Detections Classes Replacement

Class: DetectionsClassesReplacementBlockV1

Source: inference.core.workflows.core_steps.fusion.detections_classes_replacement.v1.DetectionsClassesReplacementBlockV1

Combine results of detection model with classification results performed separately for each and every bounding box.

Bounding boxes without top class predicted by classification model are discarded, for multi-label classification results, most confident label is taken as bounding box class.

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌
fallback_class_name	str	The class name to be used as a fallback if no class is predicted for a bounding box.	✅
fallback_class_id	int	The class id to be used as a fallback if no class is predicted for a bounding box;if not specified or negative, the class id will be set to 9223372036854775807.	✅

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 Classes Replacement in version v1.

• inputs: VLM as Detector, Byte Tracker, Google Vision OCR, Overlap Filter, SAM 3, Detections Stabilizer, SIFT Comparison, Image Contours, Detections Filter, LMM For Classification, VLM as Classifier, Detections Combine, VLM as Classifier, Model Monitoring Inference Aggregator, Segment Anything 2 Model, Template Matching, Moondream2, Velocity, OCR Model, Distance Measurement, Florence-2 Model, Detections Transformation, EasyOCR, Gaze Detection, SIFT Comparison, Florence-2 Model, Detection Offset, Slack Notification, Clip Comparison, Instance Segmentation Model, OpenAI, Byte Tracker, Line Counter, PTZ Tracking (ONVIF).md), Object Detection Model, Keypoint Detection Model, Google Gemini, Email Notification, Llama 3.2 Vision, Byte Tracker, Dynamic Zone, Line Counter, YOLO-World Model, Email Notification, Time in Zone, CogVLM, OpenAI, Roboflow Custom Metadata, Detections Stitch, Stitch OCR Detections, Time in Zone, CSV Formatter, VLM as Detector, Single-Label Classification Model, OpenAI, Detections Classes Replacement, Perspective Correction, Twilio SMS Notification, Single-Label Classification Model, Seg Preview, Roboflow Dataset Upload, Roboflow Dataset Upload, Webhook Sink, Instance Segmentation Model, Multi-Label Classification Model, Time in Zone, Detections Merge, Path Deviation, Keypoint Detection Model, Anthropic Claude, LMM, Google Gemini, Multi-Label Classification Model, Pixel Color Count, Dynamic Crop, Bounding Rectangle, Path Deviation, Detections Consensus, Local File Sink, Object Detection Model
• outputs: Byte Tracker, Overlap Filter, Blur Visualization, Detections Stabilizer, Circle Visualization, Time in Zone, Crop Visualization, Detections Filter, Detections Classes Replacement, Perspective Correction, Ellipse Visualization, Triangle Visualization, Roboflow Dataset Upload, Detections Combine, Stability AI Inpainting, Detections Stitch, Roboflow Dataset Upload, Background Color Visualization, Model Monitoring Inference Aggregator, Segment Anything 2 Model, Velocity, Distance Measurement, Dot Visualization, Florence-2 Model, Bounding Box Visualization, Detections Transformation, Halo Visualization, Icon Visualization, Polygon Visualization, Florence-2 Model, Time in Zone, Detection Offset, Pixelate Visualization, Path Deviation, Byte Tracker, PTZ Tracking (ONVIF).md), Color Visualization, Line Counter, Detections Merge, Label Visualization, Byte Tracker, Trace Visualization, Dynamic Zone, Dynamic Crop, Bounding Rectangle, Path Deviation, Line Counter, Detections Consensus, Model Comparison Visualization, Size Measurement, Corner Visualization, Mask Visualization, Time in Zone, Keypoint Visualization, Roboflow Custom Metadata, Stitch OCR Detections

Input and Output Bindings

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

Bindings

• input

  • object_detection_predictions (Union[object_detection_prediction, keypoint_detection_prediction, instance_segmentation_prediction]): The output of a detection model describing the bounding boxes that will have classes replaced..
  • classification_predictions (classification_prediction): The output of classification model for crops taken based on RoIs pointed as the other parameter.
  • fallback_class_name (string): The class name to be used as a fallback if no class is predicted for a bounding box.
  • fallback_class_id (integer): The class id to be used as a fallback if no class is predicted for a bounding box;if not specified or negative, the class id will be set to 9223372036854775807.

• output

  • predictions (Union[object_detection_prediction, instance_segmentation_prediction, keypoint_detection_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 or Prediction with detected bounding boxes and detected keypoints in form of sv.Detections(...) object if keypoint_detection_prediction.

Example JSON definition of step Detections Classes Replacement in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/detections_classes_replacement@v1",
    "object_detection_predictions": "$steps.my_object_detection_model.predictions",
    "classification_predictions": "$steps.my_classification_model.predictions",
    "fallback_class_name": "unknown",
    "fallback_class_id": 77
}