Image Threshold

Class: ImageThresholdBlockV1

Source: inference.core.workflows.core_steps.classical_cv.threshold.v1.ImageThresholdBlockV1

Apply a threshold to an image. The image must be in grayscale.

Type identifier

Use the following identifier in step "type" field: roboflow_core/threshold@v1to add the block as as step in your workflow.

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
threshold_type	str	Type of Edge Detection to perform..	✅
thresh_value	int	Threshold value..	✅
max_value	int	Maximum value for thresholding.	✅

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 Image Threshold in version v1.

• inputs: Florence-2 Model, Model Monitoring Inference Aggregator, Label Visualization, Depth Estimation, Florence-2 Model, Triangle Visualization, CogVLM, Image Blur, OCR Model, Model Comparison Visualization, Line Counter Visualization, Circle Visualization, Relative Static Crop, Trace Visualization, Multi-Label Classification Model, Stitch Images, Reference Path Visualization, Llama 3.2 Vision, Polygon Visualization, Roboflow Dataset Upload, Roboflow Custom Metadata, SIFT, Single-Label Classification Model, Image Threshold, Keypoint Visualization, Ellipse Visualization, Crop Visualization, Color Visualization, Image Slicer, VLM as Classifier, Local File Sink, Dynamic Crop, Google Gemini, OpenAI, Dot Visualization, Instance Segmentation Model, Roboflow Dataset Upload, Keypoint Detection Model, Stability AI Inpainting, Line Counter, Google Vision OCR, Template Matching, Corner Visualization, Background Color Visualization, Polygon Zone Visualization, Camera Focus, Grid Visualization, Perspective Correction, Stability AI Image Generation, VLM as Detector, Line Counter, Image Slicer, CSV Formatter, OpenAI, Clip Comparison, Blur Visualization, Classification Label Visualization, Image Convert Grayscale, Image Preprocessing, Slack Notification, SIFT Comparison, OpenAI, Pixel Color Count, Stability AI Outpainting, Anthropic Claude, Webhook Sink, Camera Calibration, Mask Visualization, Bounding Box Visualization, Distance Measurement, Pixelate Visualization, Twilio SMS Notification, Email Notification, Stitch OCR Detections, Image Contours, Object Detection Model, Absolute Static Crop, Halo Visualization, LMM For Classification, SIFT Comparison, LMM
• outputs: Florence-2 Model, Label Visualization, Florence-2 Model, Depth Estimation, Triangle Visualization, CogVLM, Image Blur, OCR Model, Model Comparison Visualization, Line Counter Visualization, Circle Visualization, Relative Static Crop, Barcode Detection, Detections Stitch, Trace Visualization, Multi-Label Classification Model, Object Detection Model, Clip Comparison, Gaze Detection, Stitch Images, Dominant Color, Reference Path Visualization, Llama 3.2 Vision, Polygon Visualization, Time in Zone, Segment Anything 2 Model, Roboflow Dataset Upload, Single-Label Classification Model, SIFT, Image Threshold, CLIP Embedding Model, VLM as Classifier, Keypoint Visualization, Crop Visualization, Image Slicer, Color Visualization, Ellipse Visualization, Google Gemini, Dynamic Crop, OpenAI, Instance Segmentation Model, Multi-Label Classification Model, Dot Visualization, Instance Segmentation Model, Roboflow Dataset Upload, Keypoint Detection Model, SmolVLM2, Keypoint Detection Model, Stability AI Inpainting, Google Vision OCR, Single-Label Classification Model, Template Matching, Corner Visualization, Background Color Visualization, Polygon Zone Visualization, Camera Focus, Stability AI Image Generation, Perspective Correction, VLM as Detector, Image Slicer, OpenAI, Qwen2.5-VL, Clip Comparison, Blur Visualization, Classification Label Visualization, Image Convert Grayscale, Image Preprocessing, SIFT Comparison, Byte Tracker, Pixel Color Count, Detections Stabilizer, OpenAI, YOLO-World Model, Stability AI Outpainting, Perception Encoder Embedding Model, QR Code Detection, Anthropic Claude, Moondream2, Camera Calibration, Buffer, Mask Visualization, Bounding Box Visualization, Pixelate Visualization, Object Detection Model, Image Contours, Absolute Static Crop, Halo Visualization, LMM For Classification, VLM as Detector, LMM, VLM as Classifier

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Image Threshold in version v1 has.

Bindings

• input

  • image (image): The input image for this step..
  • threshold_type (string): Type of Edge Detection to perform..
  • thresh_value (integer): Threshold value..
  • max_value (integer): Maximum value for thresholding.

• output

  • image (image): Image in workflows.

Example JSON definition of step Image Threshold in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/threshold@v1",
    "image": "$inputs.image",
    "threshold_type": "binary",
    "thresh_value": 127,
    "max_value": 255
}