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