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OpenCV C++ Lecture Materials

OpenCV C++ Lecture Materials

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📖 Full lecture available here: marearts.com/blogs/aws-lambda-lecture


📦 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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