Models#
Empanada currently implements two panoptic segmentation models: Panoptic DeepLab and Panoptic BiFPN. Optionally, both of these models have support for the PointRend module. Currently, all models that will be deployed to empanada-napari require the PointRend module.
These models accept a grayscale EM image and output a semantic segmentation, up-down and right-left offsets, and a heatmap with peaks at object centers. After postprocessing, a panoptic (or in the case below, instance) segmentation is created.
EM image (left) passes through the model and outputs, in order, a semantic segmentation, up-down and left-right offsets, centers heatmap. The panoptic (or instance) segmentation is created via postprocessing.#
To create a model with a standard ResNet50 backbone:
import empanada.models as em
model = em.PanopticDeepLabPR(encoder='resnet50')