Real-time face detection in Python: MediaPipe vs Haar cascade
Two ways to detect faces in a webcam feed with Python. See the code for both, then a straight comparison of speed, accuracy and when each one is the right choice.
Real-time vision on an ordinary webcam. Detection and tracking with OpenCV and MediaPipe, then projects that turn landmarks into something you can actually control.
Finding faces, hands and text in a frame — and choosing between the classical and modern approaches.
Two ways to detect faces in a webcam feed with Python. See the code for both, then a straight comparison of speed, accuracy and when each one is the right choice.
Hold up three fingers and Python says three. Learn the landmark logic behind finger counting, including the thumb rule that trips everyone up.
Tesseract plus a few lines of OpenCV preprocessing turns blurry photos into clean text. Learn the cleanup steps that take accuracy from unusable to reliable.
End-to-end builds that map body and hand landmarks onto real controls: a mouse, a volume dial, a rep counter.
Build a gesture volume controller with OpenCV and MediaPipe. Pinch your thumb and index finger together to turn the sound down, spread them apart to turn it up.
Use MediaPipe Pose to measure your elbow angle and count push-up reps automatically. The same state machine works for squats, curls and any repeated movement.
Learn how to build a virtual mouse in Python using OpenCV and MediaPipe hand tracking. Move the cursor with your index finger and click with a pinch — beginner-friendly step-by-step tutorial.
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