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Keypoint Visualization

Version v1

The KeypointVisualization block uses a detections from an keypoint detection model to draw keypoints on objects using sv.VertexAnnotator.

Type identifier

Use the following identifier in step "type" field: roboflow_core/keypoint_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..
annotator_type str Type of annotator to be used for keypoint visualization..
color str Color of the keypoint..
text_color str Text color of the keypoint..
text_scale float Scale of the text..
text_thickness int Thickness of the text characters..
text_padding int Padding around the text in pixels..
thickness int Thickness of the outline in pixels..
radius int Radius of the keypoint in pixels..

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 Keypoint Visualization in version v1.

The available connections depend on its binding kinds. Check what binding kinds Keypoint 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 (keypoint_detection_prediction): Predictions.
    • color (string): Color of the keypoint..
    • text_color (string): Text color of the keypoint..
    • text_scale (float): Scale of the text..
    • text_thickness (integer): Thickness of the text characters..
    • text_padding (integer): Padding around the text in pixels..
    • thickness (integer): Thickness of the outline in pixels..
    • radius (integer): Radius of the keypoint in pixels..
  • output

    • image (image): Image in workflows.
Example JSON definition of step Keypoint Visualization in version v1
{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/keypoint_visualization@v1",
    "image": "$inputs.image",
    "copy_image": true,
    "predictions": "$steps.keypoint_detection_model.predictions",
    "annotator_type": "<block_does_not_provide_example>",
    "color": "#A351FB",
    "text_color": "black",
    "text_scale": 0.5,
    "text_thickness": 1,
    "text_padding": 10,
    "thickness": 2,
    "radius": 10
}