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

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
}