Model Comparison Visualization

Class: ModelComparisonVisualizationBlockV1

Source: inference.core.workflows.core_steps.visualizations.model_comparison.v1.ModelComparisonVisualizationBlockV1

The ModelComparisonVisualization block draws all areas predicted by neither model with a specified color, lets overlapping areas of the predictions shine through, and colors areas predicted by only one model with a distinct color.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
copy_image	bool	Enable this option to create a copy of the input image for visualization, preserving the original. Use this when stacking multiple visualizations..	✅
color_a	str	Color of the areas Model A predicted that Model B did not...	✅
color_b	str	Color of the areas Model B predicted that Model A did not..	✅
background_color	str	Color of the areas neither model predicted..	✅
opacity	float	Transparency of the overlay..	✅

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

Available Connections

Compatible Blocks

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

• inputs: LMM, Depth Estimation, Classification Label Visualization, Camera Calibration, Stitch OCR Detections, LMM For Classification, Clip Comparison, CSV Formatter, Instance Segmentation Model, Stitch Images, CogVLM, Byte Tracker, Image Slicer, Roboflow Dataset Upload, Absolute Static Crop, Twilio SMS Notification, Object Detection Model, SIFT Comparison, Florence-2 Model, Byte Tracker, OpenAI, Label Visualization, Path Deviation, Single-Label Classification Model, Roboflow Dataset Upload, Detections Stitch, Bounding Box Visualization, Llama 3.2 Vision, Model Comparison Visualization, Slack Notification, Object Detection Model, VLM as Classifier, Moondream2, Bounding Rectangle, Detections Consensus, Grid Visualization, Detections Merge, Dynamic Zone, Image Convert Grayscale, Halo Visualization, Detection Offset, Overlap Filter, Triangle Visualization, Model Monitoring Inference Aggregator, Time in Zone, Keypoint Detection Model, Reference Path Visualization, Perspective Correction, Dynamic Crop, Detections Transformation, Camera Focus, Identify Changes, VLM as Detector, Detections Classes Replacement, Time in Zone, Florence-2 Model, Local File Sink, Path Deviation, VLM as Detector, Google Vision OCR, OpenAI, Stability AI Image Generation, Ellipse Visualization, SIFT, Blur Visualization, Circle Visualization, Dot Visualization, Image Blur, Background Color Visualization, Gaze Detection, Multi-Label Classification Model, Color Visualization, Byte Tracker, Detections Filter, Pixelate Visualization, Identify Outliers, Google Gemini, Stability AI Inpainting, Keypoint Detection Model, VLM as Classifier, Polygon Zone Visualization, Relative Static Crop, Detections Stabilizer, OCR Model, Keypoint Visualization, Template Matching, Mask Visualization, Velocity, Image Preprocessing, Line Counter Visualization, Roboflow Custom Metadata, Anthropic Claude, Webhook Sink, SIFT Comparison, YOLO-World Model, Trace Visualization, JSON Parser, Instance Segmentation Model, Corner Visualization, Polygon Visualization, Segment Anything 2 Model, Crop Visualization, Email Notification, Image Contours, Image Slicer, Line Counter, Image Threshold
• outputs: LMM, Depth Estimation, Classification Label Visualization, Camera Calibration, LMM For Classification, Clip Comparison, Instance Segmentation Model, Stitch Images, CogVLM, Image Slicer, Roboflow Dataset Upload, Absolute Static Crop, Multi-Label Classification Model, Object Detection Model, Florence-2 Model, QR Code Detection, OpenAI, Label Visualization, Single-Label Classification Model, Qwen2.5-VL, Roboflow Dataset Upload, Detections Stitch, Bounding Box Visualization, Llama 3.2 Vision, Model Comparison Visualization, Pixel Color Count, Object Detection Model, VLM as Classifier, Moondream2, Image Convert Grayscale, Halo Visualization, Buffer, Triangle Visualization, Time in Zone, Keypoint Detection Model, Reference Path Visualization, Perspective Correction, Dynamic Crop, Camera Focus, VLM as Detector, Florence-2 Model, OpenAI, Google Vision OCR, VLM as Detector, Stability AI Image Generation, Ellipse Visualization, SIFT, Blur Visualization, Circle Visualization, Image Blur, Dot Visualization, CLIP Embedding Model, Background Color Visualization, Gaze Detection, Multi-Label Classification Model, Single-Label Classification Model, Byte Tracker, Color Visualization, Pixelate Visualization, Dominant Color, Clip Comparison, Google Gemini, Keypoint Detection Model, Stability AI Inpainting, VLM as Classifier, Polygon Zone Visualization, Relative Static Crop, Detections Stabilizer, OCR Model, Keypoint Visualization, Template Matching, Mask Visualization, SmolVLM2, Image Preprocessing, Line Counter Visualization, Anthropic Claude, SIFT Comparison, YOLO-World Model, Trace Visualization, Instance Segmentation Model, Corner Visualization, Polygon Visualization, Segment Anything 2 Model, Barcode Detection, Crop Visualization, Image Contours, Image Slicer, Image Threshold

Input and Output Bindings

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

Bindings

• input

  • image (image): The image to visualize on..
  • copy_image (boolean): Enable this option to create a copy of the input image for visualization, preserving the original. Use this when stacking multiple visualizations..
  • predictions_a (Union[object_detection_prediction, keypoint_detection_prediction, instance_segmentation_prediction]): Predictions.
  • color_a (string): Color of the areas Model A predicted that Model B did not...
  • predictions_b (Union[object_detection_prediction, keypoint_detection_prediction, instance_segmentation_prediction]): Predictions.
  • color_b (string): Color of the areas Model B predicted that Model A did not..
  • background_color (string): Color of the areas neither model predicted..
  • opacity (float_zero_to_one): Transparency of the overlay..

• output

  • image (image): Image in workflows.

Example JSON definition of step Model Comparison Visualization in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/model_comparison_visualization@v1",
    "image": "$inputs.image",
    "copy_image": true,
    "predictions_a": "$steps.object_detection_model.predictions",
    "color_a": "GREEN",
    "predictions_b": "$steps.object_detection_model.predictions",
    "color_b": "RED",
    "background_color": "BLACK",
    "opacity": 0.7
}