The Project Leaf Recognition initiative focuses on developing an image-processing tool to detect and measure water hyacinth leaf damage caused by biocontrol agents. The system uses Python and OpenCV to analyse high-resolution photos to identify scars, lesions, and structural damage. This automated approach enhances research efficiency by standardising assessments of biocontrol effectiveness.

The project includes a user-friendly interface for researchers to submit and review data, ensuring scalable and reproducible monitoring. By integrating machine learning techniques, the tool improves precision in evaluating damage, supporting ongoing environmental management efforts.