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