Image Segmentation

Category: Mega-Polis → Analysis → Analysis Data Tools
Node ID: SvMegapolisImageSegmentation
Tooltip: Performs image segmentation on input images
Dependencies: opencv (cv2), numpy

Functionality

Performs image segmentation on an input image and outputs a segmented result suitable for downstream analysis or geometry workflows.

The node processes an image using OpenCV-based techniques and produces:

  • A segmented image (label map or mask)
  • A processed array representation
  • Optional flattened values for analysis pipelines

This node is typically used for:

  • Extracting regions from street imagery
  • Identifying land cover patterns
  • Converting raster images into data arrays for spatial analysis
  • Pre-processing for object detection or classification workflows

Inputs

Socket Type Description
Image SvStringsSocket Input image (file path or image array depending on upstream node). Must be linked.

Parameters

Name Type Default Description
Method Enum threshold Segmentation method used internally (e.g., thresholding or clustering).
Threshold Float 127 Threshold value used when the selected method requires it.
Invert Bool False Inverts segmentation result (foreground/background swap).

(Exact parameter behaviour depends on the underlying OpenCV implementation.)

Outputs

Socket Type Description
Segmented Image SvStringsSocket Resulting segmented image array.
Flatten Values SvStringsSocket Flattened array of segmentation values for analysis.

Example

Basic segmentation workflow

  1. Load an image using an upstream image-reading node.
  2. Connect the image to Image.
  3. Set:
    • Method → threshold
    • Threshold → 120
  4. Use outputs:
    • Segmented Image to visualise the mask
    • Flatten Values for statistical analysis or clustering

Street imagery analysis

  1. Use Download Street Imagery.
  2. Feed image into Image Segmentation.
  3. Use segmentation mask to:
    • Detect sky/ground ratio
    • Extract vegetation areas
    • Compute coverage statistics

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