Case Study: Oishii achieves 70% faster strawberry annotation with Labellerr

Oishii speeds strawberry robot annotation by 70% with Labellerr

Oishii, a vertical farming innovator, faced a complex data labeling challenge in training its AI-driven strawberry-harvesting robots. The task required high-accuracy segmentation of berries, calyxes, and stems amidst issues like overlapping fruit and inconsistent lighting. Their internal team lacked the bandwidth to handle the volume of data, so they partnered with Labellerr to implement its AI-assisted annotation platform.

Labellerr provided a tailored solution using bounding boxes, polygon masks, and keypoints, which integrated into Oishii's workflow. This partnership resulted in a 70% faster annotation process and pixel-perfect segmentation. The improved data quality led to better AI model performance, enabling the robots to reliably identify ripe berries and cut stems accurately, thereby reducing damage, waste, and manual labor.

Oishii