In this video, you’ll learn how to use YOLO-World, a cutting-edge zero-shot object detection model. We'll cover its speed, compare it to other models, and run a live code demo for image AND video analysis.

Chapters:

- 00:00 Intro
- 00:42 YOLO-World vs. Traditional Object Detectors: Speed and Accuracy
- 02:26 YOLO-World Architecture - prompt-then-detect
- 03:59 Setting Up and Running YOLO-World
- 05:33 Prompt Engineering and Detections Post-Processing
- 09:20 Video Processing with YOLO-World
- 13:16 Important Considerations for Using YOLO-World
- 15:08 Beyond the Basics: Advanced use cases and future potential
- 16:37 Outro

Resources:

- Roboflow: https://roboflow.com

- 🔴 Community Session February 27 2024 at 08:00 AM PST / 11:00 AM EST / 05:00 PM CET: https://www.youtube.com/live/lF1BtQL1...

- ⭐ Inference GitHub: https://github.com/roboflow/inference
- ⭐ Supervision GitHub: https://github.com/roboflow/supervision

- ⭐ YOLO-World GitHub: https://github.com/AILab-CVC/YOLO-World
- 🗞 YOLO-World arXiv paper: https://arxiv.org/abs/2401.17270

- 🗞 YOLO-World blog post: https://blog.roboflow.com/what-is-yol...
- 📓 YOLO-World notebook: https://supervision.roboflow.com/deve...
- 🤗 YOLO-World + EfficientSAM HF Space: https://huggingface.co/spaces/Skalski...

- 🗞 GroundingDINO blog post: https://blog.roboflow.com/grounding-d...
- 🗞 Non-Max Suppression blog post: https://blog.roboflow.com/how-to-code...

Stay updated with the projects I'm working on at https://github.com/roboflow and https://github.com/SkalskiP! ⭐