Detections Filter¶
Class: DetectionsFilterBlockV1
Source: inference.core.workflows.core_steps.transformations.detections_filter.v1.DetectionsFilterBlockV1
Conditionally filter out model predictions.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/detections_filter@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
operations |
List[Union[ClassificationPropertyExtract, ConvertDictionaryToJSON, ConvertImageToBase64, ConvertImageToJPEG, DetectionsFilter, DetectionsOffset, DetectionsPropertyExtract, DetectionsRename, DetectionsSelection, DetectionsShift, DetectionsToDictionary, Divide, ExtractDetectionProperty, ExtractImageProperty, LookupTable, Multiply, NumberRound, NumericSequenceAggregate, RandomNumber, SequenceAggregate, SequenceApply, SequenceLength, SequenceMap, SortDetections, StringMatches, StringSubSequence, StringToLowerCase, StringToUpperCase, ToBoolean, ToNumber, ToString]] |
Definition of filtering operations. | ❌ |
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 Filter in version v1.
- inputs:
Pixelate Visualization,Gaze Detection,CLIP Embedding Model,Blur Visualization,OCR Model,Mask Visualization,Object Detection Model,SIFT,Line Counter,YOLO-World Model,Cache Get,Halo Visualization,Environment Secrets Store,Grid Visualization,Google Vision OCR,Email Notification,Camera Focus,Byte Tracker,Image Threshold,Template Matching,Image Preprocessing,Roboflow Dataset Upload,Relative Static Crop,Background Color Visualization,Bounding Box Visualization,Image Contours,Triangle Visualization,Bounding Rectangle,Absolute Static Crop,Distance Measurement,Time in Zone,Detections Stitch,Florence-2 Model,SIFT Comparison,Keypoint Detection Model,Local File Sink,Expression,Roboflow Custom Metadata,Cache Set,Crop Visualization,Clip Comparison,Dynamic Zone,SIFT Comparison,Image Convert Grayscale,Single-Label Classification Model,Identify Outliers,Time in Zone,Florence-2 Model,Path Deviation,OpenAI,Color Visualization,Pixel Color Count,Multi-Label Classification Model,Property Definition,Path Deviation,Multi-Label Classification Model,Stitch Images,First Non Empty Or Default,LMM For Classification,Keypoint Detection Model,Line Counter,Instance Segmentation Model,Rate Limiter,Single-Label Classification Model,Detections Filter,Model Monitoring Inference Aggregator,Polygon Visualization,VLM as Detector,Model Comparison Visualization,CogVLM,Keypoint Visualization,Detections Classes Replacement,Data Aggregator,Detection Offset,Slack Notification,Stitch OCR Detections,Identify Changes,Clip Comparison,Ellipse Visualization,Label Visualization,Classification Label Visualization,Line Counter Visualization,Byte Tracker,LMM,Stability AI Inpainting,Reference Path Visualization,VLM as Detector,Dynamic Crop,Dominant Color,Byte Tracker,Object Detection Model,Barcode Detection,Corner Visualization,Perspective Correction,Cosine Similarity,Polygon Zone Visualization,VLM as Classifier,Continue If,Dimension Collapse,Twilio SMS Notification,Image Slicer,Detections Consensus,Size Measurement,OpenAI,Trace Visualization,Webhook Sink,Instance Segmentation Model,Buffer,Roboflow Dataset Upload,VLM as Classifier,Anthropic Claude,Image Blur,Circle Visualization,Dot Visualization,Google Gemini,QR Code Detection,Segment Anything 2 Model,JSON Parser,Detections Stabilizer,Delta Filter,CSV Formatter,Llama 3.2 Vision,Detections Transformation - outputs:
Time in Zone,Florence-2 Model,Path Deviation,Pixelate Visualization,Detections Stitch,Line Counter,Corner Visualization,Blur Visualization,Mask Visualization,Perspective Correction,Line Counter,Detections Filter,Model Monitoring Inference Aggregator,Polygon Visualization,Halo Visualization,Trace Visualization,Model Comparison Visualization,Size Measurement,Detections Consensus,Byte Tracker,Roboflow Custom Metadata,Keypoint Visualization,Detections Classes Replacement,Crop Visualization,Detection Offset,Roboflow Dataset Upload,Roboflow Dataset Upload,Stitch OCR Detections,Dynamic Zone,Dot Visualization,Circle Visualization,Background Color Visualization,Segment Anything 2 Model,Bounding Box Visualization,Ellipse Visualization,Label Visualization,Byte Tracker,Time in Zone,Florence-2 Model,Stability AI Inpainting,Detections Stabilizer,Path Deviation,Dynamic Crop,Byte Tracker,Triangle Visualization,Color Visualization,Bounding Rectangle,Detections Transformation,Distance Measurement
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Detections Filter in version v1 has.
Bindings
-
input
predictions(Union[instance_segmentation_prediction,keypoint_detection_prediction,object_detection_prediction]): Reference to detection-like predictions.operations_parameters(*): References to additional parameters that may be provided in runtime to parametrise operations.
-
output
predictions(Union[object_detection_prediction,instance_segmentation_prediction,keypoint_detection_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_predictionor Prediction with detected bounding boxes and detected keypoints in form of sv.Detections(...) object ifkeypoint_detection_prediction.
Example JSON definition of step Detections Filter in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/detections_filter@v1",
"predictions": "$steps.object_detection_model.predictions",
"operations": [
{
"filter_operation": {
"statements": [
{
"comparator": {
"type": "in (Sequence)"
},
"left_operand": {
"operations": [
{
"property_name": "class_name",
"type": "ExtractDetectionProperty"
}
],
"type": "DynamicOperand"
},
"right_operand": {
"operand_name": "classes",
"type": "DynamicOperand"
},
"type": "BinaryStatement"
}
],
"type": "StatementGroup"
},
"type": "DetectionsFilter"
}
],
"operations_parameters": {
"classes": "$inputs.classes"
}
}