Detections Stitch

Class: DetectionsStitchBlockV1

Source: inference.core.workflows.core_steps.fusion.detections_stitch.v1.DetectionsStitchBlockV1

This block merges detections that were inferred for multiple sub-parts of the same input image into single detection.

Block may be helpful in the following scenarios: * to apply Slicing Adaptive Inference (SAHI) technique, as a final step of procedure, which involves Image Slicer block and model block at previous stages. * to merge together detections performed by precise, high-resolution model applied as secondary model after coarse detection is performed in the first stage and Dynamic Crop is applied later.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
overlap_filtering_strategy	str	Which strategy to employ when filtering overlapping boxes. None does nothing, NMS discards lower-confidence detections, NMM combines them..	✅
iou_threshold	float	Minimum overlap threshold between boxes. If intersection over union (IoU) is above this ratio, discard or merge the lower confidence box..	✅

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 Detections Stitch in version v1.

• inputs: Detections Consensus, Path Deviation, Llama 3.2 Vision, Blur Visualization, SAM 3, Perspective Correction, Polygon Zone Visualization, Bounding Box Visualization, QR Code Generator, Pixelate Visualization, Trace Visualization, Velocity, Roboflow Custom Metadata, Detections Transformation, Segment Anything 2 Model, Image Threshold, Polygon Visualization, Dynamic Crop, Icon Visualization, Image Slicer, Identify Outliers, Stability AI Outpainting, Model Comparison Visualization, Dynamic Zone, LMM, OpenAI, Classification Label Visualization, Stitch Images, Florence-2 Model, Mask Visualization, Single-Label Classification Model, Relative Static Crop, Absolute Static Crop, SIFT Comparison, SAM 3, Time in Zone, Moondream2, Google Gemini, Circle Visualization, Florence-2 Model, LMM For Classification, Ellipse Visualization, Image Convert Grayscale, Time in Zone, Object Detection Model, OCR Model, Image Preprocessing, Color Visualization, Image Blur, Stability AI Image Generation, Google Vision OCR, Anthropic Claude, Keypoint Visualization, Camera Calibration, VLM as Detector, Local File Sink, EasyOCR, Image Slicer, Line Counter, VLM as Detector, Email Notification, Detections Combine, Detections Filter, Byte Tracker, Overlap Filter, Background Color Visualization, Triangle Visualization, Roboflow Dataset Upload, Slack Notification, Keypoint Detection Model, Halo Visualization, Object Detection Model, Corner Visualization, Detections Stabilizer, Google Gemini, Model Monitoring Inference Aggregator, Roboflow Dataset Upload, Dot Visualization, Image Contours, Detections Merge, Multi-Label Classification Model, Twilio SMS Notification, Byte Tracker, Instance Segmentation Model, Seg Preview, VLM as Classifier, CSV Formatter, Reference Path Visualization, Morphological Transformation, Motion Detection, OpenAI, Byte Tracker, Webhook Sink, PTZ Tracking (ONVIF).md), Detections Classes Replacement, Instance Segmentation Model, Detections Stitch, Contrast Equalization, Camera Focus, YOLO-World Model, Stitch OCR Detections, Stability AI Inpainting, CogVLM, Clip Comparison, Line Counter Visualization, Identify Changes, Template Matching, Path Deviation, Email Notification, Crop Visualization, Grid Visualization, OpenAI, Bounding Rectangle, SIFT, Depth Estimation, Background Subtraction, Label Visualization, SAM 3, Anthropic Claude, Time in Zone, Detection Offset, OpenAI
• outputs: Line Counter, Detections Consensus, Path Deviation, Model Monitoring Inference Aggregator, Roboflow Dataset Upload, Blur Visualization, Dot Visualization, Detections Merge, Perspective Correction, Byte Tracker, Bounding Box Visualization, Pixelate Visualization, Distance Measurement, Trace Visualization, Roboflow Custom Metadata, Velocity, Byte Tracker, Detections Transformation, Segment Anything 2 Model, PTZ Tracking (ONVIF).md), Polygon Visualization, Dynamic Crop, Icon Visualization, Detections Classes Replacement, Model Comparison Visualization, Dynamic Zone, Detections Stitch, Size Measurement, Florence-2 Model, Mask Visualization, Stitch OCR Detections, Stability AI Inpainting, Time in Zone, Circle Visualization, Florence-2 Model, Ellipse Visualization, Time in Zone, Path Deviation, Crop Visualization, Color Visualization, Bounding Rectangle, Line Counter, Detections Combine, Label Visualization, Byte Tracker, Roboflow Dataset Upload, Overlap Filter, Triangle Visualization, Background Color Visualization, Detections Filter, Time in Zone, Detection Offset, Halo Visualization, Detections Stabilizer, Corner Visualization

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Detections Stitch in version v1 has.

Bindings

• input

  • reference_image (image): Original image that was cropped to produce the predictions..
  • predictions (Union[instance_segmentation_prediction, object_detection_prediction]): Model predictions to be merged into the original image..
  • overlap_filtering_strategy (string): Which strategy to employ when filtering overlapping boxes. None does nothing, NMS discards lower-confidence detections, NMM combines them..
  • iou_threshold (float_zero_to_one): Minimum overlap threshold between boxes. If intersection over union (IoU) is above this ratio, discard or merge the lower confidence box..

• output

  • predictions (Union[object_detection_prediction, instance_segmentation_prediction]): Prediction with detected bounding boxes in form of sv.Detections(...) object if object_detection_prediction or Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object if instance_segmentation_prediction.

Example JSON definition of step Detections Stitch in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/detections_stitch@v1",
    "reference_image": "$inputs.image",
    "predictions": "$steps.my_object_detection_model.predictions",
    "overlap_filtering_strategy": "nms",
    "iou_threshold": 0.4
}