Python for Computer Vision with OpenCV and Deep Learning

Learn the latest techniques in computer vision with Python , OpenCV , and Deep Learning!

  • Jose Portilla
  • 4.62
  • (8708 reviews)
  • 14 hrs
  • 92 lectures
  • Udemy
Python for Computer Vision with OpenCV and Deep Learning

What you will 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.

Your trainer

Jose Portilla

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 and programming. He has publications and patents in various fields such as microfluidics, materials science, and data science technologies. 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, as well as present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Data Inc. 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 contact him on LinkedIn for more information on in-person training sessions or group training sessions in Las Vegas, NV.

92 lessons

Easy to follow lectures and videos covering subject details.

14 hours

This course includes hours of video material. Watch on-demand, anytime, anywhere.

Certificate of Completion

You will earn a Certificate of Completion at the end of this course.

Course curriculum

Course Overview and Introduction23:02

  • Course Overview04:54
  • FAQ - Frequently Asked Questions00:44
  • Course Curriculum Overview04:39
  • Getting Set-Up for the Course Content12:45

  • Introduction to Numpy and Image Section00:41
  • NumPy Arrays16:49
  • What is an image?05:53
  • Images and NumPy12:23
  • NumPy and Image Assessment Test02:39
  • NumPy and Image Assessment Test - Solutions08:45

  • Introduction to Images and OpenCV Basics02:37
  • Opening Image files in a notebook19:29
  • Opening Image files with OpenCV10:49
  • Drawing on Images - Part One - Basic Shapes10:00
  • Drawing on Images Part Two - Text and Polygons09:29
  • Direct Drawing on Images with a mouse - Part One09:36
  • Direct Drawing on Images with a mouse - Part Two02:41
  • Direct Drawing on Images with a mouse - Part Three10:25
  • Image Basics Assessment03:30
  • Image Basics Assessment Solutions13:26

  • Introduction to Image Processing00:39
  • Color Mappings06:47
  • Blending and Pasting Images14:15
  • Blending and Pasting Images Part Two - Masks15:55
  • Image Thresholding17:41
  • Blurring and Smoothing06:43
  • Blurring and Smoothing - Part Two19:45
  • Morphological Operators15:27
  • Gradients13:40
  • Histograms - Part One12:34
  • Histograms - Part Two - Histogram Eqaulization12:19
  • Histograms Part Three - Histogram Equalization08:12
  • Image Processing Assessment03:52
  • Image Processing Assessment Solutions08:31

  • Introduction to Video Basics01:05
  • Connecting to Camera14:14
  • Using Video Files07:00
  • Drawing on Live Camera16:45
  • Video Basics Assessment01:36
  • Video Basics Assessment Solutions05:00

  • Introduction to Object Detection02:27
  • Template Matching17:41
  • Corner Detection - Part One - Harris Corner Detection14:08
  • Corner Detection - Part Two - Shi-Tomasi Detection06:25
  • Edge Detection09:28
  • Grid Detection08:16
  • Contour Detection11:11
  • Feature Matching - Part One12:25
  • Feature Matching - Part Two18:28
  • Watershed Algorithm - Part One11:49
  • Watershed Algorithm - Part Two20:14
  • Custom Seeds with Watershed Algorithm18:54
  • Introduction to Face Detection09:11
  • Face Detection with OpenCV14:30
  • Detection Assessment03:27
  • Detection Assessment Solutions07:10

  • Introduction to Object Tracking00:34
  • Optical Flow05:37
  • Optical Flow Coding with OpenCV - Part One18:35
  • Optical Flow Coding with OpenCV - Part Two10:57
  • MeanShift and CamShift Tracking Theory05:47
  • MeanShift and CamShift Tracking with OpenCV14:41
  • Overview of various Tracking API Methods06:50
  • Tracking APIs with OpenCV06:52

  • Introduction to Deep Learning for Computer Vision02:29
  • Machine Learning Basics06:54
  • Understanding Classification Metrics14:12
  • Introduction to Deep Learning Topics01:24
  • Understanding a Neuron05:12
  • Understanding a Neural Network06:30
  • Cost Functions03:40
  • Gradient Descent and Back Propagation03:20
  • Keras Basics18:02
  • MNIST Data Overview04:41
  • Convolutional Neural Networks Overview - Part One18:53
  • Convolutional Neural Networks Overview - Part Two04:23
  • Keras Convolutional Neural Networks with MNIST17:08
  • Keras Convolutional Neural Networks with CIFAR-1011:59
  • LINK FOR CATS AND DOGS ZIP00:05
  • Deep Learning on Custom Images - Part One14:50
  • Deep Learning on Custom Images - Part Two19:34
  • Deep Learning and Convolutional Neural Networks Assessment02:37
  • Deep Learning and Convolutional Neural Networks Assessment Solutions07:07
  • Introduction to YOLO v303:16
  • YOLO Weights Download00:08
  • YOLO v3 with Python17:05

  • Introduction to CapStone Project00:50
  • Capstone Part One - Variables and Background function07:47
  • Capstone Part Two - Segmentation06:01
  • Capstone Part Three - Counting and ConvexHull14:17
  • Capstone Part Four - Bringing it all together12:15

  • BONUS LECTURE00:10
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