Master Computer Vision™ OpenCV4 in Python with Deep Learning

Master OpenCV4 like a pro while learning Dlib, Deep Learning Computer Vision (Keras, TensorFlow & Caffe) + 21 Projects! 00:00:00 Course Introduction and Setup : Introduction 00:02:05 Introduction to Computer Vision and OpenCV 00:05:13 Recomended - Setup your OpenCV4.0.1 Virtual Machine 00:10:55 Installation of OpenCV & Python on Windows 00:19:49 Set up course materials - Not needed if using the new VM 00:21:31 Basics of Computer Vision and OpenC : What are Images 00:23:58 How are Images Formed 00:27:19 Storing Images on Computers 00:32:43 Getting Started with OpenCV - A Brief OpenCV Intro 00:42:03 Grayscaling - Converting Color Images To Shades of Gray 00:44:02 Understanding Color Spaces - The Many Ways Color Images Are Stored Digitally 00:56:15 Histogram representation of Images - Visualizing the Components of Images 01:00:53 Creating Images & Drawing on Images - Make Squares, Circles, Polygons & Add Text Why Learn Computer Vision in Python using OpenCV? Computer vision applications and technology are exploding right now! With several apps and industries making amazing use of the technology, from billion-dollar apps such as Pokémon GO, Snapchat and up and coming apps like MSQRD and PRISMA. Even Facebook, Google, Microsoft, Apple, Amazon, and Tesla are all heavily utilizing computer vision for face & object recognition, image searching and especially in Self-Driving Cars! As a result, the demand for computer vision expertise is growing exponentially! However, learning computer vision is hard! Existing online tutorials, textbooks, and free MOOCs are often outdated, using older incompatible libraries or are too theoretical, making it difficult to understand. This was my problem when learning Computer Vision and it became incredibly frustrating. Even simply running example code I found online proved difficult as libraries and functions were often outdated. I created this course to teach you all the key concepts without the heavy mathematical theory while using the most up to date methods. I take a very practical approach, using more than 50 Code Examples. At the end of the course, you will be able to build 12 Awesome Computer Vision Apps using OpenCV in Python. I use OpenCV which is the most well supported open-source computer vision library that exists today! Using it in Python is just fantastic as Python allows us to focus on the problem at hand without being bogged down by complex code. If you're an academic or college student I still point you in the right direction if you wish to learn more by linking the research papers of techniques we use. So if you want to get an excellent foundation in Computer Vision, look no further. This is the course for you! In this course, you will discover the power of OpenCV in Python, and obtain skills to dramatically increase your career prospects as a Computer Vision developer. You get 3+ Hours of Deep Learning in Computer Vision using Keras, which includes: A free Virtual Machine with all Deep Learning Python Libraries such as Keras and TensorFlow pre-installed Detailed Explanations on Neural Networks and Convolutional Neural Networks Understand how Keras works and how to use and create image datasets Build a Handwritten Digit Classifier Build a Multi-Image ClassifierBuild a Cats vs Dogs Classifier Understand how to boost CNN performance using Data Augmentation Extract and Classify Credit Card Numbers Requirements: Little to no programming knowledge is needed, but basic programing knowledge will help Windows 10 or Ubuntu or a MacOS system A webcam to implement some of the mini projects Who this is for: Beginners who have an interest in computer vision College students looking to get a head start before starting computer vision research Anyone curious using Deep Learning for Computer Vision Entrepreneurs looking to implement computer vision startup ideas Hobbyists wanting to make a cool computer vision prototype Software Developers and Engineers wanting to develop a computer vision skillset ------------------------------------------------------- Donate: BTC: bc1qg69kzedgq236d9pp7v0p2kupsdevqypp34xl8g ETH: 0x60150740F8BcC8d72bC9194F27ce9cc876d7c45D DOGE: DACsgPRufvg9UGowKbBRLqG4Vv1nvRUMm1 TRX: TUU7ex62obSqqj9RM9WtBFn63VJZeZywZn BNB Smart Chain: 0x60150740F8BcC8d72bC9194F27ce9cc876d7c45D USDT ERC20: 0x60150740F8BcC8d72bC9194F27ce9cc876d7c45D USDT TRC20: TUU7ex62obSqqj9RM9WtBFn63VJZeZywZn USDT BEP2: bnb15lqd2sfzzuazt9pwkzlj52vw64jsm4yzxjr8gl If you think any content in this channel violates copyright, please contact this email: [email protected]