Challenge
One Point Needed Precise Biological Judgment
Keypoint annotation may look simple because the final output is only a coordinate. In agricultural imagery, however, deciding where that coordinate belongs requires careful visual judgment. Weeds change shape across growth stages, leaves overlap, and field conditions such as soil texture, shadows, blur, motion, and camera angle can affect visibility.
For the client's model, each eligible weed needed to be marked at its defined growth center. This meant the annotation team had to interpret plant structure consistently across crowded carrot-field images, while avoiding missed weeds, duplicate points, and small placement errors that could introduce label noise into the training dataset.
The work required more than speed. It needed a shared understanding of the biological target, clear handling of edge cases, disciplined guideline application, and a dependable review process for uncertain images. Without this consistency, the model would have weaker spatial supervision for learning where the laser should act.
