Tools and outputs

Deep-learning based framework for the automated detection of in-pipe defects in closed-circuit television (CCTV) sewer surveys

The framework developed within Co-UDlabs utilizes the Ultralytics YOLO v8 model for image processing and defect detection. By eliminating the need for manual feature extraction, this approach simplifies the identification of defects that are challenging to extract features from, such as those found in sewer pipes. The methodology, demonstration results, and recommendations for further work are outlined in this report.

The source code (including sample images and written software support) is publicly available in open access on GitHub. It has been developed to a standard to encourage others, especially non-specialists in small companies and utilities, to try and investigate whether a more simplified defect classification scheme can provide the knowledge needed to enhance the management of buried sewer assets.