Welcome to the OpenCV Python demos hub! 🚀 Here you'll find practical examples covering core computer vision tasks. Let's dive into some key areas:

📷 Image Processing Essentials

  • Filtering:

    • Gaussian blur: cv2.GaussianBlur()
    • Canny edge detection: cv2.Canny()
    • Sobel gradient calculation: cv2.Sobel()
      Image Processing

  • Thresholding:

    • Binary threshold: cv2.threshold()
    • Adaptive thresholding: cv2.adaptiveThreshold()
      Thresholding_Example

🎯 Object Detection Workflows

  • Face detection with Haar Cascades:
    face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
  • License plate recognition pipeline:
    1. Grayscale conversion
    2. Edge detection
    3. Contour analysis
    4. Text extraction
      License_Plate_Detection

📈 Machine Learning Applications

  • Train a classifier with:
    • Histogram of Oriented Gradients (HOG)
    • Support Vector Machine (SVM)
    • Random Forest algorithms
      Machine_Learning

For deeper insights, check our OpenCV Python tutorials section. Need help with specific tasks? The documentation index has comprehensive guides. 📘