Background Color Visualization¶
Class: BackgroundColorVisualizationBlockV1
The BackgroundColorVisualization block draws all areas
outside of detected regions in an image with a specified
color.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/background_color_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 |
str |
Color of the background.. | ✅ |
opacity |
float |
Transparency of the Mask 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 Background Color Visualization in version v1.
- inputs:
VLM as Detector,Byte Tracker,Google Vision OCR,Overlap Filter,SAM 3,Classification Label Visualization,Detections Stabilizer,Circle Visualization,SIFT Comparison,Image Contours,Relative Static Crop,Detections Filter,Image Preprocessing,LMM For Classification,VLM as Classifier,Ellipse Visualization,Stitch Images,Triangle Visualization,Stability AI Inpainting,Detections Combine,QR Code Generator,Image Slicer,VLM as Classifier,Background Color Visualization,Model Monitoring Inference Aggregator,Segment Anything 2 Model,Template Matching,Moondream2,Velocity,OCR Model,Dot Visualization,Florence-2 Model,SIFT,Morphological Transformation,Detections Transformation,EasyOCR,Reference Path Visualization,Halo Visualization,SIFT Comparison,Gaze Detection,Polygon Visualization,Image Slicer,Florence-2 Model,Detection Offset,Slack Notification,Clip Comparison,Image Convert Grayscale,Instance Segmentation Model,OpenAI,Byte Tracker,Color Visualization,PTZ Tracking (ONVIF).md),Line Counter,Object Detection Model,Keypoint Detection Model,Google Gemini,JSON Parser,Label Visualization,Email Notification,Llama 3.2 Vision,Trace Visualization,Byte Tracker,Dynamic Zone,YOLO-World Model,Email Notification,Corner Visualization,Mask Visualization,Time in Zone,CogVLM,Roboflow Custom Metadata,Stability AI Outpainting,OpenAI,Detections Stitch,Stitch OCR Detections,Blur Visualization,Time in Zone,CSV Formatter,Crop Visualization,VLM as Detector,OpenAI,Grid Visualization,Detections Classes Replacement,Perspective Correction,Twilio SMS Notification,Absolute Static Crop,Single-Label Classification Model,Seg Preview,Contrast Equalization,Roboflow Dataset Upload,Roboflow Dataset Upload,Polygon Zone Visualization,Stability AI Image Generation,Webhook Sink,Depth Estimation,Bounding Box Visualization,Camera Focus,Line Counter Visualization,Instance Segmentation Model,Multi-Label Classification Model,Icon Visualization,Image Blur,Time in Zone,Pixelate Visualization,Image Threshold,Detections Merge,Path Deviation,Keypoint Detection Model,Anthropic Claude,LMM,Google Gemini,Identify Outliers,Dynamic Crop,Bounding Rectangle,Path Deviation,Detections Consensus,Model Comparison Visualization,Camera Calibration,Local File Sink,Keypoint Visualization,Identify Changes,Object Detection Model - outputs:
VLM as Detector,Google Vision OCR,SAM 3,Classification Label Visualization,Detections Stabilizer,Circle Visualization,Image Contours,Relative Static Crop,Image Preprocessing,LMM For Classification,VLM as Classifier,Ellipse Visualization,Stitch Images,Triangle Visualization,Stability AI Inpainting,Image Slicer,VLM as Classifier,Background Color Visualization,Segment Anything 2 Model,Template Matching,Moondream2,OCR Model,Dot Visualization,Florence-2 Model,SIFT,Morphological Transformation,EasyOCR,Gaze Detection,Halo Visualization,Reference Path Visualization,SIFT Comparison,Buffer,Polygon Visualization,Image Slicer,Florence-2 Model,Clip Comparison,Perception Encoder Embedding Model,Instance Segmentation Model,OpenAI,Byte Tracker,Color Visualization,Image Convert Grayscale,Object Detection Model,Keypoint Detection Model,Google Gemini,Label Visualization,Email Notification,Llama 3.2 Vision,Trace Visualization,QR Code Detection,YOLO-World Model,Corner Visualization,Mask Visualization,Time in Zone,CogVLM,Stability AI Outpainting,OpenAI,Detections Stitch,Barcode Detection,Blur Visualization,Dominant Color,Crop Visualization,VLM as Detector,Single-Label Classification Model,OpenAI,Perspective Correction,Clip Comparison,Single-Label Classification Model,Absolute Static Crop,Seg Preview,Contrast Equalization,Roboflow Dataset Upload,Roboflow Dataset Upload,Polygon Zone Visualization,CLIP Embedding Model,Stability AI Image Generation,Depth Estimation,Bounding Box Visualization,Camera Focus,Line Counter Visualization,Instance Segmentation Model,Multi-Label Classification Model,Icon Visualization,Image Blur,Pixelate Visualization,Image Threshold,Keypoint Detection Model,Anthropic Claude,LMM,Google Gemini,Multi-Label Classification Model,Pixel Color Count,SmolVLM2,Dynamic Crop,Qwen2.5-VL,Model Comparison Visualization,Camera Calibration,Keypoint Visualization,Object Detection Model
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Background Color 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(Union[object_detection_prediction,keypoint_detection_prediction,instance_segmentation_prediction]): Model predictions to visualize..color(string): Color of the background..opacity(float_zero_to_one): Transparency of the Mask overlay..
-
output
image(image): Image in workflows.
Example JSON definition of step Background Color Visualization in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/background_color_visualization@v1",
"image": "$inputs.image",
"copy_image": true,
"predictions": "$steps.object_detection_model.predictions",
"color": "WHITE",
"opacity": 0.5
}