Dataset from the paper: **"Detecting potholes with monocular computer vision: A performance evaluation of techniques" by Sonja Nienaber** Supervisor: Dr. MJ Booysen Department of Electrical & Electronic Engineering, Stellenbosch University Co-supervisor: Dr. RS Kroon Computer Science Division, Stellenbosch University March 2016 ---------- The entire dataset consists of two different sets, one was considered to be simple and the other more complex. These datasets do share some files and there are a few instances where two different images would have the same name. Therefore, the appropriate measures need to be taken if the data is combined into one larger dataset. Each of the datasets contain folders containing the training (positive and negative) images as well as a set of positive test images. Credit also goes to: - S. Nienaber, M.J. Booysen, R.S. Kroon, “Detecting potholes using simple image processing techniques and real-world footage”, SATC, July 2015, Pretoria, South Africa. - S. Nienaber, R.S. Kroon, M.J. Booysen , “A Comparison of Low-Cost Monocular Vision Techniques for Pothole Distance Estimation”, IEEE CIVTS, December 2015, Cape Town, South Africa.