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volleyball-balltracking

"Ball tracking in a Volleyball environment" project for the course "Signal, Image & Video" - MSc in Artificial Intelligence Systems - University of Trento

https://github.com/lorenzialessandro/volleyball-balltracking

Science Score: 44.0%

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    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
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    .zenodo.json file
    Found .zenodo.json file
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    DOI references
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    Academic publication links
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    Scientific vocabulary similarity
    Low similarity (10.0%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

"Ball tracking in a Volleyball environment" project for the course "Signal, Image & Video" - MSc in Artificial Intelligence Systems - University of Trento

Basic Info
  • Host: GitHub
  • Owner: lorenzialessandro
  • Language: Jupyter Notebook
  • Default Branch: main
  • Size: 18 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed about 2 years ago
Metadata Files
Readme Citation

README.md

Ball tracking in a Volleyball environment 🏐

Introduction

This repository contains the code, the final report and the presentation for project of the course "Signal, Image & Video" - MSc in Artificial Intelligence Systems - University of Trento.

The aim of the project is to achieve the ball tracking in a volleyball scenario without the use of state of the art deep learning architectures.

The project is developed by @lorenzialessandro and @LuCazzola.

example image


Folder structure

The structure of the main files is as follows: . ├── notebook.ipynb # Main notebook code ├── docs │ ├── presentation.pdf │ └── report.pdf ├── models # PCA, Random Forest and YOLO (see later) │ └── ... └── ...

Installation and usage

Clone the folder through git or download (and extract) the .zip file. Then follow these steps:

  1. Install the requirements pip install -r requirements.txt
  2. Start the notebook server jupyter notebook
  3. Open the notebook project file jupyter notebook notebook.ipynb
  4. Follow the file steps in order to run the notebook python code

If you want to execute the notebook from your terminal use the execute subcommand: jupyter execute notebook.ipynb

In addition to the code, in the folder there is the presentation of the project and the summary report.


YOLOv5 comparison

A Yolov5 object detector has been trained on the same task and dataset. To see it's perfermances :

  1. Download locally Yolov5 repo and requrements git clone https://github.com/ultralytics/yolov5 # clone cd yolov5 pip install -r requirements.txt # install
  2. Run detection python3 detect.py --weights ../models/YOLOv5_weights.pt --view-img --conf-thres 0.5 --source ../videos/vid3-cut.mp4

Owner

  • Name: Alessandro
  • Login: lorenzialessandro
  • Kind: user
  • Location: Italy

IT Developer and Graphic designer. Computer science student at the University of Trento (Italy)

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Luca"
  given-names: "Cazzola"
- family-names: "Alessandro"
  given-names: "Lorenzi"
title: "volleyball-BallTracking"
version: 0.1
date-released: 2023-12-15
url: "https://github.com/lorenzialessandro/volleyball-BallTracking"

GitHub Events

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Dependencies

requirements.txt pypi
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  • Brotli ==1.0.9
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  • command-not-found ==0.3
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  • distro ==1.7.0
  • distro-info ===1.1build1
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