FiftyOne Dataset Basics¶
Dataset is the understood format that can be visualized in the
What is a FiftyOne Dataset?¶
Dataset class allows you to easily
load, modify and
visualize your data along with any related labels
(classification, detection, segmentation, etc).
It provides a way to easily load images, annotations, and model predictions
into a format that can be visualized in the FiftyOne App.
If you have your own collection of data, loading it as a
Dataset will allow
you to easily search and sort your samples.
You can use FiftyOne to identify unique samples as well as possible mistakes in
If you are training a model, the output predictions and logits can be loaded
The FiftyOne App makes it easy to visually debug what
your model has learned, even for complex label types like detection and
With this knowledge, you can update your
Dataset to include more
representative samples and samples that your model found difficult into your
Checkout out our dataset loading guide to load your dataset into FiftyOne.
Dataset is composed of multiple
Sample objects which contain
Field attributes, all of which can
be dynamically created, modified and deleted.
FiftyOne uses a lightweight non-relational database to store a
usage is easy on your computer’s memory and scalable.
Dataset should be thought of as an unordered collection. Samples can be
added to it and they can be accessed by key. However, slicing and sorting
Dataset is done through the use of a
for an ordered look into the
Dataset or a subset of the
Dataset along user
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import fiftyone as fo sample = fo.Sample(filepath="/path/to/image.png")
Fields can be dynamically created, modified, and deleted. When a new
is assigned for a
Sample in a
Dataset, it is automatically added to the
dataset’s schema and thus accessible on each other
Sample in the
When unset, the default
Field value will be