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

4 sections • 21 lectures • 2hrs 12mins
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Build a Web App With Python and OpenCv : Image Editing App
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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 sections • 21 lectures • 2hrs 12mins

Anaconda download and installation - 07mins
Preview
Importing the libraries / packages - 04mins
Set a title and a subtitle for the app - 05mins
Create the "Detection" part - 13mins
Create the "About" part - 06mins
Images to use
Option 1: Gray-scaling - 11mins
Option 2: Contrast - 07mins
Option 3: Brightness - 03mins
Option 4: Blurriness - 04mins
Option 5: Sharpness - 04mins
Option 6: Original - 03mins
Set the selectbox features - 03mins
Detect faces (part 1) - 04mins
Set the haar cascade files - 04mins
Haar cascade files
Detect faces (part 2) - 17mins
Detect eyes - 04mins
Cartoonize an image (part 1) - 12mins
Cartoonize an image (part 2) - 04mins
Cannize an image - 07mins
  • 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
Image
Haithem Gasmi

Hi, My name is Haithem , I'm a data scientist and machine learning practitioner with an experience of more than 3 years in the industry.

I share my knowledge through online courses with tangible and impressive real world problems. I worked on many projects in different areas such as predective modelling, generative modelling, natural language processing and computer vision.

I love implementing my stuff with Python.

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