I want to address three things about our YOLO Kickstarter I know you are thinking about.
 

"I can just prompt AI to write the YOLO code."

You can. AI is strong at syntax and scaffolding.
What it cannot do is understand your physical context.

It does not know your camera's focal length, your edge device's thermal limits, or the dataset biases that cause a model to fail when the lighting shifts mid-shift.

An AI-generated YOLO script gets you to a demo.
Understanding the pipeline gets you to a deployed product that does not need babysitting.

The engineers at $165k are not using AI less.
They are using it better, because they understand the output well enough to know when it is wrong.

"560 pages is too much. I do not have the time."

The eBook is a reference, not a novel.
Most engineers use it the way they use documentation: go to the section relevant to the current project, reference others as needed.

The Quick-Start Path gets you to a running v12 project in under an hour.
The video course covers the same content in watch-and-run format.
The code runs without modification.

As one of our readers put it:

"The code provided just works. And if you need help, the support is quick and helpful."

"Why does this cost more than a cheap online course?"

A cheap course teaches you detect.py.
This teaches you the full pipeline.
The salary gap between the junior and senior roles this course separates is $30,000 to $50,000 per year.
This course costs less than two days of that difference.

PyImageSearch has published free tutorials every single week for over 10 years.
We have run 8 Kickstarter campaigns and raised over $850,000 in education funding.
Every campaign delivered.

Back the YOLO Kickstarter

Talk soon,
The PyImageSearch Team

P.S. Questions before backing? Reply here and we will get you an answer.

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