Sample frames for this project are available under NDA. Write to bilal@wortel.ai and we will share the relevant before and after pairs.
Challenges
- Identifying Sclerotinia-affected areas against complex agricultural backgrounds.
- Disease-affected regions were easily confused with normal plant structures.
- Small or partially visible disease symptoms required close inspection.
- Keeping bounding boxes tight around both sunflower targets and affected areas.
- Lighting conditions, plant sizes and field environments varied throughout the dataset.
Related work
Ground Cover Quadrat Segmentation
2,275 cover-crop plot images annotated in Labelbox: plot corners boxed, then every pixel classed as groundcover, weed, residue, crop or soil.
Almond Tree Detection
Bounding boxes around individual almond trees in top-down drone imagery, where shadows and neighbouring vegetation mimicked real trees.
Apple Detection
Bounding boxes around individual apples on tree branches, where dense leaves and occlusion hid much of each fruit.