Grid Visualization¶
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¶
Check what blocks you can connect to Grid Visualization in version v1.
- inputs:
Google Gemini,Line Counter,Buffer,Image Contours,Pixel Color Count,Dynamic Zone,Florence-2 Model,Clip Comparison,SIFT Comparison,Dimension Collapse,Template Matching,Clip Comparison,Anthropic Claude,Florence-2 Model,Distance Measurement,Size Measurement,SIFT Comparison,OpenAI,Line Counter - outputs:
Multi-Label Classification Model,Reference Path Visualization,OpenAI,Single-Label Classification Model,OCR Model,LMM For Classification,Roboflow Dataset Upload,Stability AI Inpainting,Absolute Static Crop,Trace Visualization,Byte Tracker,Halo Visualization,Instance Segmentation Model,SIFT Comparison,SIFT,Pixelate Visualization,Anthropic Claude,Classification Label Visualization,Mask Visualization,Background Color Visualization,Crop Visualization,Relative Static Crop,VLM as Classifier,Google Gemini,Image Contours,Gaze Detection,Image Threshold,Keypoint Detection Model,Multi-Label Classification Model,YOLO-World Model,Instance Segmentation Model,Template Matching,Florence-2 Model,Object Detection Model,CogVLM,LMM,Roboflow Dataset Upload,Camera Focus,Keypoint Visualization,Label Visualization,Polygon Zone Visualization,Pixel Color Count,Object Detection Model,Triangle Visualization,Barcode Detection,Single-Label Classification Model,Clip Comparison,Ellipse Visualization,Detections Stitch,Clip Comparison,Image Blur,Dot Visualization,Model Comparison Visualization,VLM as Detector,Dynamic Crop,Image Slicer,VLM as Classifier,Perspective Correction,Line Counter Visualization,Time in Zone,Google Vision OCR,Image Convert Grayscale,Buffer,Stitch Images,Blur Visualization,Florence-2 Model,Keypoint Detection Model,Color Visualization,Dominant Color,Image Preprocessing,QR Code Detection,CLIP Embedding Model,VLM as Detector,Polygon Visualization,Detections Stabilizer,Segment Anything 2 Model,OpenAI,Circle Visualization,Bounding Box Visualization,Corner 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
}