GSense Documentation
  • Welcome to GSense
  • Getting Started
    • Installation
    • Workflow
    • Features
  • Basics
    • Image loading and managing
      • Load images
      • Viewer
      • Layers
    • Spectral Indexing
    • Image Segmentation
      • Default models
      • Custom models
    • Annotation
    • Binarizer
    • Export
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  1. Basics
  2. Image Segmentation

Default models

Using default model checkpoints with ViT-huge and ViT-base backbones

PreviousImage SegmentationNextCustom models

Last updated 6 months ago

  1. Select Model Type

    • In the Model Settings tab, choose the model type from the dropdown menu. Available options include:

      • vit-h (Vision Transformer - huge)

      • vit-b (Vision Transformer - base)

  2. Select Checkpoint

    • Select the default option in the Checkpoint dropdown.

  3. Initialize the Model

    • Click on the Initialize Model button.

    • A message box will confirm if the model initialization is successful.

    Note: Initializing takes a longer time the first time.


Once the model is initialized, you can now run segmentation:

Prerequisites:

  • Ensure you have generated pseudo-RGB images using the Spectral Indexingtab.

  1. Run Segmentation:

    • Click the Run Segmentation button.

    All generated pseudo-RGB images of all loaded images will be processed. The segmentation may take some time, depending on the number of images and model complexity.

  2. View Results:

    Once segmentation is complete, the segmented masks will appear as additional layers in the viewer.

    • Each pseudo-RGB image will have its mask as a new layer. Select the Pseudo-RGB x-x button of choice to view its mask.

    • You can toggle the visibility of the layers using the Layer List dock (enable from the Layers button).

Video demo link to segment images with default SAM ViT-h and ViT-b models:

Ensure you have (either RGB or hyperspectral).

loaded images