Within few minutes, anyone can define classes and build image interpretation solutions using logical and simple-to-use interface.
No need for programming or specialized machine learning expertise.

perClass Mira is built for commodity hardware. No need to purchase a powerful workstation to use it. Our intention is that any biologist or plant specialist can use it on her existing machine.

perClass Mira provides feedback suggesting the user places where additional labeling actually helps to improve the model. Stop wasting time with blind labeling that only increases training time and confuses the model.

Benefit from computational power present in your GPU. Speed up processing of large spectral cubes, and improve your insight by validating your solution on many large cubes.

Solutions may be exported for execution using perClass Runtime. It is very easy to embed automatic classification into custom application. New images can be processed by models exported from perClass Mira. You can also execute classifiers directly on a live spectral video feed.
The screenshot shows integration of perClass Runtime into Cubert Utilities