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

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
}