pytorch-image-models | PyTorch image models , scripts , pretrained weights -- ResNet | Machine Learning library

 by   rwightman Python Version: v0.8.10dev0 License: Apache-2.0

kandi X-RAY | pytorch-image-models Summary

kandi X-RAY | pytorch-image-models Summary

pytorch-image-models is a Python library typically used in Telecommunications, Media, Media, Entertainment, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. pytorch-image-models has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install pytorch-image-models' or download it from GitHub, PyPI.

PyTorch Image Models (timm) is a collection of image models, layers, utilities, optimizers, schedulers, data-loaders / augmentations, and reference training / validation scripts that aim to pull together a wide variety of SOTA models with ability to reproduce ImageNet training results. The work of many others is present here. I've tried to make sure all source material is acknowledged via links to github, arxiv papers, etc in the README, documentation, and code docstrings. Please let me know if I missed anything.
Support
    Quality
      Security
        License
          Reuse

            kandi-support Support

              pytorch-image-models has a medium active ecosystem.
              It has 23581 star(s) with 3908 fork(s). There are 299 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 64 open issues and 597 have been closed. On average issues are closed in 86 days. There are 26 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of pytorch-image-models is v0.8.10dev0

            kandi-Quality Quality

              pytorch-image-models has 0 bugs and 0 code smells.

            kandi-Security Security

              pytorch-image-models has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              pytorch-image-models code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              pytorch-image-models 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.

            kandi-Reuse Reuse

              pytorch-image-models releases are available to install and integrate.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              It has 30607 lines of code, 2468 functions and 193 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed pytorch-image-models and discovered the below as its top functions. This is intended to give you an instant insight into pytorch-image-models implemented functionality, and help decide if they suit your requirements.
            • Create an Optimizer V2 .
            • Create selecs .
            • Initialize the network .
            • Decode a block string .
            • Create a loader .
            • Train one epoch .
            • Extract tar files from a directory .
            • Create a scheduler .
            • Generate mobilenet V3 .
            • Create a dataset .
            Get all kandi verified functions for this library.

            pytorch-image-models Key Features

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

            pytorch-image-models Examples and Code Snippets

            # Ensemble Adversarial Inception ResNet v2-Citation
            Pythondot img1Lines of Code : 35dot img1License : Permissive (Apache-2.0)
            copy iconCopy
            @article{DBLP:journals/corr/abs-1804-00097,
              author    = {Alexey Kurakin and
                           Ian J. Goodfellow and
                           Samy Bengio and
                           Yinpeng Dong and
                           Fangzhou Liao and
                           Ming Liang and
                       
            Adversarial Inception v3-Citation
            Pythondot img2Lines of Code : 35dot img2License : Permissive (Apache-2.0)
            copy iconCopy
            @article{DBLP:journals/corr/abs-1804-00097,
              author    = {Alexey Kurakin and
                           Ian J. Goodfellow and
                           Samy Bengio and
                           Yinpeng Dong and
                           Fangzhou Liao and
                           Ming Liang and
                       
            How do I use this model on an image?
            Pythondot img3Lines of Code : 33dot img3License : Permissive (Apache-2.0)
            copy iconCopy
            import timm
            model = timm.create_model('{{ model_name }}', pretrained=True)
            model.eval()
            
            import urllib
            from PIL import Image
            from timm.data import resolve_data_config
            from timm.data.transforms_factory import create_transform
            
            config = resolve_data_co  
            pytorch-image-models - generate readmes
            Pythondot img4Lines of Code : 43dot img4License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            """
            Run this script to generate the model-index files in `models` from the templates in `.templates/models`.
            """
            
            import argparse
            from pathlib import Path
            
            from jinja2 import Environment, FileSystemLoader
            
            import modelindex
            
            
            def generate_readmes(tem  
            pytorch-image-models - tables
            JavaScriptdot img5Lines of Code : 6dot img5License : Non-SPDX (Apache License 2.0)
            copy iconCopy
            app.location$.subscribe(function() {
              var tables = document.querySelectorAll("article table")
              tables.forEach(function(table) {
                new Tablesort(table)
              })
            })  

            Community Discussions

            QUESTION

            Why is the timm visual transformer position embedding initializing to zeros?
            Asked 2021-Mar-12 at 07:28

            I'm looking at the timm implementation of visual transformers and for the positional embedding, he is initializing his position embedding with zeros as follows:

            ...

            ANSWER

            Answered 2021-Mar-11 at 21:30

            The positional embedding is a parameter that gets included in the computational graph and gets updated during training. So, it doesn't matter if you initialize with zeros; they are learned during training.

            Source https://stackoverflow.com/questions/66054042

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

            Vulnerabilities

            No vulnerabilities reported

            Install pytorch-image-models

            My current documentation for timm covers the basics. timmdocs is quickly becoming a much more comprehensive set of documentation for timm. A big thanks to Aman Arora for his efforts creating timmdocs. paperswithcode is a good resource for browsing the models within timm.

            Support

            My current documentation for timm covers the basics. timmdocs is quickly becoming a much more comprehensive set of documentation for timm. A big thanks to Aman Arora for his efforts creating timmdocs. paperswithcode is a good resource for browsing the models within timm.
            Find more information at:

            Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items

            Find more libraries
            CLONE
          • HTTPS

            https://github.com/rwightman/pytorch-image-models.git

          • CLI

            gh repo clone rwightman/pytorch-image-models

          • sshUrl

            git@github.com:rwightman/pytorch-image-models.git

          • Stay Updated

            Subscribe to our newsletter for trending solutions and developer bootcamps

            Agree to Sign up and Terms & Conditions

            Share this Page

            share link