Python Image Processing – Make Instagram-Style Filters
Course
Online
Description
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Type
Course
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Methodology
Online
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Start date
Different dates available
In this course we’ll be building a photo filter editor which allows you to create filters such as those used in Instagram and Snapchat. This app allows you to load a photo, edit it’s contrast, brightness and gray-scale. You can also create and apply custom filters using this tool.
Theory sections are included, where concepts such as matrices, color models, brightness, contrast and convolution are explained in detail from a mathematical perspective. Practical sections include the installation of the Anaconda development environment, matrix operations and OpenCV. The photo editor is built from scratch using OpenCV UI.
Learning goals:
Matrices
Color Models
Brightness and Contrast
Convolution
OpenCV UI
Frameworks and tools covered: Python 3.6, Anaconda 5.2, NumPy 1.15, OpenCV-Python 3.4.1
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About this course
Basic to intermediate Python skills.
It is recommended to take this course as part of the Python Computer Vision Mini-Degree, which includes 8 courses on the fundamentals of coding with Python, and teaches core concepts in computer vision.
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Subjects
- Access
- Image
Course programme
Introduction 3:22
Introduction 3:22
3:22
Images 7:45
Images 7:45
7:45
Matrices 9:10
Matrices 9:10
9:10
Anaconda Development Environment 8:35
Anaconda Development Environment 8:35
8:35
Overview 3:04
Overview 3:04
3:04
Creating the UI - Part 1 20:12
Creating the UI - Part 1 20:12
20:12
Creating the UI - Part 2 5:57
Creating the UI - Part 2 5:57
5:57
Matrix Addition and Subtraction 6:54
Matrix Addition and Subtraction 6:54
6:54
Constraints on Matrix Addition and Subtraction 3:22
Constraints on Matrix Addition and Subtraction 3:22
3:22
Scalar Multiplication 7:23
Scalar Multiplication 7:23
7:23
Color Models 12:03
Color Models 12:03
12:03
Grayscale Filter 9:47
Grayscale Filter 9:47
9:47
Brightness and Contrast 14:20
Brightness and Contrast 14:20
14:20
Brightness and Contrast Filter 14:09
Brightness and Contrast Filter 14:09
14:09
Kernels 8:24
Kernels 8:24
8:24
Intro to Convolution 9:21
Intro to Convolution 9:21
9:21
Convolution Filters 19:21
Convolution Filters 19:21
19:21
Save Functionality 6:13
Save Functionality 6:13
6:13
Conclusion 2:14
Conclusion 2:14
2:14
Convolution Example (optional) 9:18
Convolution Example (optional) 9:18
9:18
Convolution Detailed Example (optional) 8:34
Convolution Detailed Example (optional) 8:34
8:34
Additional information
Python Image Processing – Make Instagram-Style Filters