An image made up of integer components.ClassIds.
Each pixel corresponds to a components.ClassId that will be mapped to a color based on archetypes.AnnotationContext.
In the case of floating point images, the label will be looked up based on rounding to the nearest integer value.
Use archetypes.AnnotationContext to associate each class with a color and a label.
Fields
Required
buffer:ImageBufferformat:ImageFormat
Optional
Can be shown in
- Spatial2DView
- Spatial3DView (if logged under a projection)
- DataframeView
API reference links
- 🌊 C++ API docs for
SegmentationImage - 🐍 Python API docs for
SegmentationImage - 🦀 Rust API docs for
SegmentationImage
Example
Simple segmentation image
"""Create and log a segmentation image."""
import numpy as np
import rerun as rr
# Create a segmentation image
image = np.zeros((8, 12), dtype=np.uint8)
image[0:4, 0:6] = 1
image[4:8, 6:12] = 2
rr.init("rerun_example_segmentation_image", spawn=True)
# Assign a label and color to each class
rr.log("/", rr.AnnotationContext([(1, "red", (255, 0, 0)), (2, "green", (0, 255, 0))]), static=True)
rr.log("image", rr.SegmentationImage(image))
