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

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"
}