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Computer Vision Smart Systems : Python, Yolo And Opencv -1
Published 10/2024
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.84 GB | Duration: 6h 41m
Develop Your Own Computer Vision Smart System with Python and YOLO | Step-by-Step | OpenCV | Real-Time Object Detection
What you'll learn
Introduction to Image Processing and Computer Vision,
Object Detection with YOLO Algorithm
Building Custom Deep Learning Models
Practical Vehicle Counting Project
Project Development and Implementation
Requirements
No Prior Experience Required
Basic Computer Skills
Eagerness to Learn
Description
This course is designed for anyone interested in pursuing a career in artificial intelligence and computer vision or looking to implement computer vision applications in their projects. In "Computer Vision Smart Systems: Python, YOLO, and OpenCV -1," we start with the fundamentals of computer vision and cover image processing techniques using the Python programming language and OpenCV library. Then, we advance to object detection and deep learning modeling using the YOLO (You Only Look Once) algorithm. Students will learn to build custom deep learning models from scratch, work with datasets, perform object detection, and apply these models in various projects.Throughout the course, practical exercises are provided step-by-step along with theoretical knowledge, giving students the chance to apply what they've learned. Additionally, we address common challenges you may face and provide detailed solutions. Aimed at building skills from basic to intermediate levels, this course serves as a comprehensive guide for anyone interested in the field of computer vision. It empowers you to develop smart systems for your projects and enhances your expertise in this exciting domain."You are never too old to set another goal or to dream a new dream." - C.S.Lewis"Do the difficult things while they are easy and do the great things while they are small. A journey of a thousand miles begins with a single step" - Lao TzuYou get the best information that I have compiled over years of trial and error and experience!Best wishes,Yılmaz ALACA
Overview
Section 1: Introduction
Lecture 1 Hello!
Section 2: Docs - Optional
Lecture 2 File Operations
Lecture 3 applyColorMap
Section 3: Python 3
Lecture 4 Installation of Python
Lecture 5 Installation of Jupyter Notebook
Lecture 6 What Is Variable?
Lecture 7 Numerical Data Types (Variables) -1
Lecture 8 Numerical Data Types (Rules of Variables) -2
Lecture 9 Numerical Data Types (Rules of Variables) -3
Lecture 10 String Data Type -1
Lecture 11 Changing Variable (Rules of Variables) -4
Lecture 12 Standart OUTPUT Function
Lecture 13 Lists -1
Lecture 14 Lists -2
Lecture 15 Standart Input Function
Lecture 16 Type Conversions -1
Lecture 17 Type Conversions 2
Lecture 18 Tuples
Lecture 19 Logical Data Types
Lecture 20 Logical Conjuctions -1
Lecture 21 Logical Conjuctions -2
Lecture 22 What is Conditional Structure?
Lecture 23 If Condition
Lecture 24 If-Else Condition
Lecture 25 If-Elif-Else Condition
Lecture 26 What is loop?
Lecture 27 Structure "in"
Lecture 28 For Loop -1
Lecture 29 For Loop -2
Lecture 30 While Loop
Lecture 31 While - Else
Lecture 32 break and continue
Lecture 33 Functions -1
Lecture 34 Default Parameter and Parameter Order
Lecture 35 Functions -2
Lecture 36 Multiple Data in a Parameter
Lecture 37 Functions -3
Lecture 38 Functions -4
Lecture 39 Functions -5
Lecture 40 Modules -1
Lecture 41 Modules -2
Lecture 42 Modules -3
Lecture 43 Installation of PyCharm
Section 4: OpenCV
Lecture 44 Installation of OpenCV
Lecture 45 Displaying an Image
Lecture 46 Getting Size of Images
Lecture 47 Resizing
Lecture 48 Cropping a Certain Area
Lecture 49 Drawing Functions -1
Lecture 50 Drawing Operations -2
Lecture 51 Drawing Functions -3
Section 5: Coding Exercises
Section 6: Libraries | Modules
Lecture 52 Theory: Creating a Special PutText Function
Lecture 53 Creating a Special PutText Function (Coding) -1
Lecture 54 Creating a Special PutText Function (Coding) -2
Lecture 55 Creating a Special Rectangle Function (Coding) -1
Lecture 56 Creating a Special Rectangle Function (Coding) -2
Lecture 57 Creating a Object List Function for YOLO -1
Lecture 58 Creating a Object List Function for YOLO -2
Lecture 59 Creating a Object List Function for YOLO -3
Lecture 60 Creating a Object List Function for YOLO -4
Lecture 61 Creating a Stacking Images Function -1
Lecture 62 Creating a Stacking Images Function -2
Lecture 63 Creating a Dir Function
Lecture 64 Creating a pointsOfMouse Function
Section 7: Creating Custom Models with YOLO (Deep Learning)
Lecture 65 Installation of Packages
Lecture 66 Yolo (GPU)
Lecture 67 Data Collection -1 (Modules and Variables)
Lecture 68 Data Collection -2 (Modules and Variables)
Lecture 69 Data Collection -3 (Loops)
Lecture 70 Data Collection -4 (Loops)
Lecture 71 Data Collection -5 (Loops)
Lecture 72 Data Collection -6 (Loops)
Lecture 73 Solving Problems about Data Collection
Lecture 74 Collecting Data
Lecture 75 Data Cleaning -1
Lecture 76 Data Cleaning -2
Lecture 77 Data Cleaning -3
Lecture 78 Data Cleaning -4
Lecture 79 Data Cleaning -5
Lecture 80 Data Cleaning -6
Lecture 81 Data Cleaning
Lecture 82 Data Splitting
Lecture 83 Data Splitting -2
Lecture 84 Training (Custom Model)
Lecture 85 Testing -1
Lecture 86 Testing -2
Section 8: Project 1: Car Counter
Lecture 87 Creation of Variables
Lecture 88 Creation of Loop
Beginners in Programming: Individuals with no prior programming experience who want to learn Python and apply it to real-world applications in computer vision.,Aspiring Data Scientists: Those looking to enter the field of data science and machine learning, particularly in the domain of computer vision.,Students and Professionals: College students, recent graduates, or professionals seeking to expand their skill set in artificial intelligence and image processing.,Hobbyists and Enthusiasts: Anyone with a keen interest in technology, artificial intelligence, or robotics who wants to explore how computer vision systems are built.,Developers Transitioning to AI: Programmers or software developers wanting to branch into the field of artificial intelligence and machine learning, specifically in computer vision.,Project-Based Learners: Individuals who learn best through hands-on projects and practical applications, as this course includes a final project on vehicle counting.
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