Pixel Color Count¶
Class: PixelationCountBlockV1
Source: inference.core.workflows.core_steps.classical_cv.pixel_color_count.v1.PixelationCountBlockV1
Count the number of pixels that match a specific color within a given tolerance.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/pixel_color_count@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
target_color |
Union[Tuple[int, int, int], str] |
Target color to count in the image. Can be a hex string (like '#431112') RGB string (like '(128, 32, 64)') or a RGB tuple (like (18, 17, 67)).. | ✅ |
tolerance |
int |
Tolerance for color matching.. | ✅ |
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 Pixel Color Count in version v1.
- inputs:
Stitch Images,Pixelate Visualization,Multi-Label Classification Model,LMM For Classification,Line Counter,Blur Visualization,Single-Label Classification Model,Mask Visualization,OCR Model,Object Detection Model,SIFT,Line Counter,Model Monitoring Inference Aggregator,Polygon Visualization,Halo Visualization,Grid Visualization,Google Vision OCR,Model Comparison Visualization,Email Notification,Camera Focus,CogVLM,Image Threshold,Keypoint Visualization,Template Matching,Image Preprocessing,Roboflow Dataset Upload,Slack Notification,Stitch OCR Detections,Relative Static Crop,Background Color Visualization,Bounding Box Visualization,Ellipse Visualization,Image Contours,Label Visualization,Classification Label Visualization,Line Counter Visualization,LMM,Stability AI Inpainting,Reference Path Visualization,VLM as Detector,Dynamic Crop,Dominant Color,Triangle Visualization,Absolute Static Crop,Distance Measurement,Florence-2 Model,SIFT Comparison,Keypoint Detection Model,Corner Visualization,Perspective Correction,Local File Sink,Polygon Zone Visualization,VLM as Classifier,Image Slicer,Trace Visualization,Webhook Sink,OpenAI,Twilio SMS Notification,Roboflow Custom Metadata,Crop Visualization,Instance Segmentation Model,Roboflow Dataset Upload,Clip Comparison,Anthropic Claude,SIFT Comparison,Image Blur,Circle Visualization,Image Convert Grayscale,Dot Visualization,Google Gemini,Florence-2 Model,OpenAI,Color Visualization,Pixel Color Count,CSV Formatter,Llama 3.2 Vision - outputs:
Stitch Images,Pixelate Visualization,Keypoint Detection Model,SIFT Comparison,Instance Segmentation Model,Keypoint Detection Model,Corner Visualization,Blur Visualization,Mask Visualization,Object Detection Model,Perspective Correction,Polygon Visualization,Halo Visualization,Grid Visualization,Trace Visualization,Image Slicer,Webhook Sink,Detections Consensus,Twilio SMS Notification,Image Threshold,Byte Tracker,Keypoint Visualization,Email Notification,Instance Segmentation Model,Crop Visualization,Image Preprocessing,Detection Offset,Slack Notification,Stitch OCR Detections,Anthropic Claude,SIFT Comparison,Image Blur,Dot Visualization,Circle Visualization,Identify Changes,Dynamic Zone,Bounding Box Visualization,Ellipse Visualization,Label Visualization,Line Counter Visualization,Image Contours,Identify Outliers,Byte Tracker,Classification Label Visualization,Reference Path Visualization,Detections Stabilizer,Dominant Color,Byte Tracker,Color Visualization,Triangle Visualization,Pixel Color Count,Absolute Static Crop,Object Detection Model
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Pixel Color Count in version v1 has.
Bindings
-
input
-
output
matching_pixels_count(integer): Integer value.
Example JSON definition of step Pixel Color Count in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/pixel_color_count@v1",
"image": "$inputs.image",
"target_color": "#431112",
"tolerance": 10
}