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Build a Web App With Python and OpenCv : Image Editing App

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  • 3,040 Students
  • Updated 11/2021
4.8
(30 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
2 Hour(s) 12 Minute(s)
Language
English
Taught by
Gasmi Haithem
Rating
4.8
(30 Ratings)

Course Overview

Build a Web App With Python and OpenCv : Image Editing App

Build a modern prototype of an image editing web application with streamlit and OpenCv

In this course you are going to build a modern prototype of a web application : image editing app using streamlit which is a python-based framework that provides you with all the tools to build your app from scratch in a simple and fast way. Through this course you are going to learn how to implement different image processing techniques like : gray-scaling, contrast, brightness, sharpness and blurriness and connect them to your application giving the hand to users to choose and control the degree of each one. You will also, learn how to create functions that allow you to detect faces and eyes in images, functions that create cartoon version of your images and other to detect edges of different objects and regions in images.

The content of this course: 

Section 1: First steps :

                 - Anaconda download and installation

                 - Importing the libraries / packages

Section 2 : Set up the main part of the app

                  - Setting a title and a subtitle for the app

                  - Create the " Detection " part

                  - Create the " About " part

Section 3 : Connect the image processing techniques to the app

                  - Option 1 : Gray-scaling

                  - Option 2 : Contrast

                  - Option 3 : Brightness

                  - Option 4 : Blurriness

                  - Option 5 : Sharpness

                  - Option 6 : Original

Section 4 : Set up the main part of the app

                 - Set the features selectbox

                 - Detect faces (part 1)

                 - Set the haar cascade files

                 - Detect faces (part 2)

                 - Detect eyes

                 - Cartoonize an image (part 1)

                 - Cartoonize an image (part 2)

                 - Cannize an image

Course Content

  • 4 section(s)
  • 21 lecture(s)
  • Section 1 First steps
  • Section 2 Set up the main part of the app
  • Section 3 Connect the image processing techniques to the app
  • Section 4 Face detection / Eye detection / Cartoonizing / Cannizing

What You’ll Learn

  • Create a web application using an efficient python based framework : Streamlit
  • Create and set different widgets on your app: selectboxes, buttons, radio Buttons, sliders, image uploaders, markdowns, message boxes, ...etc
  • Apply image editing techniques (gray-scaling, contrast, brightness, blurriness, sharpness) to an uploaded image
  • Detect faces and eyes in an image using OpenCv
  • Use the different methods and functions provided by streamlit to display your images in the app
  • Cartoonize images and detect edges by applying OpenCV functions


Reviews

  • H
    Hamid Aminirad
    5.0

    A very pregnant course. I really liked it. No sidetalks or the like, the course keeps a straight line and explains very well on how to use opencv with streamlit. Keep up the good work :)

  • D
    Deb
    5.0

    Good walkthrough

  • V
    Varun Lobo
    5.0

    so far this is a great intro to streamlit and openCV. i like the step by step information provided by the instructor.

  • S
    Stella Phillips
    5.0

    I found this tutorial very clear and much easy explanations.

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