
Create the about section to display developer or app information using markdown links with the Tremlett library, linking to personal sites and social profiles, and testing with run-and-stop workflow.
Build a web app with Python and OpenCV that edits uploaded images using sidebar radio buttons for grayscale, contrast, brightness, and blur, with sliders to adjust each effect in detection.
Set up haar cascade files for face and eye detection with OpenCV's CascadeClassifier in a Python image editing app, configuring paths to enable detection, edge detection, and cartoon effects.
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