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Halo Visualization

Version v1

The HaloVisualization block uses a detected polygon from an instance segmentation to draw a halo using sv.HaloAnnotator.

Type identifier

Use the following identifier in step "type" field: roboflow_core/halo_visualization@v1to add the block as as step in your workflow.

Properties

Name Type Description Refs
name str The unique name of this step..
copy_image bool Duplicate the image contents (vs overwriting the image in place). Deselect for chained visualizations that should stack on previous ones where the intermediate state is not needed..
color_palette str Color palette to use for annotations..
palette_size int Number of colors in the color palette. Applies when using a matplotlib color_palette..
custom_colors List[str] List of colors to use for annotations when color_palette is set to "CUSTOM"..
color_axis str Strategy to use for mapping colors to annotations..
opacity float Transparency of the halo overlay..
kernel_size int Size of the average pooling kernel used for creating the halo..

The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.

Available Connections

Check what blocks you can connect to Halo Visualization in version v1.

The available connections depend on its binding kinds. Check what binding kinds Halo Visualization in version v1 has.

Bindings
  • input

    • image (image): The input image for this step..
    • copy_image (boolean): Duplicate the image contents (vs overwriting the image in place). Deselect for chained visualizations that should stack on previous ones where the intermediate state is not needed..
    • predictions (instance_segmentation_prediction): Predictions.
    • color_palette (string): Color palette to use for annotations..
    • palette_size (integer): Number of colors in the color palette. Applies when using a matplotlib color_palette..
    • custom_colors (list_of_values): List of colors to use for annotations when color_palette is set to "CUSTOM"..
    • color_axis (string): Strategy to use for mapping colors to annotations..
    • opacity (float_zero_to_one): Transparency of the halo overlay..
    • kernel_size (integer): Size of the average pooling kernel used for creating the halo..
  • output

    • image (image): Image in workflows.
Example JSON definition of step Halo Visualization in version v1
{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/halo_visualization@v1",
    "image": "$inputs.image",
    "copy_image": true,
    "predictions": "$steps.instance_segmentation_model.predictions",
    "color_palette": "DEFAULT",
    "palette_size": 10,
    "custom_colors": [
        "#FF0000",
        "#00FF00",
        "#0000FF"
    ],
    "color_axis": "CLASS",
    "opacity": 0.8,
    "kernel_size": 40
}