Understanding Grouped Datasets – FiftyOne Tips and Tricks – Sep 1, 2023

This week's FiftyOne tips and tricks blog delves into Grouped Datasets. Grouped datasets are collections of multiple slices of samples, possibly of different modalities (image, video, or point cloud), organized into groups. They can be used to represent multiview scenes where data for multiple perspectives of the same scene can be stored, visualized, and queried in ways that respect the relationships between the slices of data. To create a grouped dataset, first import FiftyOne and define your groups. Then prepare the data by creating a dictionary of filepaths and their corresponding groups. Afterwards, add the samples to the dataset using the `add_samples` function. Finally, visualize the dataset with the `launch_app` function. Working with grouped datasets is similar to working with non-grouped datasets. You can access basic information about your dataset and change the active slice. To get the entire group for a sample, use the group ID and pull like normal. Iterating through your grouped dataset can be done in two ways: iterating through your active slice or iterating through each group using the `iter_groups` function. Creating views in your grouped dataset is also possible, allowing you to sort, slice, and search through your dataset. You can filter based on class, exclude individual groups from a view, create views of joined group slices, and perform aggregations. The possibilities are endless with FiftyOne's powerful grouped datasets feature.