Prepare Your Dataset

Prepare Your Data · 0 of 3

Create a Dataset

Upload Images and Videos

Annotate Your Data

Create a Dataset

Before You Start

20 or more images for your use case
Annotations for those images, or a plan to create them in Vi

By the end of this guide

Prepare a dataset with uploaded images and annotations ready for a training run.

Datature Vi organizes training data as datasets. Each dataset holds your images, their annotations, and metadata about the task type. You need to create the dataset project first, then fill it.

This stage has three steps. Work through them in order.

Create a dataset

Click Dataset in the left sidebar, then click Create Dataset. Choose your task type: Phrase Grounding to locate objects with bounding boxes, Visual Question Answering to answer questions about images, or Freeform Text for open-ended descriptions and structured data extraction (JSON reports, captions, inspection checklists). Select Image as the data type, name your dataset, then pick storage: Multi-Region is the default for performance; choose a single region if policy requires data residency in one geography (Security and compliance). Click Create Dataset.

What each step covers

Follow the linked guides for the full walkthrough of each step.

Create a dataset

Choose a task type (phrase grounding, visual question answering, or freeform text), select Image as the data type, name your dataset, and pick storage localization.

Upload images

Drag and drop images into the Explorer tab, or use the Vi SDK for larger batches.

Add annotations

Import existing annotation files or use the built-in annotator to label images. IntelliScribe can auto-generate captions to speed things up.

Next steps

Next: Train A Model

Create a training project, configure a workflow, and start your first training run.

Step 1: Create A Dataset

Choose your task type and configure dataset settings. This is the first step in this stage.