Workspaces, Projects, and Models

Learn how Workspaces, Projects, Versions, and Models structure your computer vision work in Roboflow

Everything in Roboflow follows this structure:

Workspace → Projects → Dataset Versions → Models → Workflows → Deployments

Workspaces

A Workspace is the top-level container.

• It's where you and your team collaborate.

• All Projects and Workflows live inside a Workspace

• Billing and subscription plans are managed at the Workspace level

Think of it like a company folder that holds all your computer vision work.

Projects

A Project lives inside a Workspace. Each Project is built around a computer vision dataset. This is where you manage:

• Images

• Annotations

• Dataset updates over time

When you create a Project, you have to choose the Project type - one of the computer vision task type:

• Object detection

• Classification

• Instance segmentation

• Keypoint detection

• Semantic segmentation

• Multimodal

This determines how your data is structured and which model architectures you can train.

Dataset Versions

A Dataset Version is a snapshot of your dataset at a specific moment in time.

• You create a Version from the current state of your Project

• Once created, it does not change

• Any future edits to images or annotations will not affect existing Versions

Which ensures reproducibility, clear tracking, and helps with model comparison.

Models

Models are trained using Dataset Versions.

• You select a specific Dataset Version which will be used to train a model

• That model is permanently linked to that version

• Available model architectures for training will depend on your Project type

You can also upload trained models to Roboflow.

After you have a model, create a workflow, or go right to deploy!