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

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
}