Model Comparison Visualization¶
Class: 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:
Circle Visualization,Background Color Visualization,Corner Visualization,Twilio SMS Notification,Slack Notification,VLM as Detector,VLM as Classifier,LMM,Polygon Zone Visualization,Camera Focus,Image Slicer,Image Blur,Dot Visualization,Path Deviation,Detections Merge,Detection Offset,Google Gemini,Roboflow Dataset Upload,Stability AI Inpainting,Pixelate Visualization,Line Counter,OpenAI,Detections Consensus,Gaze Detection,Image Convert Grayscale,Absolute Static Crop,Stability AI Image Generation,Webhook Sink,Color Visualization,Image Threshold,Halo Visualization,Polygon Visualization,VLM as Classifier,Detections Classes Replacement,Dynamic Zone,Instance Segmentation Model,CogVLM,Camera Calibration,Email Notification,Object Detection Model,Classification Label Visualization,Single-Label Classification Model,Llama 3.2 Vision,Google Vision OCR,Roboflow Dataset Upload,Byte Tracker,Ellipse Visualization,Bounding Box Visualization,JSON Parser,Object Detection Model,Line Counter Visualization,Image Preprocessing,Keypoint Detection Model,Trace Visualization,Label Visualization,Local File Sink,Image Slicer,Detections Transformation,Anthropic Claude,Crop Visualization,Identify Outliers,Detections Stitch,OCR Model,YOLO-World Model,Relative Static Crop,Model Comparison Visualization,Stitch OCR Detections,Perspective Correction,Byte Tracker,OpenAI,Path Deviation,Mask Visualization,Time in Zone,Detections Filter,Clip Comparison,Time in Zone,Dynamic Crop,Template Matching,CSV Formatter,Byte Tracker,Florence-2 Model,Instance Segmentation Model,Keypoint Detection Model,Image Contours,SIFT,SIFT Comparison,Reference Path Visualization,Florence-2 Model,Triangle Visualization,Model Monitoring Inference Aggregator,Bounding Rectangle,Velocity,SIFT Comparison,VLM as Detector,Keypoint Visualization,Identify Changes,Multi-Label Classification Model,LMM For Classification,Roboflow Custom Metadata,Grid Visualization,Segment Anything 2 Model,Detections Stabilizer,Stitch Images,Blur Visualization - outputs:
Circle Visualization,Background Color Visualization,Corner Visualization,VLM as Detector,VLM as Classifier,LMM,Polygon Zone Visualization,Camera Focus,Image Slicer,Image Blur,Dot Visualization,Google Gemini,Roboflow Dataset Upload,Single-Label Classification Model,Stability AI Inpainting,Pixelate Visualization,OpenAI,Gaze Detection,Dominant Color,Stability AI Image Generation,Image Convert Grayscale,Absolute Static Crop,Color Visualization,Image Threshold,Halo Visualization,Polygon Visualization,VLM as Classifier,CogVLM,Instance Segmentation Model,Camera Calibration,Object Detection Model,Classification Label Visualization,Single-Label Classification Model,Llama 3.2 Vision,Google Vision OCR,Roboflow Dataset Upload,Byte Tracker,Ellipse Visualization,Pixel Color Count,Bounding Box Visualization,Object Detection Model,Line Counter Visualization,Image Preprocessing,Keypoint Detection Model,Trace Visualization,Label Visualization,Clip Comparison,Image Slicer,Anthropic Claude,Crop Visualization,Detections Stitch,OCR Model,YOLO-World Model,Model Comparison Visualization,Relative Static Crop,QR Code Detection,Perspective Correction,OpenAI,Qwen2.5-VL,Mask Visualization,Time in Zone,Clip Comparison,Dynamic Crop,Template Matching,Florence-2 Model,Barcode Detection,Instance Segmentation Model,Keypoint Detection Model,Image Contours,Buffer,SIFT,Multi-Label Classification Model,Florence-2 Model,Reference Path Visualization,CLIP Embedding Model,Triangle Visualization,SIFT Comparison,VLM as Detector,Keypoint Visualization,Multi-Label Classification Model,LMM For Classification,Segment Anything 2 Model,Detections Stabilizer,Stitch Images,Blur Visualization
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[keypoint_detection_prediction,instance_segmentation_prediction,object_detection_prediction]): Predictions.color_a(string): Color of the areas Model A predicted that Model B did not...predictions_b(Union[keypoint_detection_prediction,instance_segmentation_prediction,object_detection_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
}