update readme

.github/workflows/ruff.yml

@@ -1,18 +1,19 @@
 name: Ruff
-on: [ push, pull_request ]
+on: [push, pull_request]
 
 jobs:
   ruff:
-    runs-on: ubuntu-latest 
+    runs-on: ubuntu-latest
     steps:
     - uses: actions/checkout@v4
     - uses: actions/setup-python@v4
       with:
         python-version: "3.9"
-    - uses: chartboost/ruff-action@v1
+    - name: Run Ruff with auto-fix
+      uses: chartboost/ruff-action@v1
       with:
-        config: .ruff.toml
-        args: --fix --unsafe-fixes
+        args: --fix  # Automatically apply safe fixes
     - uses: stefanzweifel/git-auto-commit-action@v4
       with:
         commit_message: 'style fixes by ruff'
+        file_pattern: '*.py'  # Ensure only Python files are committed

README.md

@@ -1,27 +1,176 @@
-# Python-Project-Template
 
-Data Source
-1. [ImageNet](https://image-net.org/challenges/LSVRC/2017/index.php): The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) 2017
+<a name="readme-top"></a>
+
+[![Contributors][contributors-shield]][contributors-url]
+[![Forks][forks-shield]][forks-url]
+[![Stargazers][stars-shield]][stars-url]
+[![MIT License][license-shield]][license-url]
+[![LinkedIn][linkedin-shield]][linkedin-url]
+
+<!-- PROJECT LOGO -->
+<br />
+<div align="center">
+  <a href="https://github.com/UTAustin-SwarmLab/temporal-logic-video-dataset">
+    <img src="images/logo.png" alt="Logo" width="240" height="240">
+  </a>
+
+  <h3 align="center">Temporal Logic Video (TLV) Dataset</h3>
+
+  <p align="center">
+    Synthetic and real video dataset with temporal logic annotation
+    <br />
+    <a href="https://github.com/UTAustin-SwarmLab/temporal-logic-video-dataset"><strong>Explore the docs »</strong></a>
+    <br />
+    <br />
+    <a href="https://github.com/UTAustin-SwarmLab/temporal-logic-video-dataset">View Demo</a>
+    ·
+    <a href="https://github.com/UTAustin-SwarmLab/temporal-logic-video-dataset/issues">Report Bug</a>
+    ·
+    <a href="https://github.com/UTAustin-SwarmLab/temporal-logic-video-dataset">Request Feature</a>
+  </p>
+</div>
+
+
+<!-- TABLE OF CONTENTS -->
+<details>
+  <summary>Table of Contents</summary>
+  <ol>
+    <li><a href="#about-the-project">About The Project</a></li>
+    <li>
+      <a href="#getting-started">Getting Started</a>
+      <ul>
+        <li><a href="#prerequisites">Prerequisites</a></li>
+        <li><a href="#installation">Installation</a></li>
+      </ul>
+    </li>
+    <li><a href="#usage">Usage</a></li>
+    <li><a href="#roadmap">Roadmap</a></li>
+    <li><a href="#contributing">Contributing</a></li>
+    <li><a href="#license">License</a></li>
+    <li><a href="#contact">Contact</a></li>
+    <li><a href="#acknowledgments">Acknowledgments</a></li>
+  </ol>
+</details>
+
+<!-- ABOUT THE PROJECT -->
+## About The Project
+
+<!-- [![Product Name Screen Shot][product-screenshot]](https://example.com) -->
+
+Given the lack of SOTA video datasets for long-horizon,
+temporally extended activity and object detection, we intro-
+duce the Temporal Logic Video (TLV) datasets. The syn-
+thetic TLV datasets are compiled by stitching together static
+images from computer vision datasets like COCO and
+ImageNet. This enables the artificial introduction of
+a wide range of TL specifications. Additionally, we have
+created two video datasets based on the open-source au-
+tonomous vehicle (AV) driving datasets NuScenes and
+Waymo.
+
+<p align="right">(<a href="#readme-top">back to top</a>)</p>
 
+<!-- GETTING STARTED -->
+## Getting Started
 
-This is a template repository. Please initialize your python project using this template.
+This is an example of how you may give instructions on setting up your project locally.
+To get a local copy up and running follow these simple example steps.
 
-1. Make sure you have a right python version installed locally and change the version of python from the files below
-   - `.github/workflows/ruff.yml`
-   - `pyproject.toml`
+### Prerequisites
 
-2. `your_project_name` is your project package name including src.
+If you want to generate syntetic dataset from COCO and ImageNet, you should download the source data first. 
 
-3. Development
-   ```
-   python -m venv .venv
-   source .venv/bin/activate
-   python -m pip install --upgrade pip build
-   python -m pip install --editable ."[dev, test]"
-   ```
+1. [ImageNet](https://image-net.org/challenges/LSVRC/2017/index.php): The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) 2017
+
+2. [COCO](google.com): TODO
+
+### Installation
+```
+python -m venv .venv
+source .venv/bin/activate
+python -m pip install --upgrade pip build
+python -m pip install --editable ."[dev, test]"
+```
 
-5. If you want to build a project
-   ```
-   python -m build
-   ```
+<p align="right">(<a href="#readme-top">back to top</a>)</p>
+
+
+<!-- USAGE EXAMPLES -->
+## Usage
+
+TBD
+
+<p align="right">(<a href="#readme-top">back to top</a>)</p>
+
+
+
+<!-- ROADMAP -->
+## Roadmap
+
+- [ ] Publication
+   - [ ] Repository
+   - [ ] Blog
+
+<p align="right">(<a href="#readme-top">back to top</a>)</p>
+
+<!-- CONTRIBUTING 
+## Contributing
+
+Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are **greatly appreciated**.
+
+If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement".
+Don't forget to give the project a star! Thanks again!
+
+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
+
+<p align="right">(<a href="#readme-top">back to top</a>)</p>
+-->
+
+
+<!-- LICENSE -->
+## License
+
+Distributed under the MIT License. See `LICENSE` for more information.
+
+<p align="right">(<a href="#readme-top">back to top</a>)</p>
+
+<!-- CONTACT -->
+## Contact
+
+Minkyu Choi - [@your_twitter](https://twitter.com/MinkyuChoi7) - minkyu.choi@utexas.edu
+
+Project Link: TBD
+
+<p align="right">(<a href="#readme-top">back to top</a>)</p>
+
+
+
+<!-- ACKNOWLEDGMENTS -->
+## Acknowledgments
+
+* University of Texas at Austin (UT Austin)
+* UT Austin Swarm Lab
+
+<p align="right">(<a href="#readme-top">back to top</a>)</p>
+
+
 
+<!-- MARKDOWN LINKS & IMAGES -->
+<!-- https://www.markdownguide.org/basic-syntax/#reference-style-links -->
+[contributors-shield]: https://img.shields.io/github/contributors/othneildrew/Best-README-Template.svg?style=for-the-badge
+[contributors-url]: https://github.com/UTAustin-SwarmLab/temporal-logic-video-dataset/graphs/contributors
+[forks-shield]: https://img.shields.io/github/forks/othneildrew/Best-README-Template.svg?style=for-the-badge
+[forks-url]: https://github.com/UTAustin-SwarmLab/temporal-logic-video-dataset/network/members
+[stars-shield]: https://img.shields.io/github/stars/othneildrew/Best-README-Template.svg?style=for-the-badge
+[stars-url]: https://github.com/UTAustin-SwarmLab/temporal-logic-video-dataset/stargazers
+[issues-shield]: https://img.shields.io/github/issues/othneildrew/Best-README-Template.svg?style=for-the-badge
+[issues-url]: https://github.com/UTAustin-SwarmLab/temporal-logic-video-dataset/issues
+[license-shield]: https://img.shields.io/github/license/othneildrew/Best-README-Template.svg?style=for-the-badge
+[license-url]: https://github.com/UTAustin-SwarmLab/temporal-logic-video-dataset/blob/master/LICENSE.txt
+[linkedin-shield]: https://img.shields.io/badge/-LinkedIn-black.svg?style=for-the-badge&logo=linkedin&colorB=555
+[linkedin-url]: https://www.linkedin.com/in/mchoi07/
+[product-screenshot]: images/screenshot.png