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

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
}