Dimension Collapse

Class: DimensionCollapseBlockV1

Source: inference.core.workflows.core_steps.fusion.dimension_collapse.v1.DimensionCollapseBlockV1

Takes multiple step outputs at data depth level n, concatenate them into list and reduce dimensionality to level n-1.

Useful in scenarios like: * aggregation of classification results for dynamically cropped images * aggregation of OCR results for dynamically cropped images

Type identifier

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

Properties

Name	Type	Description	Refs
name	str	Enter a unique identifier for this step..	❌

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 Dimension Collapse in version v1.

• inputs: Image Contours, Line Counter, Stability AI Inpainting, Corner Visualization, CSV Formatter, Google Gemini, Model Monitoring Inference Aggregator, Expression, Florence-2 Model, YOLO-World Model, SIFT Comparison, Property Definition, JSON Parser, PTZ Tracking (ONVIF).md), Image Convert Grayscale, Byte Tracker, Pixelate Visualization, Dominant Color, Model Comparison Visualization, Detections Stitch, Trace Visualization, Path Deviation, Velocity, Twilio SMS Notification, Bounding Rectangle, Label Visualization, Classification Label Visualization, Blur Visualization, Moondream2, Bounding Box Visualization, Template Matching, Anthropic Claude, Detection Offset, Pixel Color Count, Polygon Zone Visualization, VLM as Classifier, Gaze Detection, Image Slicer, Image Slicer, Cache Get, Crop Visualization, Perspective Correction, Dot Visualization, QR Code Detection, Mask Visualization, Local File Sink, Absolute Static Crop, Image Blur, OpenAI, Path Deviation, Detections Merge, Distance Measurement, Triangle Visualization, Background Color Visualization, CLIP Embedding Model, SIFT Comparison, Florence-2 Model, Camera Calibration, Image Threshold, Single-Label Classification Model, Buffer, Rate Limiter, OpenAI, CogVLM, Keypoint Detection Model, SIFT, Grid Visualization, Stitch Images, Identify Outliers, Stability AI Outpainting, Size Measurement, Polygon Visualization, Barcode Detection, Byte Tracker, Delta Filter, LMM For Classification, Detections Consensus, Time in Zone, Line Counter Visualization, Continue If, Keypoint Detection Model, Reference Path Visualization, Circle Visualization, OCR Model, Llama 3.2 Vision, Relative Static Crop, Dimension Collapse, Roboflow Dataset Upload, Dynamic Zone, Detections Classes Replacement, Multi-Label Classification Model, Object Detection Model, LMM, Roboflow Dataset Upload, Depth Estimation, Perception Encoder Embedding Model, OpenAI, Color Visualization, Ellipse Visualization, Instance Segmentation Model, Detections Transformation, Object Detection Model, Roboflow Custom Metadata, VLM as Detector, Halo Visualization, Environment Secrets Store, Cache Set, Detections Stabilizer, Keypoint Visualization, SmolVLM2, Line Counter, Stitch OCR Detections, Clip Comparison, Cosine Similarity, VLM as Classifier, Qwen2.5-VL, Clip Comparison, Byte Tracker, Identify Changes, Instance Segmentation Model, Data Aggregator, Overlap Filter, Segment Anything 2 Model, Google Vision OCR, Image Preprocessing, Slack Notification, VLM as Detector, Stability AI Image Generation, First Non Empty Or Default, Camera Focus, Multi-Label Classification Model, Webhook Sink, Dynamic Crop, Time in Zone, Email Notification, Single-Label Classification Model, Detections Filter
• outputs: Line Counter, Detections Consensus, Corner Visualization, Cache Set, Time in Zone, Mask Visualization, Google Gemini, Keypoint Visualization, Line Counter Visualization, Reference Path Visualization, Keypoint Detection Model, Florence-2 Model, YOLO-World Model, Circle Visualization, Llama 3.2 Vision, Line Counter, Clip Comparison, OpenAI, Roboflow Dataset Upload, VLM as Classifier, Perspective Correction, Clip Comparison, Path Deviation, LMM For Classification, Instance Segmentation Model, Object Detection Model, Trace Visualization, Triangle Visualization, Path Deviation, Roboflow Dataset Upload, Florence-2 Model, Label Visualization, Classification Label Visualization, Buffer, Color Visualization, OpenAI, VLM as Detector, Bounding Box Visualization, Keypoint Detection Model, Ellipse Visualization, Instance Segmentation Model, Anthropic Claude, VLM as Classifier, Polygon Zone Visualization, Object Detection Model, Grid Visualization, Size Measurement, Polygon Visualization, VLM as Detector, Webhook Sink, Time in Zone, Email Notification, Crop Visualization, Halo Visualization, Dot Visualization

Input and Output Bindings

The available connections depend on its binding kinds. Check what binding kinds Dimension Collapse in version v1 has.

Bindings

• input

  • data (*): Reference to step outputs at depth level n to be concatenated and moved into level n-1..

• output

  • output (list_of_values): List of values of any type.

Example JSON definition of step Dimension Collapse in version v1

{
    "name": "<your_step_name_here>",
    "type": "roboflow_core/dimension_collapse@v1",
    "data": "$steps.ocr_step.results"
}