Skip to content

Latest commit

 

History

History
62 lines (36 loc) · 1.8 KB

README.md

File metadata and controls

62 lines (36 loc) · 1.8 KB
Raw

cric-ai logo

A data-driven approach in cricket to achieve highly accurate results using minimal data.

Project Features

  • Pitch-Map

    newplot3

    Objective

    Determine pitch map of deliveries by just using the Umpire POV video feed

    All the visualizations I used in this are mostly images that I provide along with explanations and based visualizations. generate-pitch-map.ipynb is attached to the report.

    This is a demo Desmos simulation for the ball pitching and perspective analysis. Each ball can be roughly assumed to be a skewed sine line in 3D space. To check that live : Click Here

  • Ultra-Edge

    image

    Objective

    Noise Suppression: Use two microphones (one near the bat, one further away) to filter out crowd noise. Frequency Analysis: Using a frequency spectrum tool, identify spikes in bat-ball strike frequency band gaps. Detect spikes in specific frequency ranges that indicate bat-ball strikes.

Prerequisites

  • Python 3.x
  • Required Python packages (listed in requirements.txt)

Setup Instructions

  1. Clone the repository:

    git clone https://github.com/sudo-boo/cric-ai
cd cric-ai

  2. Install dependencies:

    Make sure you have pip installed, then run:

    pip install -r requirements.txt