Background Color Visualization

Class: BackgroundColorVisualizationBlockV1

Source: inference.core.workflows.core_steps.visualizations.background_color.v1.BackgroundColorVisualizationBlockV1

Apply a colored overlay to areas outside detected regions, effectively masking the background while preserving detected objects at their original appearance.

How This Block Works

This block takes an image and detection predictions and applies a colored overlay to all areas outside of the detected objects, leaving the detected regions unchanged. The block:

1. Takes an image and predictions as input
2. Creates a colored mask layer with the specified background color
3. Identifies detected regions from bounding boxes or segmentation masks (preserves detected objects)
4. Applies the colored overlay to all areas outside the detected regions with the specified opacity
5. Blends the colored overlay with the original image based on the opacity setting
6. Returns an annotated image where detected objects appear unchanged, while the background is filled with the specified color

The block works with both object detection predictions (using bounding boxes) and instance segmentation predictions (using masks). When masks are available, it preserves the exact shape of detected objects; otherwise, it uses bounding box regions. The opacity parameter controls how transparent or opaque the background overlay is, allowing you to create effects ranging from subtle background dimming (low opacity) to complete background replacement (high opacity). This creates a visual focus effect that highlights the detected objects by de-emphasizing or completely hiding the background.

Common Use Cases

• Object Focus and Highlighting: Highlight detected objects by dimming or replacing the background, making objects stand out for presentations, documentation, or user interfaces
• Background Removal Effects: Create images where backgrounds are replaced with solid colors or semi-transparent overlays for product photography, content creation, or design workflows
• Privacy and Anonymization: Mask backgrounds while preserving detected objects (e.g., people, vehicles) to anonymize images, protect privacy, or comply with data protection requirements
• Visual Debugging and Validation: Dim backgrounds to focus attention on detected regions when validating model performance, checking detection accuracy, or debugging detection results
• Presentation and Documentation: Create clean, professional visualizations for reports, presentations, or documentation where you want to emphasize detected objects without distracting backgrounds
• Content Creation and Editing: Prepare images for further processing, compositing, or editing by isolating detected objects with colored backgrounds for easier manipulation or integration into other workflows

Connecting to Other Blocks

The annotated image from this block can be connected to:

• Other visualization blocks (e.g., Label Visualization, Bounding Box Visualization, Polygon Visualization) to add additional annotations on top of the background-colored image for comprehensive visualization
• Data storage blocks (e.g., Local File Sink, CSV Formatter, Roboflow Dataset Upload) to save images with background coloring for documentation, reporting, or archiving
• Webhook blocks to send visualized results with background coloring to external systems, APIs, or web applications for display in dashboards or monitoring tools
• Notification blocks (e.g., Email Notification, Slack Notification) to send annotated images with background coloring as visual evidence in alerts or reports
• Video output blocks to create annotated video streams or recordings with background coloring for live monitoring, tracking visualization, or post-processing analysis

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 to use for the background overlay. Areas outside detected regions will be filled with this color. Can be a color name (e.g., 'BLACK', 'WHITE') or color code in HEX format (e.g., '#000000') or RGB format (e.g., 'rgb(0, 0, 0)')..	✅
opacity	float	Opacity of the background overlay, ranging from 0.0 (fully transparent, original background visible) to 1.0 (fully opaque, complete background replacement). Values between 0.0 and 1.0 create a blend between the original image and the background color. Lower values create subtle background dimming, while higher values create stronger background replacement effects..	✅

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: Trace Visualization, Detections Consensus, Background Color Visualization, VLM As Classifier, Florence-2 Model, Reference Path Visualization, Corner Visualization, Bounding Rectangle, SAM 3, Seg Preview, Perspective Correction, Roboflow Dataset Upload, Detection Offset, OpenAI, Model Monitoring Inference Aggregator, Image Threshold, Pixelate Visualization, Object Detection Model, Email Notification, Label Visualization, Image Slicer, Object Detection Model, Bounding Box Visualization, Google Vision OCR, Crop Visualization, VLM As Detector, Time in Zone, Image Blur, Path Deviation, Anthropic Claude, SIFT, Triangle Visualization, Detection Event Log, Instance Segmentation Model, Gaze Detection, Stitch Images, SIFT Comparison, Heatmap Visualization, SAM 3, Time in Zone, Mask Visualization, Detections Stitch, Email Notification, Stability AI Outpainting, Time in Zone, LMM For Classification, Segment Anything 2 Model, Google Gemini, Velocity, Anthropic Claude, Google Gemini, Dynamic Zone, Template Matching, Google Gemini, Twilio SMS Notification, Keypoint Detection Model, Byte Tracker, Roboflow Dataset Upload, Stability AI Image Generation, SIFT Comparison, Polygon Zone Visualization, YOLO-World Model, Depth Estimation, Dot Visualization, Llama 3.2 Vision, PTZ Tracking (ONVIF).md), Dynamic Crop, Detections Merge, Contrast Equalization, Circle Visualization, Slack Notification, Color Visualization, Image Slicer, Stability AI Inpainting, OpenAI, Clip Comparison, Local File Sink, Byte Tracker, Detections Transformation, JSON Parser, Relative Static Crop, Detections Filter, Instance Segmentation Model, Polygon Visualization, Ellipse Visualization, OCR Model, CogVLM, VLM As Detector, SAM 3, Stitch OCR Detections, Twilio SMS/MMS Notification, Stitch OCR Detections, Moondream2, Halo Visualization, Icon Visualization, Anthropic Claude, Image Contours, Morphological Transformation, Motion Detection, Line Counter, Blur Visualization, Detections List Roll-Up, Detections Combine, OpenAI, Polygon Visualization, CSV Formatter, Detections Stabilizer, Camera Calibration, Detections Classes Replacement, Single-Label Classification Model, Line Counter Visualization, Camera Focus, OpenAI, Webhook Sink, Image Convert Grayscale, LMM, Multi-Label Classification Model, Camera Focus, Classification Label Visualization, Model Comparison Visualization, EasyOCR, Image Preprocessing, VLM As Classifier, Grid Visualization, Background Subtraction, Halo Visualization, Overlap Filter, Keypoint Visualization, QR Code Generator, Identify Outliers, Florence-2 Model, Text Display, Identify Changes, Roboflow Custom Metadata, Byte Tracker, Mask Area Measurement, Keypoint Detection Model, Path Deviation, Absolute Static Crop
• outputs: Trace Visualization, Contrast Equalization, CLIP Embedding Model, Circle Visualization, Background Color Visualization, SmolVLM2, Perception Encoder Embedding Model, VLM As Classifier, Color Visualization, Florence-2 Model, Image Slicer, Stability AI Inpainting, Reference Path Visualization, OpenAI, Corner Visualization, Pixel Color Count, SAM 3, Clip Comparison, Seg Preview, Relative Static Crop, Perspective Correction, Roboflow Dataset Upload, OpenAI, Instance Segmentation Model, Image Threshold, Pixelate Visualization, Object Detection Model, Multi-Label Classification Model, Polygon Visualization, Ellipse Visualization, OCR Model, CogVLM, Label Visualization, VLM As Detector, Image Slicer, Dominant Color, Object Detection Model, Bounding Box Visualization, Google Vision OCR, Crop Visualization, Barcode Detection, SAM 3, Twilio SMS/MMS Notification, VLM As Detector, Image Blur, Qwen2.5-VL, Moondream2, Halo Visualization, Clip Comparison, Anthropic Claude, Icon Visualization, SIFT, QR Code Detection, Triangle Visualization, Anthropic Claude, Image Contours, Morphological Transformation, Motion Detection, Instance Segmentation Model, Gaze Detection, Stitch Images, Heatmap Visualization, Blur Visualization, SAM 3, OpenAI, Polygon Visualization, Mask Visualization, Detections Stabilizer, Detections Stitch, Email Notification, Stability AI Outpainting, Time in Zone, Google Gemini, Segment Anything 2 Model, LMM For Classification, Camera Calibration, Anthropic Claude, Google Gemini, Single-Label Classification Model, Google Gemini, Template Matching, Line Counter Visualization, OpenAI, Camera Focus, Image Convert Grayscale, Keypoint Detection Model, LMM, Byte Tracker, Multi-Label Classification Model, Camera Focus, Model Comparison Visualization, Classification Label Visualization, Roboflow Dataset Upload, Stability AI Image Generation, EasyOCR, SIFT Comparison, Qwen3-VL, Polygon Zone Visualization, YOLO-World Model, VLM As Classifier, Background Subtraction, Halo Visualization, Buffer, Keypoint Visualization, Florence-2 Model, Depth Estimation, Text Display, Single-Label Classification Model, Dot Visualization, Llama 3.2 Vision, Dynamic Crop, Image Preprocessing, Keypoint Detection Model, Absolute Static Crop

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[rle_instance_segmentation_prediction, keypoint_detection_prediction, object_detection_prediction, instance_segmentation_prediction]): Model predictions to visualize..
  • color (string): Color to use for the background overlay. Areas outside detected regions will be filled with this color. Can be a color name (e.g., 'BLACK', 'WHITE') or color code in HEX format (e.g., '#000000') or RGB format (e.g., 'rgb(0, 0, 0)')..
  • opacity (float_zero_to_one): Opacity of the background overlay, ranging from 0.0 (fully transparent, original background visible) to 1.0 (fully opaque, complete background replacement). Values between 0.0 and 1.0 create a blend between the original image and the background color. Lower values create subtle background dimming, while higher values create stronger background replacement effects..

• 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
}