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

Requirements
Just basic python

Description
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

Who this course is for
Python developers who want to extand their knowledge on deploying efficient modern web apps using streamlit and OpenCv
Programmers who want to apply image processing techniques into a tangible application that can be used by everyone