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Download Udemy - Master Computer Vision™ OpenCV4 in Python with Deep Learning

Download Udemy - Master Computer Vision™ OpenCV4 in Python with Deep Learning
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Master Computer Vision™ OpenCV4 in Python with Deep Learning
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Master OpenCV4 like a pro while learning Dlib, Deep Learning Computer Vision (Keras, TensorFlow & Caffe) + 21. .13 or OpenCV . with the contrib package added.

13 or OpenCV . Ideally you should be using Python . and OpenCV . 0 with the contrib package added.

Why Learn Computer Vision in Python using OpenCV? Computer vision applications and technology are . 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.

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.

Computer Vision - OpenCV3 Python & Machine Learning. Key concepts of computer Vision & OpenCV. This course is taught by Computer Vision expert from University of Edinberg. The course is implementation oriented and less of theorey. If you do not care about the theorey and are looking for a quick implememntation guide on popular OpenCV algorithms, this is the course to take. What I learnt from this course. Perform image manipulations such as transformations, cropping, blurring, thresholding, edge detection and cropping

Learn OpenCV4, Dlib, Keras, TensorFlow & Caffe while completing over 21 projects such as classifiers, detectors & more! . 2. Introduction to Computer Vision and OpenCV. vtt (. KB). 3. About this course.

Learn OpenCV4, Dlib, Keras, TensorFlow & Caffe while completing over 21 projects such as classifiers, detectors & more! Created by Rajeev Ratan Last updated 6/2019. Files: Udemy - Master Computer Vision™ OpenCV4 in Python with Deep Learning 1. Course Introduction and Setup. mp4 (1. MB). 1. Introduction. mp4 (.

3 Deep Learning Computer Vision OC. df. 9 MB. Download Your Deep Learning Virtual Machine HERE. 127 B. Intro to Handwritten Digit Classification (MNIST).

Grasp Laptop Imaginative and prescient™ OpenCV4 in Python with Deep Studying. On this course, you’ll uncover the ability of OpenCV in Python, and acquire abilities to dramatically enhance your profession prospects as a Laptop Imaginative and prescient developer

Grasp Laptop Imaginative and prescient™ OpenCV4 in Python with Deep Studying. Study OpenCV4, Dlib, Keras, TensorFlow & Caffe whereas finishing over 21 tasks comparable to classifiers, detectors & extra! What you’ll study. Perceive and use OpenCV4 in Python. On this course, you’ll uncover the ability of OpenCV in Python, and acquire abilities to dramatically enhance your profession prospects as a Laptop Imaginative and prescient developer.

What most computer vision and deep learning courses & textbooks tell you simply isn't true: You don’t need complicated theory. You don’t need pages of complex math equations. And you certainly don’t need a degree in computer science or mathematics. All you need is some basic programming experience and a willingness to learn.

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Welcome to one of the most thorough and well taught courses on OpenCV, where you'll learn how to Master Computer Vision using newest version of OpenCV4 in Python!

Welcome to one of the most thorough and well taught courses on OpenCV, where you'll learn how to Master Computer Vision using newest version of OpenCV4 in Python! . Welcome to one of the most thorough and well taught courses on OpenCV, where you'll learn how to Master Computer Vision using newest version of OpenCV4 in Python! Free Courses Online Courses Python Computer Vision Going To University College Classes Online Tutorials Schools First Learning Courses.


Description
Welcome to one of the most thorough and well taught courses on OpenCV, where you’ll learn how to Master Computer Vision using newest version of OpenCV4 in Python!
You will be learning:
The key concepts of Computer Vision & OpenCV (using the newest version OpenCV 4)
To perform image manipulations such as transformations, cropping, blurring, thresholding, edge detection and cropping.
To segment images by understanding contours, circle, and line detection. You’ll even learn how to approximate contours, do contour filtering and ordering as well as approximations.
Use feature detection (SIFT, SURF, FAST, BRIEF & ORB) to do object detection.
Implement Object Detection for faces, people & cars.
Extract facial landmarks for face analysis, applying filters and face swaps.
Implement Machine Learning in Computer Vision for handwritten digit recognition.
Implement Facial Recognition.
Implement and understand Motion Analysis & Object Tracking.
Use basic computational photography techniques for Photo Restoration (eliminate marks, lines, creases, and smudges from old damaged photos).
How to become a true computer vision expert by getting started in Deep Learning ( 3+ hours of Deep Learning with Keras in Python)
How to develop Computer Vision Product Ideas
How to perform Multi Object Detection (90 Object Types)
How to colorize Black & White Photos and Video
Neural Style Transfers – Apply the artistic style of Van Gogh, Picasso and others to any image even your webcam input
How to make your own Automatic Number-Plate Recognition (ALPR
Credit Card Number Identification (Build your own OCR Classifier with PyTesseract)
OpenCV Projects Include:
Live Drawing Sketch using your webcam
Identifying Shapes
Counting Circles and Ellipses
Finding Waldo
Single Object Detectors using OpenCV
Car and Pedestrian Detector using Cascade Classifiers
Live Face Swapper (like MSQRD & Snapchat filters!!!)
Yawn Detector and Counter
Handwritten Digit Classification
Facial Recognition
Ball Tracking
Photo-Restoration
Automatic Number-Plate Recognition (ALPR)
Neural Style Transfer Mini Project
Multi Object Detection in OpenCV (up to 90 Objects!) using SSD (Single Shot Detector)
Colorize Black & White Photos and Video
Deep Learning Projects Include:
Build a Handwritten Digit Classifier
Build a Multi Image Classifier
Build a Cats vs Dogs Classifier
Understand how to boost CNN performance using Data Augmentation
Extract and Classify Credit Card Numbers
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 an 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 Classifier
Build a Cats vs Dogs Classifier
Understand how to boost CNN performance using Data Augmentation
Extract and Classify Credit Card Numbers
As for Updates and support:
I will be continuously adding updates, fixes, and new amazing projects every month!
I will be active daily in the ‘questions and answers’ area of the course, so you are never on your own.
So, are you ready to get started? Enroll now and start the process of becoming a master in Computer Vision today!
Who this courseis 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
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
Last updated 6/2019

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Udemy - Master Computer Vision™ OpenCV4 in Python with Deep Learning