Grid Visualization¶
Class: GridVisualizationBlockV1
Source: inference.core.workflows.core_steps.visualizations.grid.v1.GridVisualizationBlockV1
The GridVisualization block displays an array of images in a grid.
It will automatically resize the images to in the specified width and
height. The first image will be in the top left corner, and the rest
will be added to the right of the previous image until the row is full.
Type identifier¶
Use the following identifier in step "type" field: roboflow_core/grid_visualization@v1to add the block as
as step in your workflow.
Properties¶
| Name | Type | Description | Refs |
|---|---|---|---|
name |
str |
Enter a unique identifier for this step.. | ❌ |
width |
int |
Width of the output image.. | ✅ |
height |
int |
Height of the output image.. | ✅ |
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 Grid Visualization in version v1.
- inputs:
Dimension Collapse,Line Counter,Anthropic Claude,Florence-2 Model,Llama 3.2 Vision,Google Gemini,Dynamic Zone,Distance Measurement,Clip Comparison,Florence-2 Model,Line Counter,Buffer,Size Measurement,SIFT Comparison,Clip Comparison,Template Matching,OpenAI,Pixel Color Count,SIFT Comparison,Image Contours - outputs:
Reference Path Visualization,Florence-2 Model,Triangle Visualization,Florence-2 Model,Circle Visualization,Keypoint Detection Model,Dot Visualization,Multi-Label Classification Model,Mask Visualization,Stability AI Image Generation,Polygon Zone Visualization,SIFT Comparison,Stitch Images,LMM For Classification,Classification Label Visualization,VLM as Detector,Background Color Visualization,Byte Tracker,Camera Focus,Image Convert Grayscale,Color Visualization,Single-Label Classification Model,Google Gemini,Pixelate Visualization,Gaze Detection,Perspective Correction,Clip Comparison,Image Preprocessing,Trace Visualization,Absolute Static Crop,Corner Visualization,VLM as Classifier,Stability AI Inpainting,Keypoint Detection Model,VLM as Classifier,Template Matching,Halo Visualization,Keypoint Visualization,SIFT,Label Visualization,Image Contours,Single-Label Classification Model,Image Threshold,Time in Zone,Line Counter Visualization,Instance Segmentation Model,Polygon Visualization,Object Detection Model,VLM as Detector,Bounding Box Visualization,Buffer,Roboflow Dataset Upload,OpenAI,Object Detection Model,Model Comparison Visualization,Ellipse Visualization,Clip Comparison,Detections Stitch,Instance Segmentation Model,YOLO-World Model,Pixel Color Count,CLIP Embedding Model,Relative Static Crop,Crop Visualization,Image Blur,LMM,Google Vision OCR,Barcode Detection,CogVLM,Anthropic Claude,Llama 3.2 Vision,Multi-Label Classification Model,QR Code Detection,Segment Anything 2 Model,Dynamic Crop,Detections Stabilizer,OCR Model,Image Slicer,OpenAI,Roboflow Dataset Upload,Dominant Color,Blur Visualization
Input and Output Bindings¶
The available connections depend on its binding kinds. Check what binding kinds
Grid Visualization in version v1 has.
Bindings
-
input
images(list_of_values): Images to visualize.width(integer): Width of the output image..height(integer): Height of the output image..
-
output
image(image): Image in workflows.
Example JSON definition of step Grid Visualization in version v1
{
"name": "<your_step_name_here>",
"type": "roboflow_core/grid_visualization@v1",
"images": "$steps.buffer.output",
"width": 2560,
"height": 1440
}