Metadata-Version: 2.1
Name: lightnet
Version: 1.1.0
Summary: Building blocks for recreating darknet networks in pytorch
Home-page: UNKNOWN
Author: EAVISE
License: UNKNOWN
Description: <img src="https://gitlab.com/EAVISE/lightnet/raw/master/docs/.static/lightnet-long.png" alt="Logo" width="100%">  
        
        Building blocks to recreate Darknet networks in Pytorch  
        [![Version][version-badge]][release-url]
        [![Documentation][doc-badge]][documentation-url]
        [![PyTorch][pytorch-badge]][pytorch-url]
        [![Pipeline][pipeline-badge]][pipeline-url]
        
        
        
        ## Why another framework
        [pytorch-yolo2](https://github.com/marvis/pytorch-yolo2) is working perfectly fine, but does not easily allow a user to modify an existing network.
        This is why I decided to create a library, that gives the user all the necessary building blocks, to recreate any darknet network.  
        This library has everything you need to control your network, weight loading & saving, datasets, dataloaders and data augmentation.
        
        ## Installing
        First install [PyTorch and Torchvision](http://pytorch.org/).  
        Then clone this repository and run one of the following commands:
        ```bash
        # If you just want to use Lightnet
        pip install brambox   # Optional (needed for training)
        pip install .
        
        # If you want to develop Lightnet
        pip install -r develop.txt
        ```
        > This project is python 3.6 and higher so on some systems you might want to use 'pip3.6' instead of 'pip'
        
        ## How to use
        [Click Here](https://eavise.gitlab.io/lightnet) for the API documentation and guides on how to use this library.  
        The _examples_ folder contains code snippets to train and test networks with lightnet. For examples on how to implement your own networks, you can take a look at the files in _lightnet/models_.
        >If you are using a different version than the latest,
        >you can generate the documentation yourself by running `make clean html` in the _docs_ folder.
        >This does require some dependencies, like Sphinx.
        >The easiest way to install them is by using the __-r develop.txt__ option when installing lightnet.
        
        ## Cite
        If you use Lightnet in your research, please cite it.
        ```
        @misc{lightnet18,
          author = {Tanguy Ophoff},
          title = {Lightnet: Building Blocks to Recreate Darknet Networks in Pytorch},
          howpublished = {\url{https://gitlab.com/EAVISE/lightnet}},
          year = {2018}
        }
        ```
        
        ## Main Contributors
        Here is a list of people that made noteworthy contributions and helped to get this project where it stands today!
          - [Tanguy Ophoff](https://gitlab.com/0phoff)
          - [Jon Crall](https://gitlab.com/Erotemic)
        
        
        [version-badge]: https://img.shields.io/pypi/v/lightnet-torch.svg?label=version
        [doc-badge]: https://img.shields.io/badge/-Documentation-9B59B6.svg
        [pytorch-badge]: https://img.shields.io/badge/PyTorch-1.4.0-F05732.svg
        [pipeline-badge]: https://gitlab.com/EAVISE/lightnet/badges/master/pipeline.svg
        [release-url]: https://gitlab.com/EAVISE/lightnet/tags
        [documentation-url]: https://eavise.gitlab.io/lightnet
        [pytorch-url]: https://pytorch.org
        [pipeline-url]: https://pypi.org/project/lightnet-torch
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
