This repository contains the data, labels, and code for the Tyre Tread Depth Measurement project. The aim of this project is to develop an accurate and efficient method for measuring tyre tread depth using computer vision techniques and machine learning algorithms.
The approach involves depth estimation using MiDaS on a custom dataset, tyre classification using segmentation, HOG feature extraction, and SVM classifier, and the development of a mobile app to facilitate user interaction.
This repository provides a comprehensive collection of resources to ensure the transparency, reproducibility, and ease of collaboration for those interested in the project. Contributions and suggestions for improvements are welcome!
