Master Computer Vision™ OpenCV4 in Python with Deep Learning | Part 2

Publicado em: 07 Fevereiro 2024
no canal de: Learnly Development

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Master OpenCV4 like a pro while learning Dlib, Deep Learning Computer Vision (Keras, TensorFlow & Caffe) + 21 Projects!

00:00:00 Image Manipulations & Processing
01:01:24 Image Segmentation & Contours
01:58:06 Object Detection in OpenCV
02:48:59 Object Detection - Build a Face, People and CarVehicle Detectors
03:11:37 Augmented Reality (AR) - Facial Landmark Identification (Face Swaps)
03:46:54 Simple Machine Learning using OpenCV

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 Existing online tutorials, textbooks, and free MOOCs are often outdated, using older incompatible libraries or are too theoretical, making it difficult to understand.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 Even simply running example code I found online proved difficult as libraries and functions were often outdated.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

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