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:
Dynamic Zone,Line Counter,Clip Comparison,Anthropic Claude,SIFT Comparison,Pixel Color Count,Distance Measurement,Google Gemini,Florence-2 Model,Clip Comparison,SIFT Comparison,Line Counter,OpenAI,Dimension Collapse,Image Contours,Florence-2 Model,Template Matching,Buffer,Llama 3.2 Vision,Size Measurement - outputs:
Clip Comparison,Triangle Visualization,Mask Visualization,Instance Segmentation Model,Image Threshold,Anthropic Claude,Single-Label Classification Model,Object Detection Model,Detections Stitch,Dot Visualization,Barcode Detection,Pixelate Visualization,Multi-Label Classification Model,YOLO-World Model,Time in Zone,Keypoint Detection Model,Model Comparison Visualization,CogVLM,Roboflow Dataset Upload,Keypoint Visualization,Circle Visualization,Google Vision OCR,Segment Anything 2 Model,Blur Visualization,VLM as Classifier,Crop Visualization,Line Counter Visualization,Ellipse Visualization,Pixel Color Count,Dominant Color,Google Gemini,Byte Tracker,OCR Model,LMM,Background Color Visualization,Classification Label Visualization,Relative Static Crop,SIFT Comparison,Gaze Detection,Template Matching,VLM as Classifier,Buffer,Image Convert Grayscale,Image Blur,Halo Visualization,Single-Label Classification Model,Object Detection Model,Absolute Static Crop,Qwen2.5-VL,SIFT,Stability AI Image Generation,Trace Visualization,Detections Stabilizer,VLM as Detector,CLIP Embedding Model,Polygon Zone Visualization,Clip Comparison,Dynamic Crop,Roboflow Dataset Upload,Multi-Label Classification Model,LMM For Classification,OpenAI,Stitch Images,Keypoint Detection Model,Florence-2 Model,QR Code Detection,Image Slicer,Reference Path Visualization,Image Preprocessing,Camera Calibration,Label Visualization,Perspective Correction,Image Slicer,Instance Segmentation Model,Stability AI Inpainting,Camera Focus,Florence-2 Model,VLM as Detector,Corner Visualization,Color Visualization,OpenAI,Image Contours,Polygon Visualization,Llama 3.2 Vision,Bounding Box 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
}