Automated image acquisition and quantification of leaf lesion from plant fungal pathogen

This workflow integrates a Bash script to monitor automated image acquisition, a series of Jupyter Notebooks for dataset preparation, a training script for model development, a prediction script using the trained model, and post-processing tools for downstream analysis. The pipeline was designed to phenotype plant disease symptoms through the quantification of necrosis caused by Sclerotinia sclerotiorum on Brassica napus (oilseed rape) leaves using deep learning methods.