Image Contours

Class: ImageContoursDetectionBlockV1

Source: inference.core.workflows.core_steps.classical_cv.contours.v1.ImageContoursDetectionBlockV1

Finds the contours in an image. It returns the contours and number of contours. The input image should be thresholded before using this block.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
line_thickness	int	Line thickness for drawing contours..	✅

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 Contours in version v1.

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

Input and Output Bindings

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

Bindings

• input

  • image (image): The input image for this step..
  • line_thickness (integer): Line thickness for drawing contours..

• output

  • image (image): Image in workflows.
  • contours (contours): List of numpy arrays where each array represents contour points.
  • hierarchy (numpy_array): Numpy array.
  • number_contours (integer): Integer value.

Example JSON definition of step Image Contours in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/contours_detection@v1",
    "image": "$inputs.image",
    "line_thickness": 3
}