Dimension Collapse¶
Version v1¶
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 |
The unique name of 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¶
Check what blocks you can connect to Dimension Collapse in version v1.
- inputs:
Template Matching,Segment Anything 2 Model,Blur Visualization,Image Convert Grayscale,VLM as Detector,Circle Visualization,CogVLM,Absolute Static Crop,LMM For Classification,Background Color Visualization,YOLO-World Model,Detections Transformation,Polygon Visualization,Image Threshold,OCR Model,Detections Classes Replacement,Image Contours,Bounding Box Visualization,Object Detection Model,Roboflow Custom Metadata,Dimension Collapse,Clip Comparison,First Non Empty Or Default,Detections Filter,Instance Segmentation Model,Halo Visualization,SIFT,Roboflow Dataset Upload,Google Gemini,Dynamic Crop,Image Slicer,Detection Offset,Detections Stitch,Multi-Label Classification Model,Roboflow Dataset Upload,Barcode Detection,Camera Focus,Dot Visualization,Corner Visualization,OpenAI,Triangle Visualization,Relative Static Crop,Pixel Color Count,Pixelate Visualization,JSON Parser,Dynamic Zone,Detections Consensus,Label Visualization,Crop Visualization,Mask Visualization,LMM,Property Definition,QR Code Detection,Color Visualization,VLM as Classifier,Perspective Correction,OpenAI,Keypoint Detection Model,Clip Comparison,Anthropic Claude,Dominant Color,Continue If,Expression,SIFT Comparison,Image Blur,Ellipse Visualization,Single-Label Classification Model - outputs:
VLM as Detector,VLM as Classifier,Perspective Correction
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"
}