Grid Visualization
Shows an array of images in a grid.
Arrange multiple images in a grid layout, automatically organizing a list of images into a square grid pattern with automatic resizing and cell-based positioning for side-by-side comparison, thumbnail displays, or batch visualization.
How This Block Works
This block takes a list of images and arranges them into a grid layout within a single output image. The block:
Takes a list of images and output dimensions (width and height) as input
Calculates the grid size based on the number of images (creates a square grid with dimensions equal to the square root of the image count, rounded up)
Divides the output canvas into equal-sized cells based on the grid dimensions
Resizes each input image to fit within its assigned cell while maintaining aspect ratio (images are scaled to fit the cell dimensions without distortion)
Places images in the grid starting from the top-left corner, filling left-to-right and top-to-bottom (row-major order)
Centers each resized image within its cell, creating evenly spaced grid layout
Returns a single output image containing all input images arranged in the grid
The block automatically organizes multiple images into a grid for easy comparison or batch viewing. Each image is resized to fit its grid cell while preserving aspect ratio, and images are centered within their cells. The grid dimensions are automatically calculated to create a roughly square grid (e.g., 4 images = 2x2, 9 images = 3x3, 10 images = 4x4). This creates a compact, organized layout ideal for comparing multiple images, displaying thumbnails, or creating batch visualization outputs. The block uses caching to optimize performance when the same images are reused.
Common Use Cases
Batch Image Comparison: Arrange multiple images side-by-side in a grid for easy comparison, allowing you to visualize results from different models, time periods, or processing steps simultaneously
Thumbnail Gallery Creation: Create thumbnail grids from collections of images for gallery displays, image browsers, or preview interfaces where multiple images need to be shown in a compact layout
Multi-Image Workflow Results: Display results from multi-image workflows (like batch processing, image slicer outputs, or buffer collections) in an organized grid format for overview visualization
Before/After Comparisons: Arrange before and after images, original and processed versions, or multiple workflow outputs in a grid for comparison and validation workflows
Time-Series Visualization: Display images from different time points, frames, or snapshots in a grid to visualize temporal changes, sequences, or progression over time
Quality Control and Review: Create grid layouts for quality control workflows, batch review, or inspection processes where multiple images need to be viewed together for evaluation or validation
Connecting to Other Blocks
The grid output image from this block can be connected to:
Image processing blocks (e.g., Buffer, Image Slicer, Dynamic Crop) to receive lists of images that are arranged into grid layouts
Data storage blocks (e.g., Local File Sink, CSV Formatter, Roboflow Dataset Upload) to save grid images for documentation, reporting, or batch review purposes
Webhook blocks to send grid visualizations to external systems, APIs, or web applications for display in dashboards, galleries, or batch viewing interfaces
Notification blocks (e.g., Email Notification, Slack Notification) to send grid images as visual evidence in alerts or reports containing multiple images
Video output blocks to create video streams or recordings with grid layouts for live multi-image monitoring or batch visualization workflows
Other visualization blocks that can accept single images, allowing grid outputs to be further processed or combined with additional annotations
Type identifier
Use the following identifier in step "type" field: roboflow_core/grid_visualization@v1 to add the block as a step in your workflow.
Properties
Name
Type
Description
Refs
name
str
Enter a unique identifier for this step..
❌
width
int
Width of the output grid image in pixels. Controls the total width of the canvas where the image grid will be arranged. The width is divided into equal-sized cells based on the grid dimensions. Typical values range from 1280 to 3840 pixels depending on desired output size and number of images..
✅
height
int
Height of the output grid image in pixels. Controls the total height of the canvas where the image grid will be arranged. The height is divided into equal-sized cells based on the grid dimensions. Typical values range from 720 to 2160 pixels depending on desired output size and number of images..
✅
The Refs column marks possibility to parametrise the property with dynamic values available in workflow runtime. See Bindings for more info.
Input and Output Bindings
The available connections depend on its binding kinds. Check what binding kinds Grid Visualization in version v1 has.
Input and output bindings
input
images(list_of_values): List of images to arrange in a grid layout. Can be a list of image outputs from blocks like Buffer, Image Slicer, Dynamic Crop, or other blocks that output multiple images. Images will be automatically arranged in a square grid (calculated from the number of images) and resized to fit their grid cells while maintaining aspect ratio..width(integer): Width of the output grid image in pixels. Controls the total width of the canvas where the image grid will be arranged. The width is divided into equal-sized cells based on the grid dimensions. Typical values range from 1280 to 3840 pixels depending on desired output size and number of images..height(integer): Height of the output grid image in pixels. Controls the total height of the canvas where the image grid will be arranged. The height is divided into equal-sized cells based on the grid dimensions. Typical values range from 720 to 2160 pixels depending on desired output size and number of images..
output
image(image): Image in workflows.
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