/stereo-depth-estimation

A minimal code example for stereo depth estimation

Primary LanguagePython

Stereo Depth Estimation

Introduction

This repository contains a minimal code example to estimate disparity using rectified stereo images from the Middlebury Cones dataset. A local, fixed-support stereo correspondence algorithm is used. Specifically, a window-based method using the sum-of-absolute-differences (SAD) similarity measure is implemented.

Left Stereo Image Right Stereo Image
Left Stereo Image Right Stereo Image
Groundtruth Disparity Image Estimated Disparity Image
Ground Truth Disparity Estimated Disparity

Installation

  1. Create a conda environment and activate it.
conda create -n stereo python=3.9
conda activate stereo
  1. Clone the repository
git clone https://github.com/ed-winning/stereo_depth_estimation.git
  1. Install the dependencies
pip install -r requirements.txt

Running the Code

The following code will generate and visualize the estimated disparity image shown above:

python main.py