Breeze Documentation Segmentations Segmentations In this space, you will find all the Segmentations in Breeze with what parameters are available and example usage Model — Separate object from background using PCA Model Expression — Segment objects from measurements using expressions and models. Deep Learning image segmentation — Object detection using pre-trained algorithms via ONNX Constrained Spectral Unmixing (segmentation) — Segmentation using unmixing of spectral data Grid and inset — Spatial segmentation in grid format Group (segmentation) — Separate on based on Breeze group Horizontal interval — Spatial segmentation in the field of view width Intensity — Segment objects from measurements using intensities in the different bands/wavelengths Manual selection in pixel explore — Manual exploratory segmentation Pixel class from external file — Classify objects using pixel classification from external files. Pixel coordinates — Lets the user create a specified region in the measurement based on pixel coordinates. Python script (segmentation) — Segmentation of measurement using an external python script. Representative spectrum — Create sub-sample from segmentation Shapefile — Segment the image according to the specified shapefile Structure — Select a band at which the segmentation should be applied. ×