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Computer Vision Tutorial

Learn how computers see: pixels and colour, filters, edges and contours in NumPy, then OpenCV, CNNs, detection, segmentation and a document scanner project.

28 free lessons Intermediate to Advanced Covers NumPy and matplotlib in the browser; OpenCV 5.0 and PyTorch 2.15 as plain code

Start the first lesson

Getting Started Intermediate

  1. 1Computer Vision Introduction
  2. 2Pixels, Channels & Colour Spaces
  3. 3Images as NumPy Arrays
  4. 4Reading & Writing Images with OpenCV

Basic Image Operations Intermediate

  1. 5Resizing, Cropping & Rotating
  2. 6Brightness, Contrast & Gamma
  3. 7Histograms & Equalisation
  4. 8Thresholding

Filters & Features Intermediate

  1. 9Convolution Step by Step
  2. 10Blurring, Sharpening & Noise
  3. 11Edge Detection: Sobel & Canny
  4. 12Morphology: Erode, Dilate, Open & Close
  5. 13Contours & Shapes
  6. 14Corners & Features: Harris & ORB
  7. 15Affine & Perspective Transforms

Learning from Images Advanced

  1. 16Classifying Images with Classical ML
  2. 17Image Classification with CNNs
  3. 18Transfer Learning for Vision
  4. 19Data Augmentation
  5. 20Evaluating Vision Models

Detection & Segmentation Advanced

  1. 21Object Detection: Boxes, IoU & NMS
  2. 22Detection Models: YOLO-Style & Two-Stage
  3. 23Image Segmentation

Vision in the Real World Advanced

  1. 24Face Detection & Privacy in India
  2. 25OCR for Indian Documents
  3. 26Video Processing Basics
  4. 27Deploying Vision Models
  5. 28Project: Document Scanner

Learn Computer Vision with a mentor

Free lessons get you started. Our Data Science & Machine Learning training adds real projects and code reviews from working developers.

  • Project-based learning
  • Mentor code reviews
  • Free counselling call
Get course details +91 90532 10052