Detasseling: Male & Female Tassel Detection - Wortel AI annotation portfolio

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

Determining correctly whether a tassel was inside or outside the designated row.
Distinguishing male and female tassels based on their position in the field.
Small or partially visible remaining female tassels were hard to identify.
Handling dense corn plants and overlapping tassels.
Ensuring that remaining female tassels were not missed during annotation.
Consistent annotations had to be maintained across different row layouts and image conditions.

Project overview

The Detasseling project involved annotating tassels in corn fields to identify male and female tassels based on their position relative to the corn rows. The main objective was to identify female tassels that remained after the detasseling process and to quantify the remaining tassels that needed to be removed.

Tassels located within the designated row were considered male tassels, while tassels appearing outside the row were considered female tassels. The annotation focused particularly on the remaining female tassels after detasseling, because these indicate tassels that were not successfully removed and may require further attention.

Dataset

Images: 1,000+
Classes: 2
Annotation: Bounding box detection
Source: Client-provided
Tool: CVAT
Client: Private client

Industry

Agriculture

Annotation type

Bounding Box

Labels

Male Tassel Female Tassel

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.