/Computer-Vision-with-Python-Udemy

This course is tailor made for an individual who wishes to transition quickly from an absolute beginner to a Computer Vision expert in a few weeks. The most difficult concepts are explained in plain and simple manner using code examples.

Primary LanguageJupyter NotebookMIT LicenseMIT

Computer-Vision-with-Python-Udemy

forthebadge - forthebadge - forthebadge

Description

  • Introduction course to Computer Vision with Python
  • Make Computer Vision Apps?
  • Learn Computer Vision theory?

This course is tailor made for an individual who wishes to transition quickly from an absolute beginner to a Computer Vision expert in a few weeks. The most difficult concepts are explained in plain and simple manner using code examples.

  • We will build:
    • Multimedia apps
    • Image Similarity apps
    • Obect Detection apps
    • Face detection apps
    • Reverse Image Search app

Course Content

  • Numpy and Image Basics

    • NumPy Arrays
    • Image and NumPy
    • NumPu and Image Assessment

  • Image Basics with OpenCV

    • Opening Image Files in a NoteBook
    • Opening Image Files OpenCV
    • Drawing On Images
    • Direct Drawing with Mouse
    • Image Basics Assessment

  • Image Processing

    • Color Mappings
    • Blending and Pasting Images
    • Image Thresholding
    • Blurring and Smoothing
    • Morphological Operators
    • Gradients
    • Histograms
    • Image Processing Assessment

  • Video Basics

    • Connecting to Camera
    • Using Video Files
    • Drawing on Live Camera
    • Video Basics Assessment

  • Object Detection

    • Template Matching
    • Corner Detection
    • Edge Detection
    • Grid Detection
    • Contour Detection
    • Feature Matching
    • Watershed Algorithm
    • Custom Seeds with WaterShed Algo
    • Face Detection
    • Detection Assessment

  • Object Tracking

    • Optical Flow
    • MeanShift Tracking
    • CamShift Tracking
    • Tracking APIs
    • Meanshift

  • Deep Learning Computer Vision

    • Keras Basics
    • Keras CNN MNIST
    • Keras CNN CIFAR-10
    • Deep Learning Custom Images
    • DL-CV_Assessment

  • YOLO Algorithm

    • YOLO Object Detection
    • Darknet53
    • Yolo Model

  • Capstone Project

    • Finger Counter Application

What I learnt

  • 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.

Author

Ashlesh Khajbage

Instructor

Jose

Jose Portilla

Head of Data Science, Pierian Data Inc.

Reference Links

  1. Course Reference Thumbnail

Course Description

Udemy

  1. Certificate

Certificate

  1. I am Extremely ThankFull For

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