Course curriculum

  • 1

    Intro

    • Welcome! (how to use the course)
  • 2

    Installations

    • Install Python and Opencv (on Windows)

    • PyCharm IDE (Install, create new projects, useful shortcuts)

    • Install Opencv with CUDA GPU (on Windows)

    • Install Darknet with CUDA GPU (on Windows)
  • 3

    OpenCV - Computer Vision Basics

    • What Is OpenCV and What you'll learn in this module

    • 1. Load and Save images

    • 2. Load and Save videos

    • 3. Drawing functions

    • 4. Basic Operations with images

    • 5. Arithmetical Operations

    • 6. Find and draw contours

    • 7. Contours 4 main features
  • 4

    Module 1: Simple Object detection with Opencv

    • 4 different Object Detection methods

    • 1.1 OBJECT DETECTION BY COLOR: The HSV Colorspace

    • 1.2 OBJECT DETECTION BY COLOR: Detect objects on an Image and in Real Time

    • 2.1 OBJECT DETECTION ON HOMOGENEOUS BACKGROUND: The Threshold

    • 2.2 OBJECT DETECTION ON HOMOGENEOUS BACKGROUND: Detect objects on an Image and in Real time

    • 3.1 OBJECT DETECTION WITH BACKGROUND SUBTRACTION: Simple background subtraction and MOG

    • 3.2 OBJECT DETECTION WITH BACKGROUND SUBTRACTION: Detect objects on an Image and In Real Time

    • 4.1 OBJECT DETECTION USING FEATURES: What are Features and Feature Matching

    • 4.2 OBJECT DETECTION USING FEATURES: Detect objects on an Image and in Real Time

    • 4.3 OBJECT DETECTION USING FEATURES: Improve the detection with Lowe's ratio test
  • 5

    Module 2: Object Detection with Deep Learning

    • Object detection with Deep Learning

    • 1. Detect Object with YOLO

    • 2.1 Create an Image Dataset

    • 2.2 Download Images from OID (on Google Colab)

    • 2.3 Download Images from OID (with OIDV4 Toolkit) - for big datasets

    • 2.4 Convert OID (open Images Dataset) to YOLO

    • 2.5 Video Annotation (Create images dataset from a video)

    • 3.1 Train Custom Object Detector with CUDA GPU (on Windows)

    • 3.2 Train Custom Object Detector with Google Colab

    • 4. Detect Custom Objects

    • Run YOLO on GPU

    • Improve the Detection (coming soon)
  • 6

    Module 3: Object Tracking

    • 1. Object Detection vs Object Tracking

    • 2. Object Tracking (with Euclidean Distance)

    • 3. Object Tracking (with SORT)

    • 4. Object Tracking (YOLO + SORT)

    • 5. Object Counting

    • 6. Object Trajectory

    • 7. Object Tracking (with Deep Sort)
  • 7

    Module 4: Full Projects

    • [Agriculture] Count plants crops (from Drone footage) - Part 1

    • [Agriculture] Count plants crops (from Drone footage) - Part 2

    • [Agriculture] Count plants crops (from Drone footage) - Part 3
  • 8

    Raspberry PI

    • Raspberry PI Setup (Install Rasperry PI OS and Opencv)

    • Detect Objects with Opencv and YOLO
  • 9

    Jetson Nano

    • Jetson Nano Setup (Install OS, Opencv and more)

    • Real time object detection YOLO