M6-Project: Video Surveillance for Road Traffic Monitoring Team 3

Repo containing the assigments for the different weeks of the module

Table of Contents

1. About The Project
   • Built With
2. Getting Started
   • Prerequisites
   • Installation
3. Usage
4. Project
5. Contributing
6. Contact
7. License
8. Acknowledgments

About The Project

M6-Video Analysis project from the Msc: Master in Computer Vision done by the UAB. This repository is maintained mainly by Alberto Barreiro, Manel Guzmán, Jiaqiang Ye Zhu and Advait Dixit.

The main goal is to learn the basic concepts and techniques to Video analysis.

(back to top)

Built With

• Numpy
• OpenCV
• PyTorch

(back to top)

Getting Started

In order to make our project reproductible, we have make use of the python package manager conda.

Prerequisites

This is an example of how to list things you need to use the software and how to install them.

• conda

  conda env create -f environment.yml

Installation

1. Clone the repo

   git clone https://github.com/mcv-m6-video/mcv-m6-2023-team3.git

2. Install Anaconda Manager

   wget https://repo.anaconda.com/archive/Anaconda3-2020.02-Linux-x86_64.sh

    bash Anaconda3-2020.02-Linux-x86_64.sh
   

(back to top)

Usage

python main.py -h
usage: main.py [-h] <-w WEEK> <-t TASK>

M6 - Video Analysis: Video Surveillance for Road Traffic Monitoring

Arguments:
-h, --help            show this help message and exit
-w WEEK, --week WEEK  week to execute. Options are [1,2,3,4,5]
-t TASK, --task TASK  task to execute. Options depend on each week.

(back to top)

Project

• Week 1: Datasets and metrics implementations

• Week 2: Background Estimation

• Week 3: Oject Detection and Tracking

  • Task 1
  • Task 2

• Week 4: Optical Flow: Stabilization and Tracking

  • Task 1
  • Task 2/3

• Week 5: Multi-Target Multi-Camera Tracking You can also visualize the week 5/final presentation in a static PDF

Report

The final report is available here

(back to top)

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

(back to top)

Contact

Albert Barreiro	Manel Guzman	Jiaqiang Ye Zhu	Advait Dixit
albertbarreirod@gmail.com	manelguz7@gmail.com	jiaqiangyz@gmail.com	advaitdixit99@gmail.com

(back to top)

License

Distributed under the MIT License.

(back to top)