Python for Computer Vision with OpenCV and Deep Learning
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       Video Length : 15h10m0s
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       Tasks Number : 100
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       Students Enrolled : 713
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       Medium Level
  • Curriculum
  • 1. Course Overview and Introduction
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      Course Overview
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      FAQ - Frequently Asked Questions
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      Course Curriculum Overview
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      Getting Set-Up for the Course Content
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  • 2. NumPy and Image Basics
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      Introduction to Numpy and Image Section
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      NumPy Arrays
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      What is an image?
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      Images and NumPy
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      NumPy and Image Assessment Test
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      NumPy and Image Assessment Test - Solutions
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  • 3. Image Basics with OpenCV
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      Introduction to Images and OpenCV Basics
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      Opening Image files in a notebook
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      Opening Image files with OpenCV
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      Drawing on Images - Part One - Basic Shapes
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      Drawing on Images Part Two - Text and Polygons
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      Direct Drawing on Images with a mouse - Part One
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      Direct Drawing on Images with a mouse - Part Two
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      Direct Drawing on Images with a mouse - Part Three
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      Image Basics Assessment
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      Image Basics Assessment Solutions
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  • 4. Image Processing
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      Introduction to Image Processing
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      Color Mappings
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      Blending and Pasting Images
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      Blending and Pasting Images Part Two - Masks
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      Image Thresholding
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      Blurring and Smoothing
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      Blurring and Smoothing - Part Two
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      Morphological Operators
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      Gradients
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      Histograms - Part One
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      Histograms - Part Two - Histogram Eqaulization
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      Histograms Part Three - Histogram Equalization
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      Image Processing Assessment
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      Image Processing Assessment Solutions
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  • 5. Video Basics with Python and OpenCV
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      Introduction to Video Basics
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      Connecting to Camera
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      Using Video Files
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      Drawing on Live Camera
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      Video Basics Assessment
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      Video Basics Assessment Solutions
      10m0s
  • 6. Object Detection with OpenCV and Python
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      Introduction to Object Detection
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      Template Matching
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      Corner Detection - Part One - Harris Corner Detection
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      Corner Detection - Part Two - Shi-Tomasi Detection
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      Edge Detection
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      Grid Detection
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      Contour Detection
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      Feature Matching - Part One
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      Feature Matching - Part Two
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      Watershed Algorithm - Part One
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      Watershed Algorithm - Part Two
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      Custom Seeds with Watershed Algorithm
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      Introduction to Face Detection
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      Face Detection with OpenCV
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      Detection Assessment
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      Detection Assessment Solutions
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  • 7. Object Tracking
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      Introduction to Object Tracking
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      Optical Flow
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      Optical Flow Coding with OpenCV - Part One
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      Optical Flow Coding with OpenCV - Part Two
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      MeanShift and CamShift Tracking Theory
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      MeanShift and CamShift Tracking with OpenCV
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      Overview of various Tracking API Methods
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      Tracking APIs with OpenCV
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  • 8. Deep Learning for Computer Vision
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      Introduction to Deep Learning for Computer Vision
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      Machine Learning Basics
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      Understanding Classification Metrics
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      Introduction to Deep Learning Topics
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      Understanding a Neuron
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      Understanding a Neural Network
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      Cost Functions
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      Gradient Descent and Back Propagation
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      Keras Basics
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      MNIST Data Overview
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      Convolutional Neural Networks Overview - Part One
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      Convolutional Neural Networks Overview - Part Two
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      Keras Convolutional Neural Networks with MNIST
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      Keras Convolutional Neural Networks with CIFAR-10
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      LINK FOR CATS AND DOGS ZIP
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      Deep Learning on Custom Images - Part One
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      Deep Learning on Custom Images - Part Two
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      Deep Learning and Convolutional Neural Networks Assessment
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      Deep Learning and Convolutional Neural Networks Assessment Solutions
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    • videocam
      Introduction to YOLO v3
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      YOLO Weights Download
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      YOLO v3 with Python
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  • 9. Capstone Project
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      Introduction to CapStone Project
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      Capstone Part One - Variables and Background function
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      Capstone Part Two - Segmentation
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      Capstone Part Three - Counting and ConvexHull
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      Capstone Part Four - Bringing it all together
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Authors

Kevin Gautama is a systems design and programming engineer with 16 years of expertise in the fields of electrical and electronics and information technology.

He teaches at the Hanoi University of Industry in the period 2003-2011 and he has a certificate of vocational training by the Ministry of Industry and Commerce and the Hanoi University of Industry.

From extensive design experience through numerous engineering projects, the author founded the Enziin Academy.

The Enziin Academy is a startup in the field of educational, it's core goal is to training design engineers in the fields technology related.

The Enziin Academy is headquartered in Stockholm-Sweden with an orientation operating multi-lingual and global.

The author's skills in IT:

  • Implementing the application infrastructure on Amazon's cloud computing platform.
  • Linux server system administration (Sysadmin).
  • Design load balancing and content distribution system.
  • MySQL database administration.
  • C/C++/C# Programming
  • Ruby and Ruby on Rails Programming
  • Python and Django Programming
  • The WPF/C# on the .NET Framework Programming
  • The PHP/JAVA Programming
  • Machine Learning and Expert System.
  • Internet of Things.

The author's skills in the fields of electric and electronic:

  • The design of popular CPU / MCU systems.
  • Design FPGA / CPLD system (Xilinx - Altera).
  • Design and programming of DSP systems (Texas Instruments).
  • Embedded ARM system design.
  • The RTOS Programming
  • Design and programming electronic power systems.
  • PLC - inverter - sensor - electric control cabinet industrial.
  • Control systems distributed connection with Server.

Read more...

Python for Computer Vision with OpenCV and Deep Learning


Python for Computer Vision with OpenCV and Deep Learning

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