Python for Computer Vision with OpenCV and Deep Learning
What you'll learn
- Understand basics of NumPy
- Manipulate and open Images with NumPy
- Use OpenCV to work with image files
- Use Python and OpenCV to draw shapes on images and videos
- Perform image manipulation with OpenCV, including smoothing, blurring, thresholding, and morphological operations.
- Create Color Histograms with OpenCV
- Open and Stream video with Python and OpenCV
- Detect Objects, including corner, edge, and grid detection techniques with OpenCV and Python
- Create Face Detection Software
- Segment Images with the Watershed Algorithm
- Track Objects in Video
- Use Python and Deep Learning to build image classifiers
- Work with Tensorflow, Keras, and Python to train on your own custom images.
- Must have clear understanding of Python Basics
- Windows 10 or MacOS or Ubuntu
- Must have Install Permissions on Computer
- WebCam if you want to learn the video streaming content
Welcome to the ultimate online course on Python for Computer Vision!
This course is your best resource for learning how to use the Python programming language for Computer Vision.
We'll be exploring how to use Python and the OpenCV (Open Computer Vision) library to analyze images and video data.
The most popular platforms in the world are generating never before seen amounts of image and video data. Every 60 seconds users upload more than 300 hours of video to Youtube, Netflix subscribers stream over 80,000 hours of video, and Instagram users like over 2 million photos! Now more than ever its necessary for developers to gain the necessary skills to work with image and video data using computer vision.
Computer vision allows us to analyze and leverage image and video data, with applications in a variety of industries, including self-driving cars, social network apps, medical diagnostics, and many more.
As the fastest growing language in popularity, Python is well suited to leverage the power of existing computer vision libraries to learn from all this image and video data.
In this course we'll teach you everything you need to know to become an expert in computer vision! This $20 billion dollar industry will be one of the most important job markets in the years to come.
We'll start the course by learning about numerical processing with the NumPy library and how to open and manipulate images with NumPy. Then will move on to using the OpenCV library to open and work with image basics. Then we'll start to understand how to process images and apply a variety of effects, including color mappings, blending, thresholds, gradients, and more.
Then we'll move on to understanding video basics with OpenCV, including working with streaming video from a webcam. Afterwards we'll learn about direct video topics, such as optical flow and object detection. Including face detection and object tracking.
Then we'll move on to an entire section of the course devoted to the latest deep learning topics, including image recognition and custom image classifications. We'll even cover the latest deep learning networks, including the YOLO (you only look once) deep learning network.
This course covers all this and more, including the following topics:
Images with NumPy
Image and Video Basics with NumPy
Blending and Pasting Images
Blurring and Smoothing
Streaming video with OpenCV
Corner, Edge, and Grid Detection
Deep Learning with Keras
Keras and Convolutional Networks
Customized Deep Learning Networks
State of the Art YOLO Networks
and much more!
Feel free to message me on Udemy if you have any questions about the course!
Thanks for checking out the course page, and I hope to see you inside!
Who this course is for:
- Python Developers interested in Computer Vision and Deep Learning. This course is not for complete python beginners.
Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science, Machine Learning and Python Programming. He has publications and patents in various fields such as microfluidics, materials science, and data science. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming, the ability to analyze data, and the skills needed to present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Training and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, The New York Times, Credit Suisse, McKinsey and many more. Feel free to check out the website link to find out more information about training offerings.