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Raspberry Pi · Intermediate · Stufe 22 / 40

Computer Vision with OpenCV

Process live camera frames to detect, measure and track objects in real time.

Intermediate freischalten · CHF 19.90 Stufen 14–26, einmalig, kein Abo

10 Lektionen in dieser Stufe

  1. Installing OpenCV and Understanding Image Arrays
    Set up OpenCV in a venv and handle channel order and data types. · Lab: Display a picamera2 frame with OpenCV and fix the swapped red and blue channels.
  2. Colour Spaces and HSV Thresholding
    Isolate objects by colour under varying brightness. · Lab: Build trackbars to tune an HSV mask for one coloured object.
  3. Blurring, Edges and Morphology
    Clean up images and extract outlines. · Lab: Apply Gaussian blur, Canny edges and open and close operations to a noisy mask.
  4. Finding and Measuring Contours
    Detect shapes and compute area, centre and bounding boxes. · Lab: Count objects on a tray and draw each one's area and centroid.
  5. Motion Detection by Background Subtraction
    Detect change while ignoring noise and slow lighting drift. · Lab: Trigger on movement larger than a set area and ignore a swaying curtain zone.
  6. Tracking a Coloured Object in Real Time
    Follow a target frame to frame and output its position. · Lab: Track a ball and drive the Level 14 pan-tilt head to keep it centred.
  7. Calibrating a Camera and Removing Lens Distortion
    Compute intrinsic parameters and undistort images. · Lab: Calibrate with twenty chessboard images and straighten a wide-angle frame.
  8. Pose from ArUco Markers
    Detect fiducial markers and estimate distance and orientation. · Lab: Print markers and measure the distance to one within a few millimetres.
  9. Reading QR Codes and Barcodes
    Decode symbols from live frames and act on their content. · Lab: Scan a QR code that selects which inspection recipe to run.
  10. Profiling a Vision Loop for Frame Rate
    Find the slow stage and speed it up with resolution, regions and threads. · Lab: Time each stage, then double the frame rate using a lores stream and a capture thread.

Abschlussprojekt

A vision inspection station that counts and measures parts on a tray in millimetres, flags rejects and reads a QR job label.

Teile für diese Stufe

  • 1 × Raspberry Pi 5 set from Level 1 (Pi 4 also works)
  • 1 × Camera module with autofocus
  • 1 × Camera mount or tripod
  • 1 × Printed calibration chessboard and ArUco marker sheet
  • 1 × LED light panel or ring light
  • 1 × Assorted coloured objects and small parts tray

In jeder Lektion legst du die passenden Teile direkt in den Warenkorb. Raspberry Pi →

Voraussetzung: Level 21: picamera2 configurations and frames as NumPy arrays.

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