Today we’re excited to announce the release of ImagePlot 1.1 - a free software tool that visualizes collections of images and video. This updated version was developed by Jay Chow and Matias Giachino. The development was supported by Mellon Foundation grant "Tools for the Analysis and Visualization of Large Image and Video Collections for the Humanities."
Download ImagePlot 1.1
ImagePlot creates new types of visualizations not offered by any other application. It displays your data and images as a 2D line graph or a scatter plot, with the images superimposed over data points. The images can be sorted using any available metadata (e.g, dates), or by their visual properties which can be automatically measured with the included software. ImagePlot works on Mac, Windows, and Linux. Max visualization size: up to 2.5 GB (for example, you can render a 23,000 x 23,000 pixels visualization.) There no limits on how many images can be shown in a single visualization. (Largest image collections we visualized so far: 1 million manga pages; 1 million deviantArt artworks.)
What's New in Version 1.1
- Each new visualization is given automatically generated meaningful unique filename. It includes the names of data file and the data columns used for x-axis and y-axis.
- Option to automatically save the visualization after it have been rendered (appears in the first application dialog box).
- Option to render the visualization using a better resize algorithm (runs slower but generates nicer images; the option appears in the Image Options dialog box).
- File open error checking: if ImagePlot can't find a particular image, the filename is printed in the Log window, but rendering continues.
Comparing 90,000 images from Digital Art category on deviantArt (left) and 90,000 images from Traditional Art category (right). In each image plot, images are sorted by average brightness (x) and average saturation (y). Software which analyzes these and other image properties is included with ImagePlot.
ImagePlot code can be easily extended and customized. This visualization compares image galleries from a number of deviantArt users. The colors of the circles indicate the primary and secondary categories of each image (e.g., Traditional Art / Portraits). The individual plots are combined into a matrix using ImageJ built-in command.
ImagePlot can create animated visualizations. Here we animated 128 paintings by Piet Mondrian from 1904-1917 over time. The year is indicated in the upper left corner. The distances between paintings indicate their visual similarity.