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Vehicle Speed Estimation

Overview

This project uses the optical flow algorithm, specifically the Lucas-Kanade tracker, to estimate vehicle speeds from mono camera (CCTV) footage.

Prerequisites

  • Python 3.x
  • Required libraries: opencv-python, numpy

Setup

  1. Clone the Repository

    git clone https://github.com/swhan0329/vehicle_speed_estimation.git
cd vehicle_speed_estimation

  2. Install Dependencies

    pip install -r requirements.txt

Usage

  1. With an Input Video

    python main.py [input video name]

    Replace [input video name] with the path to your video file.

  2. Without an Input Video The script will automatically use the webcam on your computer.

    python main.py

File Descriptions

  • main.py: The main script to run the vehicle speed estimation.
  • video.py: Contains functions to handle video input and processing.
  • common.py: Includes common functions and utilities used across the project.
  • tst_scene_render.py: Test and render scenes for visualization.

Example

To run the speed estimation on a sample video:

python main.py sample_video.mp4

To use the webcam for live speed estimation:

python main.py

Additional Notes

  • Ensure that your video has a clear view of the road and vehicles for accurate speed estimation.
  • Adjust parameters in common.py if needed to fit specific requirements or to improve performance.