pretrained-models.pytorch
python setup.py install

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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