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 Slicer,Stability AI Inpainting,Pixelate Visualization,Perspective Correction,Relative Static Crop,SIFT Comparison,Grid Visualization,Ellipse Visualization,SIFT,Model Comparison Visualization,Halo Visualization,Image Contours,Crop Visualization,Absolute Static Crop,Camera Focus,Image Blur,Trace Visualization,Distance Measurement,Circle Visualization,Image Preprocessing,Background Color Visualization,Dot Visualization,Polygon Zone Visualization,Pixel Color Count,Classification Label Visualization,Bounding Box Visualization,Corner Visualization,Image Slicer,Dynamic Crop,Reference Path Visualization,Line Counter,Label Visualization,Mask Visualization,Stitch Images,Triangle Visualization,Stability AI Image Generation,Image Threshold,Line Counter Visualization,Template Matching,Keypoint Visualization,Color Visualization,Blur Visualization,Line Counter,SIFT Comparison,Image Convert Grayscale,Polygon Visualization - outputs:
Segment Anything 2 Model,Image Slicer,Stability AI Inpainting,Clip Comparison,Perspective Correction,Object Detection Model,Object Detection Model,SIFT Comparison,Detection Offset,CogVLM,Ellipse Visualization,SIFT,VLM as Detector,Grid Visualization,Image Contours,Multi-Label Classification Model,OpenAI,Absolute Static Crop,Camera Focus,Trace Visualization,CLIP Embedding Model,Multi-Label Classification Model,VLM as Detector,Dot Visualization,Google Vision OCR,Clip Comparison,Identify Outliers,Polygon Zone Visualization,Gaze Detection,Roboflow Dataset Upload,VLM as Classifier,Identify Changes,Classification Label Visualization,Corner Visualization,Llama 3.2 Vision,Byte Tracker,Dynamic Crop,Reference Path Visualization,Detections Stabilizer,Label Visualization,Mask Visualization,Triangle Visualization,Template Matching,Line Counter Visualization,Dynamic Zone,Dominant Color,Barcode Detection,Blur Visualization,Anthropic Claude,Instance Segmentation Model,Webhook Sink,SIFT Comparison,Time in Zone,Instance Segmentation Model,Slack Notification,Stitch OCR Detections,Pixelate Visualization,OpenAI,Relative Static Crop,Detections Consensus,Twilio SMS Notification,VLM as Classifier,Keypoint Detection Model,Roboflow Dataset Upload,Google Gemini,Model Comparison Visualization,Halo Visualization,Crop Visualization,Qwen2.5-VL,Byte Tracker,Image Blur,Circle Visualization,Buffer,Keypoint Detection Model,Image Preprocessing,Background Color Visualization,QR Code Detection,Pixel Color Count,Florence-2 Model,Single-Label Classification Model,Bounding Box Visualization,Byte Tracker,Florence-2 Model,Image Slicer,LMM For Classification,Stitch Images,Stability AI Image Generation,Image Threshold,Detections Stitch,OCR Model,LMM,Keypoint Visualization,Email Notification,Color Visualization,Single-Label Classification Model,YOLO-World Model,Image Convert Grayscale,Polygon Visualization
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Image Contours in version v1 has.
Bindings
-
input
-
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
}