Detectron2 specialists for your dedicated team.

Where Detectron2 fits in a long-term product team.

Detectron2 is where to go when a bounding box is not enough. Instance segmentation produces a pixel-level mask for each object, which is what medical imaging, precise measurement and any application computing area or shape needs.

It trades speed for accuracy. The two-stage architectures it implements are more accurate on difficult and overlapping objects than single-stage detectors, and slower, which suits batch analysis and doesn't suit live video.

What your dedicated team does with Detectron2.

Segmentation annotation is substantially more expensive than bounding boxes. Pixel-level masks take an order of magnitude longer per image, and that cost belongs in the plan from the start.

Estimating that accurately at scoping is part of how work is planned, as set out in how the monthly fee is built.

Common Detectron2 use cases.

• Pixel-level masks where boxes are insufficient Area and shape measured, which a bounding box cannot express.
• Accuracy on overlapping objects Two-stage detection where objects occlude each other and single-stage struggles.
• Annotation cost planned realistically Mask labelling scoped at its real cost.

Adding Detectron2 skills to your team.

Segmentation work is assigned inside AI capacity, with annotation effort estimated realistically before the project is committed.

At Azendo, Detectron2 work sits with a dedicated AI engineering team. Every Detectron2 specialist we assign works remotely inside your tools as a dedicated member of your team, with the management on our side. It is how companies hire remote developers without opening an offshore office of their own.