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: Line Counter, OpenAI, Dimension Collapse, Florence-2 Model, OpenAI, Image Contours, Dynamic Zone, Clip Comparison, Pixel Color Count, Llama 3.2 Vision, Clip Comparison, Distance Measurement, Line Counter, Perspective Correction, Google Gemini, Buffer, SIFT Comparison, Size Measurement, SIFT Comparison, Template Matching, Florence-2 Model, Anthropic Claude
• outputs: Keypoint Detection Model, Gaze Detection, Halo Visualization, OpenAI, Stability AI Image Generation, Model Comparison Visualization, Keypoint Visualization, Crop Visualization, Image Blur, Bounding Box Visualization, Roboflow Dataset Upload, Template Matching, Mask Visualization, SmolVLM2, VLM as Classifier, Image Slicer, Instance Segmentation Model, Instance Segmentation Model, QR Code Detection, CLIP Embedding Model, Ellipse Visualization, OpenAI, VLM as Detector, Qwen2.5-VL, Label Visualization, Google Vision OCR, Stability AI Outpainting, Single-Label Classification Model, Buffer, Polygon Visualization, Barcode Detection, Dominant Color, Reference Path Visualization, Florence-2 Model, OCR Model, VLM as Detector, Anthropic Claude, Image Preprocessing, Line Counter Visualization, Florence-2 Model, Image Contours, Camera Calibration, Single-Label Classification Model, LMM For Classification, Clip Comparison, Corner Visualization, Pixel Color Count, Stitch Images, SIFT, Depth Estimation, Time in Zone, Perception Encoder Embedding Model, Blur Visualization, Image Convert Grayscale, Image Slicer, Background Color Visualization, Dynamic Crop, Perspective Correction, Circle Visualization, Triangle Visualization, Dot Visualization, CogVLM, Multi-Label Classification Model, Object Detection Model, Segment Anything 2 Model, VLM as Classifier, LMM, Color Visualization, OpenAI, Classification Label Visualization, Stability AI Inpainting, Byte Tracker, Moondream2, Absolute Static Crop, Image Threshold, Keypoint Detection Model, Llama 3.2 Vision, Pixelate Visualization, Trace Visualization, Detections Stabilizer, Camera Focus, Roboflow Dataset Upload, Clip Comparison, YOLO-World Model, Google Gemini, SIFT Comparison, Multi-Label Classification Model, Relative Static Crop, Detections Stitch, Object Detection Model, Polygon Zone 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
}