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:
Circle Visualization,Background Color Visualization,Corner Visualization,Twilio SMS Notification,Slack Notification,VLM as Detector,LMM,Polygon Zone Visualization,Camera Focus,Image Slicer,Image Blur,Dot Visualization,Path Deviation,Detections Merge,Detection Offset,Google Gemini,Roboflow Dataset Upload,Stability AI Inpainting,Pixelate Visualization,Line Counter,OpenAI,Detections Consensus,Image Convert Grayscale,Absolute Static Crop,Stability AI Image Generation,Webhook Sink,Color Visualization,Image Threshold,Halo Visualization,Polygon Visualization,Detections Classes Replacement,VLM as Classifier,Dynamic Zone,Instance Segmentation Model,CogVLM,Camera Calibration,Email Notification,Object Detection Model,Classification Label Visualization,Single-Label Classification Model,Llama 3.2 Vision,Google Vision OCR,Roboflow Dataset Upload,Byte Tracker,Ellipse Visualization,Bounding Box Visualization,Object Detection Model,Line Counter Visualization,Image Preprocessing,Trace Visualization,Label Visualization,Local File Sink,Image Slicer,Detections Transformation,Anthropic Claude,Crop Visualization,Detections Stitch,OCR Model,Identify Outliers,YOLO-World Model,Relative Static Crop,Model Comparison Visualization,Stitch OCR Detections,Perspective Correction,Byte Tracker,OpenAI,Path Deviation,Mask Visualization,Time in Zone,Detections Filter,Clip Comparison,Time in Zone,Dynamic Crop,Template Matching,CSV Formatter,Byte Tracker,Florence-2 Model,Instance Segmentation Model,Keypoint Detection Model,Image Contours,SIFT,Reference Path Visualization,Florence-2 Model,Triangle Visualization,Bounding Rectangle,Model Monitoring Inference Aggregator,Velocity,SIFT Comparison,VLM as Detector,Keypoint Visualization,Identify Changes,Multi-Label Classification Model,LMM For Classification,Roboflow Custom Metadata,Grid Visualization,Segment Anything 2 Model,Detections Stabilizer,Stitch Images,Blur Visualization - outputs:
Circle Visualization,Background Color Visualization,Corner Visualization,Bounding Box Visualization,Trace Visualization,Label Visualization,Detections Transformation,Crop Visualization,Detections Stitch,Path Deviation,Detections Merge,Dot Visualization,Detection Offset,Roboflow Dataset Upload,Model Comparison Visualization,Stability AI Inpainting,Pixelate Visualization,Line Counter,Stitch OCR Detections,Perspective Correction,Detections Consensus,Byte Tracker,Path Deviation,Detections Stabilizer,Distance Measurement,Mask Visualization,Time in Zone,Detections Filter,Color Visualization,Time in Zone,Dynamic Crop,Halo Visualization,Polygon Visualization,Byte Tracker,Detections Classes Replacement,Florence-2 Model,Dynamic Zone,Florence-2 Model,Triangle Visualization,Model Monitoring Inference Aggregator,Bounding Rectangle,Velocity,Roboflow Dataset Upload,Roboflow Custom Metadata,Byte Tracker,Line Counter,Segment Anything 2 Model,Ellipse Visualization,Size Measurement,Blur 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 ifobject_detection_predictionor Prediction with detected bounding boxes and segmentation masks in form of sv.Detections(...) object ifinstance_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
}