Udemy-PracticalComputerVisionMastery20+Python&AIProjects2025-6

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1 Introduction

2 Introduction to Your Instructor and Course Overview

3 What is AI and How It Has Evolved

4 Introduction to Computer Vision and Its Applications

5 Installing Python
6 VS Code Setup for Python Development

7 OpenCv Fundamentals Overview
8 Reading and Writing Images
9 Color Space Conversion
10 Displaying Images and Videos
11 Image Resizing Cropping and Rotation
12 Drawing Functions
13 Image Thresholding
14 Morphological Operations
15 Contour Detection
16 Mask Image Generation
17 Background Subtraction
18 Image Bitwise Operations
19 Histogram Equalization Gamma Correction
20 Smoothing Filters
21 Sharpening Filters
22 Edge Detection Sobel
23 Contrast Adjustment

24 Computer Vision Advanced Introduction Video
25 Edge Detection Canny
26 Corner Detection
27 Keypoint Detection Matching
28 Texture Analysis
29 Optical Flow and Motion Analysis
30 Object Tracking
31 Image Segmentation
32 Image object detection
33 Live streaming
34 Tesseract OCR Engine

35 Course Overview and Features
36 Installing Required Packages Dilib OpenCV etc
37 Face Enrollment
38 Extracting Face Embeddings and Identifying Landmark
39 Training the Facial Recognition Model
40 RealTime Face Recognition and Attendance
41 Building the Attendance Management GUI

42 Introduction of the Driver Drowsiness Detection System
43 Driver Drowsiness Detection Project Overview
44 Understanding Key Packages for Driver Drowsiness Detection
45 Implementing Drowsiness Detection Logic Using EAR and MAR
46 Integrating Drowsiness Detection with Tkinter GUI
47 RealTime Driver Drowsiness Detection with Live Video Streaming
48 RealTime Model Inference for Driver Drowsiness Detection

49 Introduction of the Object Detection using yolov7
50 Object Detection Project Overview
51 Understanding Key Packages for Object Detection
52 Understanding the YOLOv7tiny Model Weights
53 RealTime Object Detection with YOLOv7tiny
54 Building a Tkinter GUI for RealTime Object Detection
55 Executing RealTime Model Inference for Object Detection

56 Introduction of the Weapon Detection using YOLOv7
57 Weapon Detection Project Overview
58 Setup in Google Colab for Weapon Detection Model Training
59 Mounting Google Drive on Google Colab
60 Utilizing Sohas Weapon Detection Dataset for Weapon Detection
61 Cloning YOLOv7 Repository and Installing Required Packages
62 Visualizing the Weapon Detection Dataset
63 Splitting the Weapon Detection Dataset
64 Detailed Walkthrough of YOLOv7 Code for Weapon Detection
65 Training the YOLOv7 Model for Weapon Detection
66 Model Inference for Weapon Detection

67 Intro to RealTime EntryExit Tracking for Smart Occupancy Management
68 Understanding the YOLOv8 Algorithm
69 Setting Up and Exploring Essential Packages
70 Key Variables and Their Role in YOLOv8
71 People Counting Logic and Function Implementation
72 Accessing and Using Line Coordinates for Tracking
73 Implementing People Counting with YOLOv8 Model Inference
74 Tkinter Implementation for RealTime People Counting
75 Package Installation for People Counting System
76 Drawing Lines on Images for People Counting
77 Getting Line Coordinates Using Roboflow for People Counting
78 People In and Out Counting Code Execution

79 Introduction of the Facial Emotion Detection
80 Facial Emotion Detection Project Overview
81 Set up Google Colab
82 Facial Emotion Detection Dataset Download
83 Dataset Visualization
84 Pretrained yolov9 model weight file download
85 yolov9 model info
86 yolov9 model code explanation
87 yolov9 model training
88 Model Inference Explanation
89 Code Execution

90 Introduction to RealTime License Plate Detection and Recognition
91 License Plate Detection and Recognition System Overview
92 Managing Folders and Files of the Project
93 Setting Up and Exploring Essential Packages
94 Setting Up API Access for Vehicle Recognition
95 Key Variables and Their Role in License Plate Detection and Recognition
96 Implementing License Plate Detection and Recognition
97 VisionLanguage Model Integration
98 Tkinter Implementation for RealTime License Plate Detection and Recognition
99 Package Installation for License Plate Detection and Recognition
100 Getting Polygon Coordinates Using Roboflow for License Plate Detection
101 Obtaining the NVIDIA NIM API Key for Vehicle License Plate Detection
102 Vehicle License Plate Detection and Tracking Code Execution

103 Introduction of theTraffic Sign Detection And Recognition System
104 Google Colab Setup
105 Packages Installation
106 Dataset Preparation
107 Implementing Utility Functions for Traffic Sign Detection
108 Implementing Loss Function for Traffic Sign Detection
109 EfficientNetB0 Model Implementation Info
110 Model Training configuration
111 Training the EfficientNetB0 Model
112 Model Inference

113 Launching VS Code from the Command Line
114 Managing Folders and Files of the Project
115 Understanding and Setting Up Required Packages
116 Accessing and Using Polygon Coordinates for Tracking
117 Key Variables and Their Role in YOLOv8
118 Model Inference Code Explanation for Intrusion Detection
119 Tkinter Implementation for RealTime Intrusion Detection
120 Getting Polygon Coordinates Using Roboflow for Intrusion Detection
121 Intrusion Detection Code Execution

122 Introduction of the PPE Detection Detection System
123 PPE Detection Project Overview
124 File Uploaded on Google Colab
125 Dataset Visualization
126 PPE Model Information
127 PPE Code Execution
128 VS Code Open
129 Packages and Module Import
130 NVIDIA Nim Information
131 API Information
132 File Format
133 Predict API
134 Get API
135 Code Execution

136 Introduction to Age and Gender Detection
137 Age and Gender Detection Project Overview
138 Packages Information for Age and Gender Detection
139 Variable Initialization and System Configuration
140 Folder Creation
141 Model Inference
142 TKinter Implementation
143 Package Installation
144 Code Execution

145 Intro to AIPowered Accident Detection RealTime Monitoring Alert System
146 AI Accident Detection RealTime Monitoring Alert System Project Overview
147 Configuring the environment on Google Colab
148 Setting Up and Exploring Essential Packages
149 Dataset Acquisition Downloading Understanding
150 Dataset Visualization Analysis
151 Dataset Preprocessing Normalization Resizing
152 Label Encoding Data Preparation
153 Training Validation Data Visualization
154 CNN Model Implementation Training
155 Downloading and Saving Trained Model Weights
156 Understanding MQTT Protocol Package Requirements
157 Model Inference Code Walkthrough
158 Final Code Execution Live Demonstration

159 Introduction of Smart Vehicle Speed Tracking System
160 Vehicle Detection and Speed Tracking System Overview
161 Setting Up and Exploring Essential Packages
162 Calibration for RealWorld Measurements
163 Implementing Vehicle Speed Tracking with YOLOv8 Model Inference
164 Vehicle Speed Calculation Logic and Function Implementation
165 Tkinter Implementation for RealTime Vehicle Speed Tracking
166 Vehicle Speed Tracking Code Execution

167 Introduction to RealTime Vehicle Tracking for Effective Parking Management
168 Managing Folders and Files of the Project
169 Vehicle Detection and Parking Slot Tracking System Overview
170 Setting Up and Exploring Essential Packages
171 Implementing Vehicle Parking Management with Flask
172 Building the Backend for Vehicle Parking Management with Flask
173 Implementing Vehicle Parking Detection and Occupancy Tracking
174 Package Installation for Vehicle Parking Management system
175 Get Polygon Coordinates with Roboflow to Calculate Available Parking Spaces
176 Vehicle Parking Space Detection and Occupancy Tracking Code Execution

177 Introduction to Face Mask Detection and Recognition
178 Face Mask Detection System Project Overview
179 Google Drive Mount
180 Face Mask Detection Dataset Download
181 Dataset Visualization
182 Ultralytics Installation Setting Up YOLOv11 for Mask Detection
183 YOLOv11 Model Training for Mask Detection
184 Packages Explanation
185 Model Inference Code Explanation
186 Tkinter Implementation
187 Code Execution

188 Hand Gesture Detection and Recognition Overview
189 Setting Up and Exploring Essential Packages
190 Key Variables and Their Role in Hand Gesture Recognition
191 Annotating Frames with Detected Gestures and Landmarks
192 RealTime Gesture Recognition and Frame Processing
193 Integrating RealTime Gesture Recognition with Tkinter GUI
194 Tkinter Implementation for RealTime Hand Gesture Recognition
195 Package Installation for Hand Gesture Recognition System
196 Hand Gesture Recognition Code Execution

197 Intro to RealTime Vehicle Traffic Monitoring for Efficient Traffic Management
198 Vehicle Detection and Traffic Monitoring System Overview
199 Setting Up and Exploring Essential Packages
200 User Input and Video File Selection
201 Implementing Vehicle Monitoring with YOLOv8 Model Inference
202 Tkinter Implementation for RealTime Vehicle Monitoring
203 Vehicle Traffic Monitoring Code Execution

204 Introduction of the Human Fitness Tracking System
205 Project Overview Purpose
206 Packages Overview MediaPipe Initialization
207 Calculating Angles in Pose Estimation
208 Logic Behind Repetition Counting
209 Tkinter Log Window Variable Initialization
210 Model Inference and Code Explanation
211 Tkinter Implementation for UI
212 Package Installation Guide
213 Code Execution Workflow

214 Introduction to AIPowered Fall Down Detection Alert System
215 Fall Down Detection System Project Overview
216 Dependency Package Overview
217 Installation MQTT Setup
218 User Registration Login API
219 MQTT Flask Integration
220 Fall Detection Logic
221 Prediction API Workflow
222 Code Execution Testing

223 Introduction to Animal Detection System
224 Animal Detection System Project Overview
225 Setting Up Google Colab and Mounting Google Drive
226 Dataset Download and Exploration
227 Dataset Preprocessing and Augmentation
228 Splitting the Dataset for Training Validation and Testing
229 Visualizing the Animal Dataset and Augmented Data
230 EfficientNetB0 Model Implementation
231 Training the EfficientNetB0 Model and Monitoring Progress
232 Model Inference using Flask and Ngrok
233 Code Execution

234 Introduction of the Driver Distraction System
235 Driver Distraction Project Overview
236 Google Colab Setup Google Drive Mount
237 Dataset Download Exploration
238 Data Visualization Insights
239 Data Preprocessing Augmentation
240 ResNet50 Model Architecture Implementation
241 Model Training Optimization
242 Model Inference Code Explanation
243 Code Execution

244 Course WrapUp

Udemy - Practical Computer Vision Mastery 20+ Python & AI Projects 2025-6

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Udemy - Practical Computer Vision Mastery 20+ Python & AI Projects 2025-6

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