There is a $30,000 to $50,000 salary gap between computer vision engineers who can run a YOLO model and those who can actually ship one.

Tomorrow morning at 10 AM EST, we open the Kickstarter for the course designed to close that gap.

YOLO Object Detection Mastery, 2nd Edition.

Here is what it contains:

• Nearly 600-page eBook — 20 chapters, covering every YOLO generation from v1 through v12. Built as both a curriculum and a long-term reference.
• 11 video course modules — 25 tutorials with narrated code walkthroughs. Watch the implementation before you run it.
• Google Colab & Jupyter Notebooks — Every chapter ships with production-ready source code delivered as ready-to-run notebooks. Zero setup. The actual code you would deploy in a real project.
• 9 production projects — real-time object detection, multi-object tracking, instance segmentation, pose estimation, thermal imaging detection, edge deployment (Raspberry Pi + Jetson), browser-based detection, pothole severity classification, and custom dataset fine-tuning.

This is not another tutorial that gets you to a demo and calls it done.

YOLOv12 introduced attention-based detection — the same mechanism that made transformers dominate NLP, now applied to real-time vision. Faster than v8. More accurate than v9. And the engineers who understand the full deployment pipeline are the ones companies compete to hire at $136,000 to $175,000.

The campaign opens Friday, March 13 at 10 AM EST so click below to be notified when it goes live to snag the early-bird discounts up to 60% Off.

Watch YOLO Kickstarter Now

Talk soon,
The PyImageSearch Team

P.S. Forward this to anyone on your team who works in computer vision. Campaign pricing is only available through March 25.