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OpenCV C++ Lecture Materials

OpenCV C++ Lecture Materials

OpenCV Lecture class materials
pdf, source code and images

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Lecture is here: https://www.marearts.com/blogs/aws-lambda-lecture

OpenCV Complete Course

Section 1: OpenCV Build Setup 7 videos · 1 hour 2 minutes

  1. Step 1: Preparation (8:04)
  2. Step 2: CMake Configuration and Build (14:02)
  3. Step 3: Build, Settings, and Running Examples (12:10)
  4. OpenCV + C++ Easy Installation (Part 1/2) (10:12)
  5. OpenCV + C++ Easy Installation (Part 2/2) (6:51)
  6. OpenCV + Python Easy Installation (Part 1/2) (4:53)
  7. OpenCV + Python Easy Installation (Part 2/2) (6:14)

Section 2: OpenCV Basics - Introduction 7 videos · 1 hour 39 minutes

  1. Computer Vision & OpenCV Introduction (13:44)
  2. Getting Started with OpenCV: Download & Setup (22:04)
  3. Building OpenCV: CMake and Webcam Example (16:13)
  4. Understanding the Mat Class (15:26)
  5. Mat Basic Operations (+, -, /, *) (12:06)
  6. Basic Image Processing: Load and Display (6:33)
  7. Accessing Pixel Data (12:58)

Section 3: Working with Mat 9 videos · 2 hours 2 minutes

  1. Loading and Displaying Images and Videos (14:45)
  2. Mat Basic Functions (copy, copyTo, clone, range, region) (14:42)
  3. RGB Pixel Structure in Images (10:49)
  4. Pixel Access Using Data and At Operator (13:02)
  5. Pixel Access Using Ptr and Iterator (8:20)
  6. Saving Mat to Image Files (16:17)
  7. Linear Algebra Operations (solver, eigenvalues, SVD) (13:16)
  8. Linear Algebra (inner/cross product, inverse, trace, determinant) (13:19)
  9. GPU Mat Example (17:33)

Section 4: Drawing, Mouse, and Controls 6 videos · 1 hour 14 minutes

Section 5: Point Processing 8 videos · 1 hour 39 minutes

Section 6: Advanced Point Processing 6 videos · 54 minutes

Section 7: Histogram 6 videos · 54 minutes

Section 8: Project #1 - Intruder Detection with Google Drive Upload 5 videos · 39 minutes

Section 9: Bonus Content 3 videos · 1 hour 2 minutes

  1. Keras + CNN + MNIST with Colab (18:46)
  2. Deep Learning Model Optimization for IoT (Raspberry Pi, Mobile, AWS Lambda) (11:30)
  3. Model Performance Evaluation (Accuracy, Recall, Precision, F1, ROC, AUC) Explained (31:59)
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