shivvrat / readme-template Goto Github PK

A README template to jumpstart your projects!
Explore the docs »

View Demo · Report Bug · Request Feature

• Table of Contents
• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

In this section you should describe your project, including any datasets you used and appropriate citations. You may refer to your project report or cite your paper for more detailed information.

Here goes the title with hyperlink

When using this code, kindly reference:

@ARTICLE{Damen2020RESCALING,
   title={Rescaling Egocentric Vision},
   author={Damen, Dima and Doughty, Hazel and Farinella, Giovanni Maria  and and Furnari, Antonino 
           and Ma, Jian and Kazakos, Evangelos and Moltisanti, Davide and Munro, Jonathan 
           and Perrett, Toby and Price, Will and Wray, Michael},
           journal   = {CoRR},
           volume    = {abs/2006.13256},
           year      = {2020},
           ee        = {http://arxiv.org/abs/2006.13256},
} 

and

@misc{fan2020pyslowfast,
  author =       {Haoqi Fan and Yanghao Li and Bo Xiong and Wan-Yen Lo and
                  Christoph Feichtenhofer},
  title =        {PySlowFast},
  howpublished = {\url{https://github.com/facebookresearch/slowfast}},
  year =         {2020}
}

You can include tables or images to summarize your results when and if appropriate.

In this section you should provide instructions on how to use this repository to recreate your project locally.

Here, list all libraries, packages and other dependencies that need to be installed to run your project. Include library versions and how they should be installed if a special requirement is needed.

For example, this is how you would list them:

• Transformers 4.8.0

  conda install -c conda-forge transformers

• OpenCV 4.5.2

  conda install -c conda-forge opencv

Alternatively, you can export your Python working environment, push it to your project's repository and allow users to clone it locally. This way, anyone can install it and they will have all dependencies needed. Here is how you export a copy of your Python environment:

conda env export > requirements.yml

The user will be able to recreate it using:

conda env create -f requirements.yml

1. Clone the repo

   git clone https://github.com/catiaspsilva/README-template.git

2. Setup (and activate) your environment

conda env create -f requirements.yml

Use this space to show useful examples of how a project can be used. For course projects, include which file to execute and the format of any input variables.

Additional screenshots, code examples and demos work well in this space. You may also link to more resources.

For more examples, please refer to the Documentation

See the open issues for a list of proposed features (and known issues).

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

Distributed under the MIT License. See LICENSE for more information.

Distributed under the MIT License. See LICENSE for more information.

Your Name - @ShivvratA - [email protected]

Project Link: Charades Multi Label Activity Recognition