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
4sections
21lessons
2h 12mtotal
0reviews
What you will get
About this course
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
Learning objectives
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
4 sections
Curriculum
First steps2 lessons
Anaconda download and installation
7m
Importing the libraries / packages
4m
Set up the main part of the app3 lessons
Set a title and a subtitle for the app
5m
Create the "Detection" part
13m
Create the "About" part
6m
Connect the image processing techniques to the app7 lessons
Images to use
Option 1: Gray-scaling
11m
Option 2: Contrast
7m
Option 3: Brightness
3m
Option 4: Blurriness
4m
Option 5: Sharpness
4m
Option 6: Original
3m
Face detection / Eye detection / Cartoonizing / Cannizing9 lessons
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.