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AugeLab Studio Manual
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Image ROI

Image ROI Node Documentation

The Image ROI node in AugeLab Studio allows you to define a region of interest (ROI) by cropping an image based on specified width and height ranges. It enables you to extract a specific portion of an image for further processing or analysis.

Node Overview

The Image ROI node takes an image as input and provides the following outputs:
  1. 1.
    ROI Image: The region of interest (ROI) extracted from the input image.
  2. 2.
    ROI Coordinates: The coordinates of the ROI within the input image.

Node Properties

  • Node Title: Image ROI
  • Node ID: OP_NODE_ROI

Inputs

The Image ROI node has the following input socket:
  1. 1.
    Image: The input image from which the ROI will be extracted.

Outputs

The Image ROI node has the following output sockets:
  1. 1.
    ROI Image: The region of interest (ROI) extracted from the input image. The output is a cropped image representing the specified ROI.
  2. 2.
    ROI Coordinates: The coordinates of the ROI within the input image. The ROI coordinates are provided as a tuple with the format ((x_min, y_min), (x_max, y_max)), where (x_min, y_min) represents the top-left corner of the ROI and (x_max, y_max) represents the bottom-right corner of the ROI.

Usage

  1. 1.
    Drag and drop the Image ROI node from the node library onto the canvas in AugeLab Studio.
  2. 2.
    Connect the input image from which the ROI will be extracted to the Image input socket of the Image ROI node.
  3. 3.
    Adjust the width and height ranges using the sliders to define the desired ROI.
  4. 4.
    Run the pipeline.
  5. 5.
    The Image ROI node will crop the input image based on the specified width and height ranges.
  6. 6.
    The cropped ROI image will be outputted from the ROI Image output socket of the Image ROI node.
  7. 7.
    The coordinates of the ROI within the input image will be outputted from the ROI Coordinates output socket of the Image ROI node.
  8. 8.
    Retrieve the output ROI image and ROI coordinates for further processing or analysis.

Notes

  • The Image ROI node allows you to define a region of interest (ROI) by cropping an image based on specified width and height ranges.
  • The width and height ranges can be adjusted using the sliders provided by the node.
  • The node performs cropping based on the specified width and height ranges and outputs the cropped ROI image and ROI coordinates.
  • The extracted ROI image and ROI coordinates can be used for further processing, analysis, or visualization in subsequent nodes.
That concludes the documentation for the Image ROI node in AugeLab Studio. Use this node to define a region of interest (ROI) by cropping an image based on specified width and height ranges.