Color Visualization¶
Class: ColorVisualizationBlockV1
Source: inference.core.workflows.core_steps.visualizations.color.v1.ColorVisualizationBlockV1
The ColorVisualization
block paints a solid color on detected
objects in an image using Supervision's sv.ColorAnnotator
.
Type identifier¶
Use the following identifier in step "type"
field: roboflow_core/color_visualization@v1
to 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_palette |
str |
Select a color palette for the visualised elements.. | ✅ |
palette_size |
int |
Specify the number of colors in the palette. This applies when using custom or Matplotlib palettes.. | ✅ |
custom_colors |
List[str] |
Define a list of custom colors for bounding boxes in HEX format.. | ✅ |
color_axis |
str |
Choose how bounding box colors are assigned.. | ✅ |
opacity |
float |
Transparency of the color 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 Color Visualization
in version v1
.
- inputs:
LMM For Classification
,Single-Label Classification Model
,Moondream2
,Detection Offset
,Florence-2 Model
,Background Color Visualization
,Identify Changes
,Anthropic Claude
,Llama 3.2 Vision
,Webhook Sink
,Halo Visualization
,OpenAI
,Reference Path Visualization
,Detections Merge
,Camera Calibration
,JSON Parser
,Detections Filter
,Segment Anything 2 Model
,Triangle Visualization
,Mask Visualization
,Dynamic Crop
,SIFT Comparison
,Stability AI Outpainting
,Ellipse Visualization
,Image Threshold
,Identify Outliers
,Byte Tracker
,Relative Static Crop
,Twilio SMS Notification
,Google Vision OCR
,VLM as Classifier
,Bounding Rectangle
,Path Deviation
,Object Detection Model
,Depth Estimation
,Time in Zone
,Line Counter
,Email Notification
,Roboflow Dataset Upload
,Bounding Box Visualization
,Detections Classes Replacement
,Roboflow Custom Metadata
,Path Deviation
,VLM as Classifier
,LMM
,Color Visualization
,Instance Segmentation Model
,Classification Label Visualization
,PTZ Tracking (ONVIF)
.md),Local File Sink
,Distance Measurement
,Polygon Zone Visualization
,CogVLM
,Multi-Label Classification Model
,Detections Transformation
,Trace Visualization
,Size Measurement
,Perspective Correction
,Byte Tracker
,YOLO-World Model
,Detections Stabilizer
,Polygon Visualization
,SIFT Comparison
,Velocity
,Byte Tracker
,Stability AI Inpainting
,Stitch OCR Detections
,Label Visualization
,Model Comparison Visualization
,Time in Zone
,Stability AI Image Generation
,Detections Stitch
,CSV Formatter
,Slack Notification
,Model Monitoring Inference Aggregator
,Keypoint Detection Model
,Pixelate Visualization
,Absolute Static Crop
,Object Detection Model
,Dynamic Zone
,Line Counter
,Camera Focus
,Detections Consensus
,Keypoint Visualization
,OpenAI
,Image Contours
,Blur Visualization
,Image Blur
,Keypoint Detection Model
,Grid Visualization
,Image Convert Grayscale
,VLM as Detector
,Corner Visualization
,SIFT
,Clip Comparison
,OpenAI
,Pixel Color Count
,Crop Visualization
,Dot Visualization
,Image Slicer
,Google Gemini
,Image Slicer
,Circle Visualization
,Buffer
,Florence-2 Model
,OCR Model
,VLM as Detector
,Template Matching
,Overlap Filter
,Roboflow Dataset Upload
,Gaze Detection
,Image Preprocessing
,Line Counter Visualization
,Instance Segmentation Model
,Dimension Collapse
,Stitch Images
,Clip Comparison
- outputs:
LMM For Classification
,Single-Label Classification Model
,Moondream2
,Florence-2 Model
,Background Color Visualization
,Anthropic Claude
,Llama 3.2 Vision
,Halo Visualization
,OpenAI
,Reference Path Visualization
,Camera Calibration
,Segment Anything 2 Model
,Triangle Visualization
,Mask Visualization
,Dynamic Crop
,Stability AI Outpainting
,Ellipse Visualization
,Byte Tracker
,Image Threshold
,Relative Static Crop
,Qwen2.5-VL
,VLM as Classifier
,Dominant Color
,Object Detection Model
,Depth Estimation
,Roboflow Dataset Upload
,Bounding Box Visualization
,QR Code Detection
,VLM as Classifier
,LMM
,Color Visualization
,Instance Segmentation Model
,Classification Label Visualization
,Polygon Zone Visualization
,CogVLM
,Multi-Label Classification Model
,Trace Visualization
,YOLO-World Model
,Perspective Correction
,Detections Stabilizer
,Polygon Visualization
,SIFT Comparison
,Stability AI Inpainting
,Label Visualization
,Model Comparison Visualization
,Time in Zone
,Stability AI Image Generation
,Detections Stitch
,Keypoint Detection Model
,Pixelate Visualization
,Object Detection Model
,Absolute Static Crop
,Camera Focus
,Keypoint Visualization
,OpenAI
,Image Contours
,Blur Visualization
,Image Blur
,Keypoint Detection Model
,Clip Comparison
,OpenAI
,VLM as Detector
,Image Convert Grayscale
,Corner Visualization
,SIFT
,Pixel Color Count
,Image Slicer
,Crop Visualization
,Dot Visualization
,Google Gemini
,Single-Label Classification Model
,Image Slicer
,Barcode Detection
,Circle Visualization
,SmolVLM2
,Buffer
,Florence-2 Model
,CLIP Embedding Model
,OCR Model
,VLM as Detector
,Template Matching
,Perception Encoder Embedding Model
,Multi-Label Classification Model
,Roboflow Dataset Upload
,Gaze Detection
,Instance Segmentation Model
,Line Counter Visualization
,Google Vision OCR
,Image Preprocessing
,Stitch Images
,Clip Comparison
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
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[keypoint_detection_prediction
,instance_segmentation_prediction
,object_detection_prediction
]): Model predictions to visualize..color_palette
(string
): Select a color palette for the visualised elements..palette_size
(integer
): Specify the number of colors in the palette. This applies when using custom or Matplotlib palettes..custom_colors
(list_of_values
): Define a list of custom colors for bounding boxes in HEX format..color_axis
(string
): Choose how bounding box colors are assigned..opacity
(float_zero_to_one
): Transparency of the color overlay..
-
output
image
(image
): Image in workflows.
Example JSON definition of step Color Visualization
in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/color_visualization@v1",
"image": "$inputs.image",
"copy_image": true,
"predictions": "$steps.object_detection_model.predictions",
"color_palette": "DEFAULT",
"palette_size": 10,
"custom_colors": [
"#FF0000",
"#00FF00",
"#0000FF"
],
"color_axis": "CLASS",
"opacity": 0.5
}