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: Multi-Label Classification Model, Single-Label Classification Model, Classification Label Visualization, Background Color Visualization, Webhook Sink, Dynamic Crop, Mask Visualization, Clip Comparison, Google Vision OCR, Twilio SMS Notification, Absolute Static Crop, Model Monitoring Inference Aggregator, Stability AI Image Generation, Florence-2 Model, Image Blur, LMM For Classification, Roboflow Dataset Upload, CogVLM, Line Counter, Circle Visualization, OCR Model, Crop Visualization, Template Matching, SIFT Comparison, OpenAI, Stitch OCR Detections, OpenAI, Image Preprocessing, Pixel Color Count, Line Counter, Model Comparison Visualization, Stitch Images, Bounding Box Visualization, Keypoint Detection Model, Dominant Color, Perspective Correction, SIFT Comparison, Relative Static Crop, Slack Notification, Color Visualization, Ellipse Visualization, Reference Path Visualization, Blur Visualization, Pixelate Visualization, Anthropic Claude, Email Notification, LMM, Llama 3.2 Vision, CSV Formatter, VLM as Detector, Keypoint Visualization, Camera Focus, Florence-2 Model, Grid Visualization, Image Convert Grayscale, Image Threshold, Trace Visualization, Polygon Visualization, Triangle Visualization, Stability AI Inpainting, Halo Visualization, Dot Visualization, Polygon Zone Visualization, Google Gemini, Local File Sink, Instance Segmentation Model, Roboflow Custom Metadata, VLM as Classifier, Camera Calibration, Object Detection Model, SIFT, Corner Visualization, Image Contours, Line Counter Visualization, Roboflow Dataset Upload, Image Slicer, Image Slicer, Label Visualization, Distance Measurement
• outputs: Reference Path Visualization, Identify Outliers, Blur Visualization, Anthropic Claude, Pixelate Visualization, Email Notification, Classification Label Visualization, Instance Segmentation Model, Webhook Sink, Keypoint Visualization, Mask Visualization, Byte Tracker, Image Slicer, Twilio SMS Notification, Absolute Static Crop, Detection Offset, Image Blur, Identify Changes, Circle Visualization, Grid Visualization, Crop Visualization, Trace Visualization, Image Threshold, SIFT Comparison, Object Detection Model, Polygon Visualization, Detections Consensus, Stitch OCR Detections, Keypoint Detection Model, Color Visualization, Triangle Visualization, Halo Visualization, Dot Visualization, Dynamic Zone, Instance Segmentation Model, Pixel Color Count, Detections Stabilizer, Object Detection Model, Image Contours, Corner Visualization, Stitch Images, Line Counter Visualization, Bounding Box Visualization, Image Slicer, Keypoint Detection Model, Dominant Color, Perspective Correction, Image Preprocessing, Byte Tracker, SIFT Comparison, Byte Tracker, Label Visualization, Slack Notification, Ellipse Visualization

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

  • image (image): The input image for this step..
  • target_color (Union[rgb_color, string]): 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 (integer): Tolerance for color matching..

• 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
}