Darwin Fundamentals: Overview

Countless creators use Darwin to automate workflows, manage sprawling datasets, and create superior AI models. Here, we provide a deep dive into the fundamentals of Darwin, so you can master the platform with best practices in mind.

16:35

Annotations - Getting Started

We dive into image annotation and explain how you can get the most out of these impressive features.

5:56

Auto-Annotate Tips & Tricks

Wield Auto-Annotate like the experts, with tips and tricks to accelerate your use of the tool.

3:49

Auto-Annotate Tool

How does the Auto-Annotate tool work? We tackle accurate polygon and pixel-wise annotation masks.

0:52

Comment Tool

We explain the Comment Tool, outline how to leave comments on images - and how it benefits you.

2:28

Exports

We dive into exports and explain how to export in JSON, COCO, VOC and more, with Darwin.py.

1:37

Folders

We explain how to make data easily searchable, by organizing your ML datasets with folders and tags.

1:31

Image Statuses

Annotate, Review, Complete - how do statuses in V7’s Darwin work? We explore Images Statuses.

4:02

Instance Tracking IDs

We explore Instance Tracking IDs, explain how to use them, and underline why they’re so important.

4:44

Skeleton Keypoints

We explain how you can label and interpolate keypoint skeletons and custom polygons.

2:10

User Roles

How do you add and remove users on V7’s Darwin? We explore the what, how, and why of user roles.

6:17

Video Annotation

How does Video Annotation work? We explain how to interpolate annotations in video.