Learn how to programmatically add images and annotations to datasets using the Roboflow Upload API in Python. Explore the process of setting up a project, obtaining an API key, and navigating the API documentation. Create requests for uploading single images and annotations, then scale up to uploading entire folders of images and annotations. Discover how to incorporate active learning into projects by regularly sampling from production conditions to continuously improve datasets. Follow along with a provided Jupyter notebook and access comprehensive documentation for reference. By the end of this 21-minute tutorial, gain the skills to efficiently manage and expand datasets for computer vision projects using the Roboflow Upload API.
Overview
Syllabus
00:00 - Introduction
- Setting up project and getting API key
- Upload API documentation walkthrough
- Creating a request to upload a single image
- Creating a request for a single annotation
- Uploading a folder of images via API
- Uploading a folder of images and annotations via API
- Viewing the results
Taught by
Roboflow
