Loading page
Semantic segmentation assigns a class to every pixel, which is what scene-understanding models learn from. We produce masks to your class definitions and review boundaries where models are most sensitive.
A short call and a written brief so we agree on the problem, constraints and what done looks like.
A small, real slice of the work to test assumptions before you commit to the full program.
Regular demos or dataset drops, each reviewed against the criteria we agreed.
Documentation, access and training so your team owns the result.
Instance Segmentation
Separate masks for every individual object, even when objects overlap.
Image Annotation
Bounding boxes, polygons, keypoints and classification labels for vision models.
Computer Vision Development
Vision systems for detection, tracking and segmentation, trained on well-labeled data.
Tell us what you want to build or what data you need. We will reply with questions, not a sales script.