Build 7 Real-Time Computer Vision Apps with YOLO26

About this course

Build 7 Real-World Computer Vision Projects with Ultralytics YOLO26 and PythonWant to move beyond basic object detection and build computer vision applications that solve real problems? In this hands-on course, you’ll use Ultralytics YOLO26 and Python to build seven complete projects, from counting people in a region to tracking workout reps with AI.Every lecture is project-based. You’ll write the code step by step, understand why it works, and finish with working applications you can add to your portfolio or adapt for your own work.

What you’ll build

Region-Based Object Counting: Count people inside custom regions of a video.

Intensity Heatmaps: Build a heatmap from scratch to see where objects and activity concentrate.

Distance Measurement: Measure the distance between detected objects in a video.

Vehicle Speed Estimation: Track vehicles and estimate their speed from scratch.

AI Workout Counter: Count push-ups, squats, leg presses, and leg extensions automatically.

Face Blurring with a Custom YOLO Model: Detect and blur faces in videos using a custom YOLO model and OpenCV.Traffic Analysis: Count cars, trucks, and buses entering and leaving the frame (IN/OUT counting).

What you’ll learn

How to use Ultralytics YOLO26 for detection and tracking in real projects

How to process video frame by frame with Python and OpenCVHow to define regions and lines for counting and analytics

How to turn raw detections into useful outputs like counts, speeds, distances, and heatmaps

How to apply a custom-trained YOLO model to a real task

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