Object Detection (Opencv and Deep Learning) – Full program

OpenCV – Computer Vision Basic

You will learn the Computer Vision Basics

Intro: What Is OpenCV and What you’ll learn in this module 6m

1. Load and Save images 11m |

2. Load and Save videos 16m |

3. Drawing functions 23m |

4. Basic Operations with images 31m |

6. Find and draw contours 15m |

7. Contours 4 main features 16m |

1. Object Detection with OPENCV

On the first module you learn 4 different object detection methods using the Opencv library.

Intro: 4 detection models 9m |

1 Object detection by color:

1.1 The HSV Colorspace 35m | | Python code

1.2 Detect objects on an Image and in Real Time 34m | | Python code

2 Object detection on homogeneous background:

2.1 The Threshold 17m | | Python code

2.2 Detect objects on an Image and in Real time 20m | | Python code

3 Object detection with background subtraction:

3.1 Simple background subtraction and MOG 24m | | Python code

3.2 Detect objects on an Image and In Real Time 25m | | Python code

4 Object detection using features:

4.1 What are Features and Feature Matching 20m | | Python code

4.2 Detect objects on an Image and in Real Time 25m | | Python code

4.3 Improve the detection with Lowe’s ratio test 19m | | Python code

2. Object Detection with Deep Learning

On the second module you learn object detection methods using Deep learning with YoloV4

Intro: Object detection with Deep Learning 9m

1 Detect Object with YOLO 31m | | Python code

2 Dataset:

2.1 Create an Image Dataset 13m |

2.2 Download Dataset from OID (On Google Colab) 23m | | Notebook

2.3 Download Dataset from OID (with OIDV) – for big dataset 15m | | Python code

2.4 Convert OID (Open Image Dataset) to YOLO 11m | | Python code

2.5 Video annotation (Create images dataset from a video) 14m | | Python code

3 Train Custom Object Detector

3.1 Train custom object detector on CUDA GPU (on Windows) 56m | | Python code

3.2 Train custom object detector online (on Google Colab) 27m | | Notebook

3.3 Calculate the precision of your model coming soon

3.4 Solve most common errors (cuda out of memory, etc.) coming soon

4 Detect Custom Objects

4.1 Detect Custom Objects on an Image 11m | | Python code

4.2 Detect Custom Objects in real time (with CUDA GPU) 13m | | Python code

3. Object Tracking

In the third module we Object Tracking and Object Counting

1. Object Detection vs Object Tracking 20m | | Python code

2. Object Tracking (with Euclidean Distance) 31m | | Python code

3. Object Tracking (with SORT) 27m | | Python code

4. Object Tracking (YOLO + SORT) 29m | | Python code

5. Object Counting 25m | | Python code

6. Object Trajectory 23m | | Python code

7. Object Tracking (with Deep Sort) 38m | | Python code

4. Full Projects

AIn the fourth module there are complete projects

[Agriculture] Count plants crops (from Drone footage) – Part 1 59m | | Python code

[Agriculture] Count plants crops (from Drone footage) – Part 2 53m | | Python code

[Agriculture] Count plants crops (from Drone footage) – Part 3 34m | | Python code

5. Object Detection on Raspberry pi and Jetson Nano

Learn how to easily deploy your object detection models on Raspberry pi and Jetson Nano

Raspberry PI:

Raspberry PI Setup (Install Rasperry PI OS and Opencv) 17m |

Detect Objects with Opencv and YOLO 18m |

NVidia Jetson Nano:

Jetson Nano Setup (Install OS, Opencv GPU and more) 36m |

Real time object detection YOLO 13m |

Installations

Step-by-Step instructions for all the necessary installations

Install Python and Opencv (on Windows) 7m |

PyCharm IDE (Install, create new projects, useful shortcuts) 14m |

Install Opencv with CUDA GPU (on Windows) 33m |

Install Darknet with CUDA GPU (on Windows) 15m |