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

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
}