The OpenCV [1] library contains most of the functions we need for working with images. Handling images in programming requires a different intuition than handling text data. An image is made up of pixels. It looks like a spreadsheet full of cells with numerical values when zoomed in. Each pixel usually contains a value ranging between 0 to 255. The value indicates the degree of brightness for the color it is assigned to. So, how do we work with images in Python? We first need to load them as NumPy arrays, converting all image pixels into numerical values. Only then we can use different computer vision techniques to manipulate them.
Author: Hwei Geok Ng
In this tutorial, we are going to get our hands dirty experimenting with images using OpenCV. We will look at techniques like color conversion, resizing, blending, blurring, and thresholding. Getting your image data right is a half-way success for a useful machine learning model. Intrigued? Let’s get started.
Timestamp:
00:00 - Introduction
01:58 - Install and Import Required Modules
04:28 - Load Image and Convert Color Channels
08:24 - Resize Image
12:17 - Blend Images
16:15 - Blur Image
20:31 - Threshold Image
►► Do you want to thrive as a self-employed Python freelancer controlling your own time, income, and work schedule?
⁉️ Do you have a question? Leave a comment and we will answer as soon as possible!
⏰ Subscribe to the channel, never miss a new video!
🐍 Did you know? Finxter is one of the top 10 Python Blogs on the internet!
🚀 More about Python & Freelancing:
#finxter #python
Do you want to thrive as a self-employed Python freelancer controlling your own time, income, and work schedule? Check out our Python freelancer resources:
Finxter Python Freelancer Course:
Finxter Python Freelancer Webinar:
Leaving the Rat Race with Python (Book):