PostProcessing.ipynb

The "PostProcessing" Jupyter R notebook processes model predictions to extract biologically relevant data over time. It filters and tracks individual leaves across images using timestamp information, object confidence scores, area thresholds, and spatial position (row and column identification based on centroid coordinates), enabling robust tracking despite overlapping or shifting objects. Lesions are then assigned to their corresponding leaves by matching lesion centers to the bounding boxes of identified leaves, allowing accurate quantification of disease progression.