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Practical Computer Vision Mastery: 20+ Python & AI Projects [6/2025, ENG]

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Practical Computer Vision Mastery: 20+ Python & AI Projects [6/2025, ENG] (Size: 12.63 GB)
  1 - Introduction
  1 - Introduction.mkv 63.09 MB
  1 - Introduction.srt 2.22 KB
  10 - Project 3 Object Detection Using Yolov7 with Python Computer Vision
  49 - Introduction of the Object Detection using yolov7.mkv 6.24 MB
  49 - Introduction of the Object Detection using yolov7.srt 397 B
  50 - 3.Object-Detection.zip 75.39 MB
  50 - Object Detection Project Overview.mkv 3.43 MB
  50 - Object Detection Project Overview.srt 876 B
  51 - Understanding Key Packages for Object Detection.mkv 7.28 MB
  51 - Understanding Key Packages for Object Detection.srt 1.37 KB
  52 - Understanding the YOLOv7tiny Model Weights.mkv 3.8 MB
  52 - Understanding the YOLOv7tiny Model Weights.srt 718 B
  53 - RealTime Object Detection with YOLOv7tiny.mkv 24.58 MB
  53 - RealTime Object Detection with YOLOv7tiny.srt 3.2 KB
  54 - Building a Tkinter GUI for RealTime Object Detection.mkv 16.32 MB
  54 - Building a Tkinter GUI for RealTime Object Detection.srt 2.1 KB
  55 - Executing RealTime Model Inference for Object Detection.mkv 31.15 MB
  55 - Executing RealTime Model Inference for Object Detection.srt 1.99 KB
  11 - Project 4 AIPowered Weapon Detection for Enhanced Security with Python CV
  56 - Introduction of the Weapon Detection using YOLOv7.mkv 10.5 MB
  56 - Introduction of the Weapon Detection using YOLOv7.srt 2.06 KB
  57 - 4.wepon-detection.zip 527.47 MB
  57 - Weapon Detection Project Overview.mkv 6.99 MB
  57 - Weapon Detection Project Overview.srt 1.88 KB
  58 - Setup in Google Colab for Weapon Detection Model Training.mkv 8.05 MB
  58 - Setup in Google Colab for Weapon Detection Model Training.srt 817 B
  59 - Mounting Google Drive on Google Colab.mkv 4.73 MB
  59 - Mounting Google Drive on Google Colab.srt 471 B
  60 - Utilizing Sohas Weapon Detection Dataset for Weapon Detection.mkv 18.6 MB
  60 - Utilizing Sohas Weapon Detection Dataset for Weapon Detection.srt 1.63 KB
  61 - Cloning YOLOv7 Repository and Installing Required Packages.mkv 9.55 MB
  61 - Cloning YOLOv7 Repository and Installing Required Packages.srt 968 B
  62 - Visualizing the Weapon Detection Dataset.mkv 8.85 MB
  62 - Visualizing the Weapon Detection Dataset.srt 567 B
  63 - Splitting the Weapon Detection Dataset.mkv 22.66 MB
  63 - Splitting the Weapon Detection Dataset.srt 1.83 KB
  64 - Detailed Walkthrough of YOLOv7 Code for Weapon Detection.mkv 252.47 MB
  64 - Detailed Walkthrough of YOLOv7 Code for Weapon Detection.srt 18.5 KB
  65 - Training the YOLOv7 Model for Weapon Detection.mkv 49.05 MB
  65 - Training the YOLOv7 Model for Weapon Detection.srt 2.5 KB
  66 - Model Inference for Weapon Detection.mkv 60.36 MB
  66 - Model Inference for Weapon Detection.srt 6.6 KB
  12 - Project 5 RealTime EntryExit Occupancy Tracker using Python OpenCV
  67 - Intro to RealTime EntryExit Tracking for Smart Occupancy Management.mkv 11.59 MB
  67 - Intro to RealTime EntryExit Tracking for Smart Occupancy Management.srt 2.11 KB
  68 - 5.People-Counting-System.zip 25.73 MB
  68 - Understanding the YOLOv8 Algorithm.mkv 6.22 MB
  68 - Understanding the YOLOv8 Algorithm.srt 1.33 KB
  69 - Setting Up and Exploring Essential Packages.mkv 3.04 MB
  69 - Setting Up and Exploring Essential Packages.srt 576 B
  70 - Key Variables and Their Role in YOLOv8.mkv 6.21 MB
  70 - Key Variables and Their Role in YOLOv8.srt 1.33 KB
  71 - People Counting Logic and Function Implementation.mkv 2.83 MB
  71 - People Counting Logic and Function Implementation.srt 679 B
  72 - Accessing and Using Line Coordinates for Tracking.mkv 3.87 MB
  72 - Accessing and Using Line Coordinates for Tracking.srt 931 B
  73 - Implementing People Counting with YOLOv8 Model Inference.mkv 48.72 MB
  73 - Implementing People Counting with YOLOv8 Model Inference.srt 5.83 KB
  74 - Tkinter Implementation for RealTime People Counting.mkv 11.41 MB
  74 - Tkinter Implementation for RealTime People Counting.srt 1.65 KB
  75 - Package Installation for People Counting System.mkv 5.82 MB
  75 - Package Installation for People Counting System.srt 574 B
  76 - Drawing Lines on Images for People Counting.mkv 12.51 MB
  76 - Drawing Lines on Images for People Counting.srt 1.73 KB
  77 - Getting Line Coordinates Using Roboflow for People Counting.mkv 9.65 MB
  77 - Getting Line Coordinates Using Roboflow for People Counting.srt 1.24 KB
  78 - People In and Out Counting Code Execution.mkv 135.61 MB
  78 - People In and Out Counting Code Execution.srt 5.42 KB
  13 - Project 6 Facial Emotion Detection Recognition using Python OpenCV
  79 - Introduction of the Facial Emotion Detection.mkv 48.23 MB
  79 - Introduction of the Facial Emotion Detection.srt 3.37 KB
  80 - 6.Facial-Emotion-Detection.zip 251.31 MB
  80 - Facial Emotion Detection Project Overview.mkv 2.03 MB
  80 - Facial Emotion Detection Project Overview.srt 614 B
  81 - Set up Google Colab.mkv 20.5 MB
  81 - Set up Google Colab.srt 704 B
  82 - Facial Emotion Detection Dataset Download.mkv 21.72 MB
  82 - Facial Emotion Detection Dataset Download.srt 1.23 KB
  83 - Dataset Visualization.mkv 43.35 MB
  83 - Dataset Visualization.srt 2.11 KB
  84 - Pretrained yolov9 model weight file download.mkv 19.34 MB
  84 - Pretrained yolov9 model weight file download.srt 1.08 KB
  85 - yolov9 model info.mkv 18.7 MB
  85 - yolov9 model info.srt 2.86 KB
  86 - yolov9 model code explanation.mkv 193.73 MB
  86 - yolov9 model code explanation.srt 12.89 KB
  87 - yolov9 model training.mkv 59.7 MB
  87 - yolov9 model training.srt 4.31 KB
  88 - Model Inference Explanation.mkv 84.43 MB
  88 - Model Inference Explanation.srt 13.6 KB
  89 - Code Execution.mkv 21.51 MB
  89 - Code Execution.srt 3.54 KB
  14 - Project 7 LLMPowered License Plate Detection Recognition with Python CV
  100 - Getting Polygon Coordinates Using Roboflow for License Plate Detection.mkv 51.2 MB
  100 - Getting Polygon Coordinates Using Roboflow for License Plate Detection.srt 1.69 KB
  101 - Obtaining the NVIDIA NIM API Key for Vehicle License Plate Detection.mkv 11.14 MB
  101 - Obtaining the NVIDIA NIM API Key for Vehicle License Plate Detection.srt 391 B
  102 - Vehicle License Plate Detection and Tracking Code Execution.mkv 41.85 MB
  102 - Vehicle License Plate Detection and Tracking Code Execution.srt 2.6 KB
  90 - Introduction to RealTime License Plate Detection and Recognition.mkv 20.73 MB
  90 - Introduction to RealTime License Plate Detection and Recognition.srt 1.38 KB
  91 - 7.License-Plate-Detection-and-Recognition.zip 69.38 MB
  91 - License Plate Detection and Recognition System Overview.mkv 9.63 MB
  91 - License Plate Detection and Recognition System Overview.srt 2.09 KB
  92 - Managing Folders and Files of the Project.mkv 10.98 MB
  92 - Managing Folders and Files of the Project.srt 2.12 KB
  93 - Setting Up and Exploring Essential Packages.mkv 14.41 MB
  93 - Setting Up and Exploring Essential Packages.srt 2.93 KB
  94 - Setting Up API Access for Vehicle Recognition.mkv 4.75 MB
  94 - Setting Up API Access for Vehicle Recognition.srt 701 B
  95 - Key Variables and Their Role in License Plate Detection and Recognition.mkv 23.02 MB
  95 - Key Variables and Their Role in License Plate Detection and Recognition.srt 2.81 KB
  96 - Implementing License Plate Detection and Recognition.mkv 88.16 MB
  96 - Implementing License Plate Detection and Recognition.srt 11.56 KB
  97 - VisionLanguage Model Integration.mkv 69.08 MB
  97 - VisionLanguage Model Integration.srt 11.25 KB
  98 - Tkinter Implementation for RealTime License Plate Detection and Recognition.mkv 20.5 MB
  98 - Tkinter Implementation for RealTime License Plate Detection and Recognition.srt 2.34 KB
  99 - Package Installation for License Plate Detection and Recognition.mkv 13.85 MB
  99 - Package Installation for License Plate Detection and Recognition.srt 846 B
  15 - Project 8 Driving with AI RealTime Traffic Sign Detection with Python CV
  103 - Introduction of theTraffic Sign Detection And Recognition System.mkv 20.63 MB
  103 - Introduction of theTraffic Sign Detection And Recognition System.srt 1.25 KB
  104 - 8.Driving-with-AI-Real-Time-Traffic-Sign-Detection-for-Safer-Navigation.zip 476.99 KB
  104 - Google Colab Setup.mkv 33.72 MB
  104 - Google Colab Setup.srt 1.71 KB
  105 - Packages Installation.mkv 5.89 MB
  105 - Packages Installation.srt 1.35 KB
  106 - Dataset Preparation.mkv 58.49 MB
  106 - Dataset Preparation.srt 8.78 KB
  107 - Implementing Utility Functions for Traffic Sign Detection.mkv 44.09 MB
  107 - Implementing Utility Functions for Traffic Sign Detection.srt 3.36 KB
  108 - Implementing Loss Function for Traffic Sign Detection.mkv 33.53 MB
  108 - Implementing Loss Function for Traffic Sign Detection.srt 6.6 KB
  109 - EfficientNetB0 Model Implementation Info.mkv 55.91 MB
  109 - EfficientNetB0 Model Implementation Info.srt 4.07 KB
  110 - Model Training configuration.mkv 30.35 MB
  110 - Model Training configuration.srt 13.62 KB
  111 - Training the EfficientNetB0 Model.mkv 54.55 MB
  111 - Training the EfficientNetB0 Model.srt 2.27 KB
  112 - Model Inference.mkv 216.84 MB
  112 - Model Inference.srt 5.16 KB
  16 - Project 9 Smart Human Intrusion Detection System with Python Computer Vision
  113 - 9.Intrusion-Detection.zip 138.94 MB
  113 - Launching VS Code from the Command Line.mkv 1.74 MB
  113 - Launching VS Code from the Command Line.srt 532 B
  114 - Managing Folders and Files of the Project.mkv 4.69 MB
  114 - Managing Folders and Files of the Project.srt 767 B
  115 - Understanding and Setting Up Required Packages.mkv 9.35 MB
  115 - Understanding and Setting Up Required Packages.srt 1.83 KB
  116 - Accessing and Using Polygon Coordinates for Tracking.mkv 3.34 MB
  116 - Accessing and Using Polygon Coordinates for Tracking.srt 557 B
  117 - Key Variables and Their Role in YOLOv8.mkv 7.34 MB
  117 - Key Variables and Their Role in YOLOv8.srt 1.68 KB
  118 - Model Inference Code Explanation for Intrusion Detection.mkv 88.68 MB
  118 - Model Inference Code Explanation for Intrusion Detection.srt 4.79 KB
  119 - Tkinter Implementation for RealTime Intrusion Detection.mkv 20.6 MB
  119 - Tkinter Implementation for RealTime Intrusion Detection.srt 2.45 KB
  120 - Getting Polygon Coordinates Using Roboflow for Intrusion Detection.mkv 28.29 MB
  120 - Getting Polygon Coordinates Using Roboflow for Intrusion Detection.srt 1.71 KB
  121 - Intrusion Detection Code Execution.mkv 39.4 MB
  121 - Intrusion Detection Code Execution.srt 2.58 KB
  17 - Project 10 AIPowered PPE Detection Ensuring Workplace Safety in Real Time
  122 - Introduction of the PPE Detection Detection System.mkv 39.02 MB
  122 - Introduction of the PPE Detection Detection System.srt 2.58 KB
  123 - 10.AI-Powered-PPE-Detection-Ensuring-Workplace-Safety-in-Real-Time.zip 19.61 MB
  123 - PPE Detection Project Overview.mkv 11.47 MB
  123 - PPE Detection Project Overview.srt 3.09 KB
  124 - File Uploaded on Google Colab.mkv 29.41 MB
  124 - File Uploaded on Google Colab.srt 2.2 KB
  125 - Dataset Visualization.mkv 17.18 MB
  125 - Dataset Visualization.srt 2.55 KB
  126 - PPE Model Information.mkv 6.13 MB
  126 - PPE Model Information.srt 1.84 KB
  127 - PPE Code Execution.mkv 147.11 MB
  127 - PPE Code Execution.srt 6.91 KB
  128 - VS Code Open.mkv 2.95 MB
  128 - VS Code Open.srt 849 B
  129 - Packages and Module Import.mkv 10.56 MB
  129 - Packages and Module Import.srt 2.07 KB
  130 - NVIDIA Nim Information.mkv 6.06 MB
  130 - NVIDIA Nim Information.srt 1.65 KB
  131 - API Information.mkv 28.42 MB
  131 - API Information.srt 2.82 KB
  132 - File Format.mkv 4.67 MB
  132 - File Format.srt 670 B
  133 - Predict API.mkv 72.98 MB
  133 - Predict API.srt 8.06 KB
  134 - Get API.mkv 6.29 MB
  134 - Get API.srt 684 B
  135 - Code Execution.mkv 134.42 MB
  135 - Code Execution.srt 4.75 KB
  18 - Project 11 AI Vision Age Gender Detection with Python Computer Vision
  136 - Introduction to Age and Gender Detection.mkv 29.35 MB
  136 - Introduction to Age and Gender Detection.srt 1.91 KB
  137 - 11.AI-Vision-Intelligent-Age-and-Gender-Detection.zip 94.46 MB
  137 - Age and Gender Detection Project Overview.mkv 7.7 MB
  137 - Age and Gender Detection Project Overview.srt 929 B
  138 - Packages Information for Age and Gender Detection.mkv 9.66 MB
  138 - Packages Information for Age and Gender Detection.srt 844 B
  139 - Variable Initialization and System Configuration.mkv 9.32 MB
  139 - Variable Initialization and System Configuration.srt 722 B
  140 - Folder Creation.mkv 7.25 MB
  140 - Folder Creation.srt 1.53 KB
  141 - Model Inference.mkv 91.3 MB
  141 - Model Inference.srt 6.07 KB
  142 - TKinter Implementation.mkv 33.03 MB
  142 - TKinter Implementation.srt 5.43 KB
  143 - Package Installation.mkv 6.88 MB
  143 - Package Installation.srt 1.03 KB
  144 - Code Execution.mkv 13.98 MB
  144 - Code Execution.srt 2.62 KB
  19 - Project 12 AI Accident Detection RealTime Monitoring with Python CV
  145 - Intro to AIPowered Accident Detection RealTime Monitoring Alert System.mkv 32.43 MB
  145 - Intro to AIPowered Accident Detection RealTime Monitoring Alert System.srt 1.99 KB
  146 - 12.AI-Powered-Accident-Detection-and-Real-Time-Monitoring-Alert-System.zip 54.97 MB
  146 - AI Accident Detection RealTime Monitoring Alert System Project Overview.mkv 7.79 MB
  146 - AI Accident Detection RealTime Monitoring Alert System Project Overview.srt 2.51 KB
  147 - Configuring the environment on Google Colab.mkv 18.07 MB
  147 - Configuring the environment on Google Colab.srt 1.69 KB
  148 - Setting Up and Exploring Essential Packages.mkv 20.28 MB
  148 - Setting Up and Exploring Essential Packages.srt 3.15 KB
  149 - Dataset Acquisition Downloading Understanding.mkv 20.77 MB
  149 - Dataset Acquisition Downloading Understanding.srt 1.79 KB
  150 - Dataset Visualization Analysis.mkv 42.76 MB
  150 - Dataset Visualization Analysis.srt 1.36 KB
  151 - Dataset Preprocessing Normalization Resizing.mkv 53.65 MB
  151 - Dataset Preprocessing Normalization Resizing.srt 3.59 KB
  152 - Label Encoding Data Preparation.mkv 25.1 MB
  152 - Label Encoding Data Preparation.srt 1.41 KB
  153 - Training Validation Data Visualization.mkv 2.89 MB
  153 - Training Validation Data Visualization.srt 620 B
  154 - CNN Model Implementation Training.mkv 260.33 MB
  154 - CNN Model Implementation Training.srt 12.23 KB
  155 - Downloading and Saving Trained Model Weights.mkv 4.08 MB
  155 - Downloading and Saving Trained Model Weights.srt 652 B
  156 - Understanding MQTT Protocol Package Requirements.mkv 23.95 MB
  156 - Understanding MQTT Protocol Package Requirements.srt 4.17 KB
  157 - Model Inference Code Walkthrough.mkv 35.57 MB
  157 - Model Inference Code Walkthrough.srt 5.88 KB
  158 - Final Code Execution Live Demonstration.mkv 59.46 MB
  158 - Final Code Execution Live Demonstration.srt 2.23 KB
  2 - Meet Your Instructor
  2 - Introduction to Your Instructor and Course Overview.mkv 68.86 MB
  2 - Introduction to Your Instructor and Course Overview.srt 2.33 KB
  20 - Project 13 Smart Vehicle Speed Tracking System with Python Computer Vision
  159 - Introduction of Smart Vehicle Speed Tracking System.mkv 7.5 MB
  159 - Introduction of Smart Vehicle Speed Tracking System.srt 1.2 KB
  160 - 13.Vehicle-Speed-Tracking-System.zip 44.44 MB
  160 - Vehicle Detection and Speed Tracking System Overview.mkv 6.6 MB
  160 - Vehicle Detection and Speed Tracking System Overview.srt 1.2 KB
  161 - Setting Up and Exploring Essential Packages.mkv 6.11 MB
  161 - Setting Up and Exploring Essential Packages.srt 1.34 KB
  162 - Calibration for RealWorld Measurements.mkv 4.48 MB
  162 - Calibration for RealWorld Measurements.srt 927 B
  163 - Implementing Vehicle Speed Tracking with YOLOv8 Model Inference.mkv 27.06 MB
  163 - Implementing Vehicle Speed Tracking with YOLOv8 Model Inference.srt 4.81 KB
  164 - Vehicle Speed Calculation Logic and Function Implementation.mkv 18.29 MB
  164 - Vehicle Speed Calculation Logic and Function Implementation.srt 2.2 KB
  165 - Tkinter Implementation for RealTime Vehicle Speed Tracking.mkv 12.94 MB
  165 - Tkinter Implementation for RealTime Vehicle Speed Tracking.srt 2.01 KB
  166 - Vehicle Speed Tracking Code Execution.mkv 46.45 MB
  166 - Vehicle Speed Tracking Code Execution.srt 2.37 KB
  21 - Project 14 RealTime Vehicle Parking Management with Python Computer Vision
  167 - Introduction to RealTime Vehicle Tracking for Effective Parking Management.mkv 14.92 MB
  167 - Introduction to RealTime Vehicle Tracking for Effective Parking Management.srt 1.19 KB
  168 - 14.Vehicle-Parking-Management-System.zip 163.41 MB
  168 - Managing Folders and Files of the Project.mkv 5.47 MB
  168 - Managing Folders and Files of the Project.srt 1.29 KB
  169 - Vehicle Detection and Parking Slot Tracking System Overview.mkv 8.13 MB
  169 - Vehicle Detection and Parking Slot Tracking System Overview.srt 1.67 KB
  170 - Setting Up and Exploring Essential Packages.mkv 12.48 MB
  170 - Setting Up and Exploring Essential Packages.srt 1.74 KB
  171 - Implementing Vehicle Parking Management with Flask.mkv 2.99 MB
  171 - Implementing Vehicle Parking Management with Flask.srt 633 B
  172 - Building the Backend for Vehicle Parking Management with Flask.mkv 25.62 MB
  172 - Building the Backend for Vehicle Parking Management with Flask.srt 3.03 KB
  173 - Implementing Vehicle Parking Detection and Occupancy Tracking.mkv 68.48 MB
  173 - Implementing Vehicle Parking Detection and Occupancy Tracking.srt 7.58 KB
  174 - Package Installation for Vehicle Parking Management system.mkv 8.02 MB
  174 - Package Installation for Vehicle Parking Management system.srt 757 B
  175 - Get Polygon Coordinates with Roboflow to Calculate Available Parking Spaces.mkv 19.38 MB
  175 - Get Polygon Coordinates with Roboflow to Calculate Available Parking Spaces.srt 1.94 KB
  176 - Vehicle Parking Space Detection and Occupancy Tracking Code Execution.mkv 68.62 MB
  176 - Vehicle Parking Space Detection and Occupancy Tracking Code Execution.srt 2.68 KB
  22 - Project 15 RealTime Mask Detection with AI using Python Computer Vision
  177 - Introduction to Face Mask Detection and Recognition.mkv 21.28 MB
  177 - Introduction to Face Mask Detection and Recognition.srt 1.24 KB
  178 - 15.Face-Mask-Detection-and-Recognition.zip 28.35 MB
  178 - Face Mask Detection System Project Overview.mkv 9.4 MB
  178 - Face Mask Detection System Project Overview.srt 150 B
  179 - Google Drive Mount.mkv 29.9 MB
  179 - Google Drive Mount.srt 1.2 KB
  180 - Face Mask Detection Dataset Download.mkv 27.25 MB
  180 - Face Mask Detection Dataset Download.srt 2.07 KB
  181 - Dataset Visualization.mkv 10.61 MB
  181 - Dataset Visualization.srt 1004 B
  182 - Ultralytics Installation Setting Up YOLOv11 for Mask Detection.mkv 9.4 MB
  182 - Ultralytics Installation Setting Up YOLOv11 for Mask Detection.srt 470 B
  183 - YOLOv11 Model Training for Mask Detection.mkv 81.52 MB
  183 - YOLOv11 Model Training for Mask Detection.srt 1.92 KB
  184 - Packages Explanation.mkv 24.06 MB
  184 - Packages Explanation.srt 3.96 KB
  185 - Model Inference Code Explanation.mkv 57.63 MB
  185 - Model Inference Code Explanation.srt 6.84 KB
  186 - Tkinter Implementation.mkv 31.62 MB
  186 - Tkinter Implementation.srt 3.03 KB
  187 - Code Execution.mkv 27.82 MB
  187 - Code Execution.srt 2.69 KB
  23 - Project 16 RealTime Hand Gesture Detection Recognition with Python CV
  188 - 16.Hand-Gesture-Recognition.zip 6.16 MB
  188 - Hand Gesture Detection and Recognition Overview.mkv 4.81 MB
  188 - Hand Gesture Detection and Recognition Overview.srt 1.3 KB
  189 - Setting Up and Exploring Essential Packages.mkv 4.01 MB
  189 - Setting Up and Exploring Essential Packages.srt 923 B
  190 - Key Variables and Their Role in Hand Gesture Recognition.mkv 6.32 MB
  190 - Key Variables and Their Role in Hand Gesture Recognition.srt 1.45 KB
  191 - Annotating Frames with Detected Gestures and Landmarks.mkv 6.72 MB
  191 - Annotating Frames with Detected Gestures and Landmarks.srt 1.1 KB
  192 - RealTime Gesture Recognition and Frame Processing.mkv 6.55 MB
  192 - RealTime Gesture Recognition and Frame Processing.srt 1.42 KB
  193 - Integrating RealTime Gesture Recognition with Tkinter GUI.mkv 11.42 MB
  193 - Integrating RealTime Gesture Recognition with Tkinter GUI.srt 1.39 KB
  194 - Tkinter Implementation for RealTime Hand Gesture Recognition.mkv 11.64 MB
  194 - Tkinter Implementation for RealTime Hand Gesture Recognition.srt 1.5 KB
  195 - Package Installation for Hand Gesture Recognition System.mkv 4.72 MB
  195 - Package Installation for Hand Gesture Recognition System.srt 673 B
  196 - Hand Gesture Recognition Code Execution.mkv 14.25 MB
  196 - Hand Gesture Recognition Code Execution.srt 1.21 KB
  24 - Project 17 Smart Vehicle Traffic Monitoring System with Python CV
  197 - Intro to RealTime Vehicle Traffic Monitoring for Efficient Traffic Management.mkv 8.37 MB
  197 - Intro to RealTime Vehicle Traffic Monitoring for Efficient Traffic Management.srt 1.22 KB
  198 - 17.Vehicle-Traffic-Monitoring-System.zip 44.44 MB
  198 - Vehicle Detection and Traffic Monitoring System Overview.mkv 6.19 MB
  198 - Vehicle Detection and Traffic Monitoring System Overview.srt 1.61 KB
  199 - Setting Up and Exploring Essential Packages.mkv 5.01 MB
  199 - Setting Up and Exploring Essential Packages.srt 1.14 KB
  200 - User Input and Video File Selection.mkv 2.87 MB
  200 - User Input and Video File Selection.srt 562 B
  201 - Implementing Vehicle Monitoring with YOLOv8 Model Inference.mkv 37.77 MB
  201 - Implementing Vehicle Monitoring with YOLOv8 Model Inference.srt 5.29 KB
  202 - Tkinter Implementation for RealTime Vehicle Monitoring.mkv 24 MB
  202 - Tkinter Implementation for RealTime Vehicle Monitoring.srt 3.14 KB
  203 - Vehicle Traffic Monitoring Code Execution.mkv 48.28 MB
  203 - Vehicle Traffic Monitoring Code Execution.srt 2.75 KB
  25 - Project 18 Smart Fitness RealTime Exercise Counter using AI Python CV
  204 - Introduction of the Human Fitness Tracking System.mkv 27.32 MB
  204 - Introduction of the Human Fitness Tracking System.srt 1.55 KB
  205 - 18.Smart-Fitness-Real-Time-Exercise-Counting-with-AI-and-Computer-Vision.zip 26.15 MB
  205 - Project Overview Purpose.mkv 9.48 MB
  205 - Project Overview Purpose.srt 2.05 KB
  206 - Packages Overview MediaPipe Initialization.mkv 13.89 MB
  206 - Packages Overview MediaPipe Initialization.srt 2.51 KB
  207 - Calculating Angles in Pose Estimation.mkv 12.73 MB
  207 - Calculating Angles in Pose Estimation.srt 1.2 KB
  208 - Logic Behind Repetition Counting.mkv 76.52 MB
  208 - Logic Behind Repetition Counting.srt 9.91 KB
  209 - Tkinter Log Window Variable Initialization.mkv 13.91 MB
  209 - Tkinter Log Window Variable Initialization.srt 2.36 KB
  210 - Model Inference and Code Explanation.mkv 82.65 MB
  210 - Model Inference and Code Explanation.srt 7.03 KB
  211 - Tkinter Implementation for UI.mkv 26.82 MB
  211 - Tkinter Implementation for UI.srt 3.3 KB
  212 - Package Installation Guide.mkv 14.56 MB
  212 - Package Installation Guide.srt 1.27 KB
  213 - Code Execution Workflow.mkv 168.91 MB
  213 - Code Execution Workflow.srt 2.87 KB
  26 - Project 19 SafeFall AIPowered Fall Detection Alerts with Python CV
  214 - Introduction to AIPowered Fall Down Detection Alert System.mkv 28.08 MB
  214 - Introduction to AIPowered Fall Down Detection Alert System.srt 1.78 KB
  215 - 19.SafeFall-AI-Powered-Fall-Detection-Alert-System-with-Python-Computer-Vision.zip 14.69 MB
  215 - Fall Down Detection System Project Overview.mkv 10.07 MB
  215 - Fall Down Detection System Project Overview.srt 2.32 KB
  216 - Dependency Package Overview.mkv 13.59 MB
  216 - Dependency Package Overview.srt 2.91 KB
  217 - Installation MQTT Setup.mkv 14.6 MB
  217 - Installation MQTT Setup.srt 2.01 KB
  218 - User Registration Login API.mkv 11.71 MB
  218 - User Registration Login API.srt 1.87 KB
  219 - MQTT Flask Integration.mkv 13.38 MB
  219 - MQTT Flask Integration.srt 2.14 KB
  220 - Fall Detection Logic.mkv 12.32 MB
  220 - Fall Detection Logic.srt 1.72 KB
  221 - Prediction API Workflow.mkv 71.82 MB
  221 - Prediction API Workflow.srt 7.04 KB
  222 - Code Execution Testing.mkv 32.78 MB
  222 - Code Execution Testing.srt 3.34 KB
  27 - Project 20 Wildlife Tracking RealTime Animal ID with Python CV
  223 - Introduction to Animal Detection System.mkv 17.38 MB
  223 - Introduction to Animal Detection System.srt 1.29 KB
  224 - 20.Tracking-the-Wild-Real-Time-Animal-Identification-Using-Deep-Learning.zip 25.9 MB
  224 - Animal Detection System Project Overview.mkv 3.57 MB
  224 - Animal Detection System Project Overview.srt 708 B
  225 - Setting Up Google Colab and Mounting Google Drive.mkv 17.08 MB
  225 - Setting Up Google Colab and Mounting Google Drive.srt 2.45 KB
  226 - Dataset Download and Exploration.mkv 4.77 MB
  226 - Dataset Download and Exploration.srt 1.04 KB
  227 - Dataset Preprocessing and Augmentation.mkv 14.31 MB
  227 - Dataset Preprocessing and Augmentation.srt 1.32 KB
  228 - Splitting the Dataset for Training Validation and Testing.mkv 9.94 MB
  228 - Splitting the Dataset for Training Validation and Testing.srt 1.55 KB
  229 - Visualizing the Animal Dataset and Augmented Data.mkv 10.96 MB
  229 - Visualizing the Animal Dataset and Augmented Data.srt 1.17 KB
  230 - EfficientNetB0 Model Implementation.mkv 31.96 MB
  230 - EfficientNetB0 Model Implementation.srt 5.53 KB
  231 - Training the EfficientNetB0 Model and Monitoring Progress.mkv 55.77 MB
  231 - Training the EfficientNetB0 Model and Monitoring Progress.srt 6.01 KB
  232 - Model Inference using Flask and Ngrok.mkv 284.94 MB
  232 - Model Inference using Flask and Ngrok.srt 2.8 KB
  233 - Code Execution.mkv 78.24 MB
  233 - Code Execution.srt 4.46 KB
  28 - Project 21 AIPowered Driver Monitoring Distraction Detection with Python
  234 - Introduction of the Driver Distraction System.mkv 21.99 MB
  234 - Introduction of the Driver Distraction System.srt 1.41 KB
  235 - Driver Distraction Project Overview.mkv 4.29 MB
  235 - Driver Distraction Project Overview.srt 1.26 KB
  236 - Google Colab Setup Google Drive Mount.mkv 12 MB
  236 - Google Colab Setup Google Drive Mount.srt 1.2 KB
  237 - Dataset Download Exploration.mkv 25.6 MB
  237 - Dataset Download Exploration.srt 391 B
  238 - Data Visualization Insights.mkv 13.81 MB
  238 - Data Visualization Insights.srt 2.27 KB
  239 - Data Preprocessing Augmentation.mkv 145.22 MB
  239 - Data Preprocessing Augmentation.srt 11.64 KB
  240 - ResNet50 Model Architecture Implementation.mkv 203.75 MB
  240 - ResNet50 Model Architecture Implementation.srt 16.4 KB
  241 - Model Training Optimization.mkv 240.57 MB
  241 - Model Training Optimization.srt 13.56 KB
  242 - Model Inference Code Explanation.mkv 51.37 MB
  242 - Model Inference Code Explanation.srt 6 KB
  243 - Code Execution.mkv 79.64 MB
  243 - Code Execution.srt 2.4 KB
  29 - Wrapping Up
  244 - Course WrapUp.mkv 41.63 MB
  244 - Course WrapUp.srt 2.8 KB
  3 - Understanding AI From Origins to Impact
  3 - What is AI and How It Has Evolved.mkv 473.27 MB
  3 - What is AI and How It Has Evolved.srt 15.38 KB
  4 - Overview of computer vision
  4 - Introduction to Computer Vision and Its Applications.mkv 671.96 MB
  4 - Introduction to Computer Vision and Its Applications.srt 23.89 KB
  5 - Environment Setup for Python Development
  5 - Installing Python.mkv 11.37 MB
  5 - Installing Python.srt 1.22 KB
  6 - VS Code Setup for Python Development.mkv 32.57 MB
  6 - VS Code Setup for Python Development.srt 1.51 KB
  6 - Computer Vision Basic Techniques
  10 - Displaying Images and Videos.mkv 268.77 MB
  10 - Displaying Images and Videos.srt 11.43 KB
  11 - Image Resizing Cropping and Rotation.mkv 25.85 MB
  11 - Image Resizing Cropping and Rotation.srt 3.67 KB
  12 - Drawing Functions.mkv 131.5 MB
  12 - Drawing Functions.srt 11.83 KB
  13 - Image Thresholding.mkv 29.92 MB
  13 - Image Thresholding.srt 4.95 KB
  14 - Morphological Operations.mkv 36.38 MB
  14 - Morphological Operations.srt 5.56 KB
  15 - Contour Detection.mkv 34.86 MB
  15 - Contour Detection.srt 3.76 KB
  16 - Mask Image Generation.mkv 299.57 MB
  16 - Mask Image Generation.srt 10.04 KB
  17 - Background Subtraction.mkv 56.39 MB
  17 - Background Subtraction.srt 2.21 KB
  18 - Image Bitwise Operations.mkv 131.51 MB
  18 - Image Bitwise Operations.srt 11.83 KB
  19 - Histogram Equalization Gamma Correction.mkv 17.66 MB
  19 - Histogram Equalization Gamma Correction.srt 2.39 KB
  20 - Smoothing Filters.mkv 16.83 MB
  20 - Smoothing Filters.srt 2.74 KB
  21 - Sharpening Filters.mkv 17.9 MB
  21 - Sharpening Filters.srt 2.09 KB
  22 - Edge Detection Sobel.mkv 41.87 MB
  22 - Edge Detection Sobel.srt 4.62 KB
  23 - Contrast Adjustment.mkv 20.11 MB
  23 - Contrast Adjustment.srt 2.96 KB
  7 - OpenCv Fundamentals Overview.mkv 134.38 MB
  7 - OpenCv Fundamentals Overview.srt 8.38 KB
  8 - Computer-Vision-Basic-Source-Code.zip 222.1 MB
  8 - Reading and Writing Images.mkv 25.75 MB
  8 - Reading and Writing Images.srt 3.02 KB
  9 - Color Space Conversion.mkv 88.06 MB
  9 - Color Space Conversion.srt 9.84 KB
  7 - Computer Vision Advanced Techniques
  24 - Computer Vision Advanced Introduction Video.mkv 95.58 MB
  24 - Computer Vision Advanced Introduction Video.srt 5.36 KB
  25 - Edge Detection Canny.mkv 101.39 MB
  25 - Edge Detection Canny.srt 6.41 KB
  26 - Corner Detection.mkv 37.62 MB
  26 - Corner Detection.srt 4.26 KB
  27 - Keypoint Detection Matching.mkv 33.61 MB
  27 - Keypoint Detection Matching.srt 5.79 KB
  28 - Texture Analysis.mkv 41.11 MB
  28 - Texture Analysis.srt 5.26 KB
  29 - Optical Flow and Motion Analysis.mkv 264.21 MB
  29 - Optical Flow and Motion Analysis.srt 16.02 KB
  30 - Object Tracking.mkv 118.69 MB
  30 - Object Tracking.srt 15.72 KB
  31 - Image Segmentation.mkv 85.74 MB
  31 - Image Segmentation.srt 9.47 KB
  32 - Image object detection.mkv 417.15 MB
  32 - Image object detection.srt 23.45 KB
  33 - Live streaming.mkv 25.95 MB
  33 - Live streaming.srt 4.38 KB
  34 - Tesseract OCR Engine.mkv 87.29 MB
  34 - Tesseract OCR Engine.srt 8.19 KB
  8 - Project 1 Smart Face Attendance System with Python Computer Vision
  35 - Course Overview and Features.mkv 91.02 MB
  35 - Course Overview and Features.srt 3.96 KB
  36 - Installing Required Packages Dilib OpenCV etc.mkv 13.36 MB
  36 - Installing Required Packages Dilib OpenCV etc.srt 2.59 KB
  37 - 1.Smart-Face-Attendance-System.zip 2.81 MB
  37 - Face Enrollment.mkv 85.25 MB
  37 - Face Enrollment.srt 9.68 KB
  38 - Extracting Face Embeddings and Identifying Landmark.mkv 37.95 MB
  38 - Extracting Face Embeddings and Identifying Landmark.srt 4.37 KB
  39 - Training the Facial Recognition Model.mkv 15.74 MB
  39 - Training the Facial Recognition Model.srt 2.71 KB
  40 - RealTime Face Recognition and Attendance.mkv 24.04 MB
  40 - RealTime Face Recognition and Attendance.srt 3.7 KB
  41 - Building the Attendance Management GUI.mkv 9.35 MB
  41 - Building the Attendance Management GUI.srt 1.2 KB
  9 - Project 2 Driver Drowsiness Detection System with Python Computer Vision
  42 - Introduction of the Driver Drowsiness Detection System.mkv 41.83 MB
  42 - Introduction of the Driver Drowsiness Detection System.srt 1.76 KB
  43 - 2.Driver-Drowsiness-Detection-System.zip 2.84 KB
  43 - Driver Drowsiness Detection Project Overview.mkv 2.34 MB
  43 - Driver Drowsiness Detection Project Overview.srt 824 B
  44 - Understanding Key Packages for Driver Drowsiness Detection.mkv 3.64 MB
  44 - Understanding Key Packages for Driver Drowsiness Detection.srt 898 B
  45 - Implementing Drowsiness Detection Logic Using EAR and MAR.mkv 9.9 MB
  45 - Implementing Drowsiness Detection Logic Using EAR and MAR.srt 2.13 KB
  46 - Integrating Drowsiness Detection with Tkinter GUI.mkv 4.31 MB
  46 - Integrating Drowsiness Detection with Tkinter GUI.srt 1.16 KB
  47 - RealTime Driver Drowsiness Detection with Live Video Streaming.mkv 16.35 MB
  47 - RealTime Driver Drowsiness Detection with Live Video Streaming.srt 2.14 KB
  48 - RealTime Model Inference for Driver Drowsiness Detection.mkv 7.66 MB
  48 - RealTime Model Inference for Driver Drowsiness Detection.srt 1.35 KB
  ▲ 509 total files

Description


Обучающие видео » Компьютерные видеоуроки и обучающие интерактивные DVD » Machine/Deep Learning, Neural Networks

Practical Computer Vision Mastery: 20+ Python & AI Projects

Год выпуска: 6/2025
Производитель: Udemy
Сайт производителя: https://www.udemy.com/course/computer-vision-mastery-real-time-projects-opencv-python-ai-yolo/
Автор: Muhammad Yaqoob G
Продолжительность: 16h 14m 23s
Тип раздаваемого материала: Видеоурок
Язык: Английский
Субтитры: Английский
Описание:

Master Computer Vision Course in 2025 with Deep Learning, Python, OpenCV, YOLO, OCR & GUI through 20+ handson projects

What you'll learn Understand the origins, evolution, and real-world impact of AI, with a focus on computer vision’s role in modern applications.
Install and configure Python and VS Code for seamless development of vision-based projects on any platform.
Apply OpenCV fundamentals—reading, writing, displaying, resizing, cropping, and color-space conversion of images and videos.
Implement image processing techniques such as thresholding, morphological transforms, bitwise operations, and histogram equalization.
Detect edges, corners, contours, and keypoints; match features across images to enable object recognition and scene analysis.
Leverage advanced methods—Canny edge detection, texture analysis, optical flow, object tracking, segmentation, and OCR with Tesseract.
Build a smart face‐attendance system: enroll faces, extract embeddings, train a model, and launch a Tkinter GUI for live recognition.
Create a driver-drowsiness detector using EAR/MAR metrics, integrate it into a Tkinter dashboard, and run real-time video inference. Requirements Basic Python programming knowledge
Windows PC or Laptop with 4GB+ RAM is recommended. A GPU is optional but helpful for faster model training and processing large datasets or real-time tasks. Description

Unlock the power of image- and video-based AI in 2025 with 20+ real-time projects that guide you from foundational theory to fully functional applications. Designed for engineering and science students, STEM graduates, and professionals switching into AI, this hands-on course equips you with end-to-end computer vision skills to build a standout portfolio.

Key Highlights: Environment Setup & Basics: Install Python, configure VS Code, and master OpenCV operations—image I/O, color spaces, resizing, thresholding, filters, morphology, bitwise ops, and histogram equalization.
Core & Advanced Techniques: Implement edge detection (Sobel, Canny), contour/corner/keypoint detection, texture analysis, optical flow, object tracking, segmentation, and OCR with Tesseract.
Deep Learning Integration: Train and deploy TensorFlow/Keras models (EfficientNet-B0) alongside YOLOv7-tiny and YOLOv8 for robust detection tasks.
GUI Development: Build interactive Tkinter interfaces to visualize live video feeds, detection results, and system dashboards. 20+ Hands-On Projects Include: Smart Face Attendance with face enrollment, embedding extraction, model training, and GUI integration.
Driver Drowsiness Detection using EAR/MAR algorithms and real-time alert dashboards.
YOLO Object & Weapon Detection pipelines for live inference and visualization.
People Counting & Entry/Exit Tracking with configurable line-coordinate logic.
License-Plate & Traffic Sign Recognition leveraging Roboflow annotations and custom model training.
Intrusion & PPE Detection for workplace safety monitoring.
Accident & Fall Detection with MQTT alert systems.
Mask, Emotion, Age/Gender & Hand-Gesture Recognition using custom-trained vision models.
Wildlife Identification with EfficientNet-based classification in live streams.
Vehicle Speed Tracking using calibration and object motion analysis. By course end, you’ll be able to: Develop, train, and fine-tune deep-learning vision models for diverse real-world tasks.
Integrate CV pipelines into intuitive GUIs for live video applications.
Execute industry-standard workflows: data annotation, training, evaluation, and deployment.
Showcase a portfolio of 20+ complete projects to launch or advance your AI career. Enroll today and start building your first real-time computer vision app!

Who this course is for: Undergraduate and Graduate Students in engineering, computer science, electronics or related fields seeking hands-on CV projects to complement their studies.
Recent Graduates with STEM degrees who want to build practical AI skills and showcase real-world projects on their résumé.
Working Professionals in software, electronics, robotics or data roles aiming to pivot into AI/ML and leverage vision applications in industry.
Career-Switchers from STEM Fields (e.g., physics, mathematics, biotech) looking for a structured path into computer vision without starting from scratch.
R&D Engineers & IoT Developers who need to integrate vision analytics on edge devices like Jetson, Raspberry Pi or in cloud pipelines.
Self-Learners & Hobbyists with a science/engineering mindset who want to master end-to-end CV workflows—from algorithm basics to GUI deployment and model inference. Формат видео: MKV
Видео: avc, 1920x1080, 16:9, 29.845 к/с, 1978 кб/с
Аудио: aac lc sbr, 44.1 кгц, 62.8 кб/с, 2 аудио
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[/spoiler]
[spoiler="Скриншоты"]

[/spoiler]

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