Image Processing in Python
Image Processing in Python
Processing raster images with the Pillow library
About the Book
Pillow is the most popular Python image processing library. It provides many of the features found in imaging applications like Photoshop or GIMP, such as loading, saving, resizing, transforming images, as well as converting colours and applying filters, enhancements, and effects. This book will teach you how to use simple Python code to automate these functions using the Pillow library, so that your programs can incorporate advanced image processing. It provides a comprehensive guide to Pillow, in plain language and with lots of examples.
About the Author
Table of Contents
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Preface
- Who is this book for?
- About the author
- Keep in touch
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Introduction
- Versions
- Example sources on github
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Preface
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I Bitmap images
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1 Introduction to bitmap imaging
- 1.1 What is a bitmap image?
- 1.2 Spatial sampling
- 1.3 Colour representation
- 1.4 File formats
- 1.5 Vector images
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2 Computer colour
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2.1 Visible light
- 2.1.1 Frequency and wavelength
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2.2 What is colour?
- 2.2.1 Non-spectral colours
- 2.3 How we see colour
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2.4 The RGB colour model
- 2.4.1 Displaying colour
- 2.4.2 Representing RGB colours as a percentage
- 2.4.3 Floating point representation
- 2.4.4 Byte value representation
- 2.5 Colour resolution
- 2.6 Greyscale colour model
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2.7 The CMYK colour model
- 2.7.1 The K component
- 2.8 HSL/HSB colour models
- 2.9 HSL variants
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2.10 Perceptual colour models
- 2.10.1 CIE spaces
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2.11 Colour management
- 2.11.1 Gamuts
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2.1 Visible light
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3 Bitmap image data
- 3.1 Data layout
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3.2 8-bit per channel images
- 3.2.1 24-bit RGB
- 3.2.2 32-bit CMYK
- 3.2.3 8-bit greyscale
- 3.2.4 32-bit RGBA
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3.3 Bitmap data with fewer levels
- 3.3.1 8-bit RGB
- 3.3.2 16-bit RGB
- 3.3.3 Dithering
- 3.4 Bilevel images
- 3.5 Bitmap data with more levels
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3.6 Palette based images
- 3.6.1 Images with more than 256 colours
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3.7 Handling transparency
- 3.7.1 Alpha channel
- 3.7.2 Transparent palette entry
- 3.7.3 Transparent colour
- 3.8 Interlacing and alternate pixel ordering
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4 Image file formats
- 4.1 Why are there so many formats?
- 4.2 Image data and metadata
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4.3 Image compression
- 4.3.1 Lossless compression
- 4.3.2 Lossy compression
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4.4 Some common file formats
- 4.4.1 PNG format
- 4.4.2 JPEG format
- 4.4.3 GIF format
- 4.4.4 BMP format
- 4.5 Animation
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1 Introduction to bitmap imaging
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II Pillow library
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5 Introduction to Pillow
- 5.1 Pillow and PIL
- 5.2 Installing Pillow
- 5.3 Main features of Pillow
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6 Basic imaging
- 6.1 The Image class
- 6.2 Creating and displaying an image
- 6.3 Saving an image
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6.4 Handling colours
- 6.4.1 Converting strings to colours
- 6.5 Creating images
- 6.6 Opening an image
- 6.7 Image processing
- 6.8 Rotating an image
- 6.9 Creating a thumbnail
- 6.10 Image modes
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7 Image class
- 7.1 Example code
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7.2 Creating images
- 7.2.1 Image.new
- 7.2.2 Image.open
- 7.2.3 copy
- 7.2.4 Other methods
- 7.3 Saving images
- 7.4 Image generators
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7.5 Working with image bands
- 7.5.1 getbands
- 7.5.2 split
- 7.5.3 merge
- 7.5.4 getchannel
- 7.5.5 putalpha
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8 ImageOps module
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8.1 Image resizing functions
- 8.1.1 expand
- 8.1.2 crop
- 8.1.3 scale
- 8.1.4 pad
- 8.1.5 fit
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8.2 Image transformation functions
- 8.2.1 flip
- 8.2.2 mirror
- 8.2.3 exif-transpose
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8.3 Colour effects
- 8.3.1 grayscale
- 8.3.2 colorize
- 8.3.3 invert
- 8.3.4 posterize
- 8.3.5 solarize
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8.4 Image adjustment
- 8.4.1 autocontrast
- 8.4.2 equalize
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8.5 Deforming images
- 8.5.1 How deform works
- 8.5.2 getmesh
- 8.5.3 A wave transform
- 8.5.4 Other deformations
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8.1 Image resizing functions
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9 Image attributes and statistics
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9.1 Attributes
- 9.1.1 File size
- 9.1.2 File name
- 9.1.3 File format
- 9.1.4 Mode and bands
- 9.1.5 Palette
- 9.1.6 Info
- 9.1.7 Animation
- 9.1.8 EXIF tags
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9.2 Image statistics
- 9.2.1 Image histogram
- 9.2.2 Masking
- 9.2.3 Other Image statistics
- 9.2.4 ImageStat module
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9.1 Attributes
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10 Enhancing and filtering images
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10.1 ImageEnhance
- 10.1.1 Brightness
- 10.1.2 Contrast
- 10.1.3 Color
- 10.1.4 Sharpness
- 10.2 ImageFilter
- 10.3 Predefined filters
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10.4 Parameterised filters
- 10.4.1 Blurring functions
- 10.4.2 Unsharp masking
- 10.4.3 Ranking and averaging filters
- 10.5 Defining your own filters
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10.1 ImageEnhance
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11 Image compositing
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11.1 Simple blending
- 11.1.1 Image transparency
- 11.1.2 ImageChops blend function
- 11.1.3 ImageChops composite function
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11.2 Blend modes
- 11.2.1 Addition
- 11.2.2 Subtraction
- 11.2.3 Lighter and darker
- 11.2.4 Multiply and screen
- 11.2.5 Other blend modes
- 11.3 Logical combinations
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11.1 Simple blending
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12 Drawing on images
- 12.1 Coordinate system
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12.2 Drawing shapes
- 12.2.1 Drawing rectangles
- 12.2.2 Drawing other shapes
- 12.2.3 Points
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12.3 Handling text
- 12.3.1 Drawing simple text
- 12.3.2 Font and text metrics
- 12.3.3 Anchoring
- 12.3.4 Drawing multiline text
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12.4 Paths
- 12.4.1 Drawing a path
- 12.4.2 Transforming paths
- 12.4.3 Mapping points
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13 Accessing pixel data
- 13.1 Processing an image
- 13.2 Creating an image
- 13.3 Performance
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14 Integrating Pillow with other libraries
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14.1 NumPy integration
- 14.1.1 Converting a Pillow image to Numpy
- 14.1.2 Image data in a NumPy array
- 14.1.3 Modifying the NumPy image
- 14.1.4 Converting a NumPy array to a Pillow image
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14.1 NumPy integration
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5 Introduction to Pillow
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III Reference
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15 Pillow colour representation
- 15.1 Hexadecimal colour specifiers
- 15.2 RGB functions
- 15.3 HSL functions
- 15.4 HSV functions
- 15.5 Named colours
- 15.6 Example
- 15.7 Image modes
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More books from this author
- Numpy Recipes
- Computer Graphics in Python with Pycairo
- Functional Programming in Python
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15 Pillow colour representation
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