imaging

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README

Imaging

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Package imaging provides basic image manipulation functions (resize, rotate, flip, crop, etc.). This package is based on the standard Go image package and works best along with it.

Image manipulation functions provided by the package take any image type that implements image.Image interface as an input, and return a new image of *image.NRGBA type (32bit RGBA colors, not premultiplied by alpha).

Installation

Imaging requires Go version 1.2 or greater.

go get -u github.com/disintegration/imaging

Documentation

http://godoc.org/github.com/disintegration/imaging

Usage examples

A few usage examples can be found below. See the documentation for the full list of supported functions.

Image resizing
// Resize srcImage to size = 128x128px using the Lanczos filter.
dstImage128 := imaging.Resize(srcImage, 128, 128, imaging.Lanczos)

// Resize srcImage to width = 800px preserving the aspect ratio.
dstImage800 := imaging.Resize(srcImage, 800, 0, imaging.Lanczos)

// Scale down srcImage to fit the 800x600px bounding box.
dstImageFit := imaging.Fit(srcImage, 800, 600, imaging.Lanczos)

// Resize and crop the srcImage to fill the 100x100px area.
dstImageFill := imaging.Fill(srcImage, 100, 100, imaging.Center, imaging.Lanczos)

Imaging supports image resizing using various resampling filters. The most notable ones:

  • NearestNeighbor - Fastest resampling filter, no antialiasing.
  • Box - Simple and fast averaging filter appropriate for downscaling. When upscaling it's similar to NearestNeighbor.
  • Linear - Bilinear filter, smooth and reasonably fast.
  • MitchellNetravali - А smooth bicubic filter.
  • CatmullRom - A sharp bicubic filter.
  • Gaussian - Blurring filter that uses gaussian function, useful for noise removal.
  • Lanczos - High-quality resampling filter for photographic images yielding sharp results, but it's slower than cubic filters.

The full list of supported filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali, CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine. Custom filters can be created using ResampleFilter struct.

Resampling filters comparison

The original image.

srcImage

The same image resized from 512x512px to 128x128px using different resampling filters. From faster (lower quality) to slower (higher quality):

Filter Resize result
imaging.NearestNeighbor dstImage
imaging.Linear dstImage
imaging.CatmullRom dstImage
imaging.Lanczos dstImage
Gaussian Blur
dstImage := imaging.Blur(srcImage, 0.5)

Sigma parameter allows to control the strength of the blurring effect.

Original image Sigma = 0.5 Sigma = 1.5
srcImage dstImage dstImage
Sharpening
dstImage := imaging.Sharpen(srcImage, 0.5)

Sharpen uses gaussian function internally. Sigma parameter allows to control the strength of the sharpening effect.

Original image Sigma = 0.5 Sigma = 1.5
srcImage dstImage dstImage
Gamma correction
dstImage := imaging.AdjustGamma(srcImage, 0.75)
Original image Gamma = 0.75 Gamma = 1.25
srcImage dstImage dstImage
Contrast adjustment
dstImage := imaging.AdjustContrast(srcImage, 20)
Original image Contrast = 10 Contrast = -10
srcImage dstImage dstImage
Brightness adjustment
dstImage := imaging.AdjustBrightness(srcImage, 20)
Original image Brightness = 10 Brightness = -10
srcImage dstImage dstImage

Example code

package main

import (
	"image"
	"image/color"
	"log"

	"github.com/disintegration/imaging"
)

func main() {
	// Open the test image.
	src, err := imaging.Open("testdata/lena_512.png")
	if err != nil {
		log.Fatalf("Open failed: %v", err)
	}

	// Crop the original image to 350x350px size using the center anchor.
	src = imaging.CropAnchor(src, 350, 350, imaging.Center)

	// Resize the cropped image to width = 256px preserving the aspect ratio.
	src = imaging.Resize(src, 256, 0, imaging.Lanczos)

	// Create a blurred version of the image.
	img1 := imaging.Blur(src, 2)

	// Create a grayscale version of the image with higher contrast and sharpness.
	img2 := imaging.Grayscale(src)
	img2 = imaging.AdjustContrast(img2, 20)
	img2 = imaging.Sharpen(img2, 2)

	// Create an inverted version of the image.
	img3 := imaging.Invert(src)

	// Create an embossed version of the image using a convolution filter.
	img4 := imaging.Convolve3x3(
		src,
		[9]float64{
			-1, -1, 0,
			-1, 1, 1,
			0, 1, 1,
		},
		nil,
	)

	// Create a new image and paste the four produced images into it.
	dst := imaging.New(512, 512, color.NRGBA{0, 0, 0, 0})
	dst = imaging.Paste(dst, img1, image.Pt(0, 0))
	dst = imaging.Paste(dst, img2, image.Pt(0, 256))
	dst = imaging.Paste(dst, img3, image.Pt(256, 0))
	dst = imaging.Paste(dst, img4, image.Pt(256, 256))

	// Save the resulting image using JPEG format.
	err = imaging.Save(dst, "testdata/out_example.jpg")
	if err != nil {
		log.Fatalf("Save failed: %v", err)
	}
}

Output:

dstImage

Documentation

Overview

Package imaging provides basic image manipulation functions (resize, rotate, flip, crop, etc.). This package is based on the standard Go image package and works best along with it.

Image manipulation functions provided by the package take any image type that implements `image.Image` interface as an input, and return a new image of `*image.NRGBA` type (32bit RGBA colors, not premultiplied by alpha).

Example 
package main

import (
	"image"
	"image/color"
	"log"

	"github.com/disintegration/imaging"
)

func main() {
	// Open the test image.
	src, err := imaging.Open("testdata/lena_512.png")
	if err != nil {
		log.Fatalf("Open failed: %v", err)
	}

	// Crop the original image to 350x350px size using the center anchor.
	src = imaging.CropAnchor(src, 350, 350, imaging.Center)

	// Resize the cropped image to width = 256px preserving the aspect ratio.
	src = imaging.Resize(src, 256, 0, imaging.Lanczos)

	// Create a blurred version of the image.
	img1 := imaging.Blur(src, 2)

	// Create a grayscale version of the image with higher contrast and sharpness.
	img2 := imaging.Grayscale(src)
	img2 = imaging.AdjustContrast(img2, 20)
	img2 = imaging.Sharpen(img2, 2)

	// Create an inverted version of the image.
	img3 := imaging.Invert(src)

	// Create an embossed version of the image using a convolution filter.
	img4 := imaging.Convolve3x3(
		src,
		[9]float64{
			-1, -1, 0,
			-1, 1, 1,
			0, 1, 1,
		},
		nil,
	)

	// Create a new image and paste the four produced images into it.
	dst := imaging.New(512, 512, color.NRGBA{0, 0, 0, 0})
	dst = imaging.Paste(dst, img1, image.Pt(0, 0))
	dst = imaging.Paste(dst, img2, image.Pt(0, 256))
	dst = imaging.Paste(dst, img3, image.Pt(256, 0))
	dst = imaging.Paste(dst, img4, image.Pt(256, 256))

	// Save the resulting image using JPEG format.
	err = imaging.Save(dst, "testdata/out_example.jpg")
	if err != nil {
		log.Fatalf("Save failed: %v", err)
	}
}

Output:

Index

Examples

Constants

This section is empty.

Variables

View Source 
var (
	// ErrUnsupportedFormat means the given image format (or file extension) is unsupported.
	ErrUnsupportedFormat = errors.New("imaging: unsupported image format")
)

Functions

func AdjustBrightness 

func AdjustBrightness(img image.Image, percentage float64) *image.NRGBA

AdjustBrightness changes the brightness of the image using the percentage parameter and returns the adjusted image. The percentage must be in range (-100, 100). The percentage = 0 gives the original image. The percentage = -100 gives solid black image. The percentage = 100 gives solid white image.

Examples: 

dstImage = imaging.AdjustBrightness(srcImage, -15) // decrease image brightness by 15%
dstImage = imaging.AdjustBrightness(srcImage, 10) // increase image brightness by 10%

func AdjustContrast 

func AdjustContrast(img image.Image, percentage float64) *image.NRGBA

AdjustContrast changes the contrast of the image using the percentage parameter and returns the adjusted image. The percentage must be in range (-100, 100). The percentage = 0 gives the original image. The percentage = -100 gives solid grey image.

Examples: 

dstImage = imaging.AdjustContrast(srcImage, -10) // decrease image contrast by 10%
dstImage = imaging.AdjustContrast(srcImage, 20) // increase image contrast by 20%

func AdjustFunc 

func AdjustFunc(img image.Image, fn func(c color.NRGBA) color.NRGBA) *image.NRGBA

AdjustFunc applies the fn function to each pixel of the img image and returns the adjusted image.

Example: 

dstImage = imaging.AdjustFunc(
	srcImage,
	func(c color.NRGBA) color.NRGBA {
		// shift the red channel by 16
		r := int(c.R) + 16
		if r > 255 {
			r = 255
		}
		return color.NRGBA{uint8(r), c.G, c.B, c.A}
	}
)

func AdjustGamma 

func AdjustGamma(img image.Image, gamma float64) *image.NRGBA

AdjustGamma performs a gamma correction on the image and returns the adjusted image. Gamma parameter must be positive. Gamma = 1.0 gives the original image. Gamma less than 1.0 darkens the image and gamma greater than 1.0 lightens it.

Example: 

dstImage = imaging.AdjustGamma(srcImage, 0.7)

func AdjustSigmoid 

func AdjustSigmoid(img image.Image, midpoint, factor float64) *image.NRGBA

AdjustSigmoid changes the contrast of the image using a sigmoidal function and returns the adjusted image. It's a non-linear contrast change useful for photo adjustments as it preserves highlight and shadow detail. The midpoint parameter is the midpoint of contrast that must be between 0 and 1, typically 0.5. The factor parameter indicates how much to increase or decrease the contrast, typically in range (-10, 10). If the factor parameter is positive the image contrast is increased otherwise the contrast is decreased.

Examples: 

dstImage = imaging.AdjustSigmoid(srcImage, 0.5, 3.0) // increase the contrast
dstImage = imaging.AdjustSigmoid(srcImage, 0.5, -3.0) // decrease the contrast

func Blur 

func Blur(img image.Image, sigma float64) *image.NRGBA

Blur produces a blurred version of the image using a Gaussian function. Sigma parameter must be positive and indicates how much the image will be blurred.

Usage example: 

dstImage := imaging.Blur(srcImage, 3.5)

func Clone 

func Clone(img image.Image) *image.NRGBA

Clone returns a copy of the given image.

func Convolve3x3 added in v1.1.0 

func Convolve3x3(img image.Image, kernel [9]float64, options *ConvolveOptions) *image.NRGBA

Convolve3x3 convolves the image with the specified 3x3 convolution kernel. Default parameters are used if a nil *ConvolveOptions is passed.

func Convolve5x5 added in v1.1.0 

func Convolve5x5(img image.Image, kernel [25]float64, options *ConvolveOptions) *image.NRGBA

Convolve5x5 convolves the image with the specified 5x5 convolution kernel. Default parameters are used if a nil *ConvolveOptions is passed.

func Crop 

func Crop(img image.Image, rect image.Rectangle) *image.NRGBA

Crop cuts out a rectangular region with the specified bounds from the image and returns the cropped image.

func CropAnchor 

func CropAnchor(img image.Image, width, height int, anchor Anchor) *image.NRGBA

CropAnchor cuts out a rectangular region with the specified size from the image using the specified anchor point and returns the cropped image.

func CropCenter 

func CropCenter(img image.Image, width, height int) *image.NRGBA

CropCenter cuts out a rectangular region with the specified size from the center of the image and returns the cropped image.

func Decode 

func Decode(r io.Reader) (image.Image, error)

Decode reads an image from r.

func Encode 

func Encode(w io.Writer, img image.Image, format Format) error

Encode writes the image img to w in the specified format (JPEG, PNG, GIF, TIFF or BMP).

func Fill 

func Fill(img image.Image, width, height int, anchor Anchor, filter ResampleFilter) *image.NRGBA

Fill scales the image to the smallest possible size that will cover the specified dimensions, crops the resized image to the specified dimensions using the given anchor point and returns the transformed image.

Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali, CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine.

Usage example: 

dstImage := imaging.Fill(srcImage, 800, 600, imaging.Center, imaging.Lanczos)

func Fit 

func Fit(img image.Image, width, height int, filter ResampleFilter) *image.NRGBA

Fit scales down the image using the specified resample filter to fit the specified maximum width and height and returns the transformed image.

Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali, CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine.

Usage example: 

dstImage := imaging.Fit(srcImage, 800, 600, imaging.Lanczos)

func FlipH 

func FlipH(img image.Image) *image.NRGBA

FlipH flips the image horizontally (from left to right) and returns the transformed image.

func FlipV 

func FlipV(img image.Image) *image.NRGBA

FlipV flips the image vertically (from top to bottom) and returns the transformed image.

func Grayscale 

func Grayscale(img image.Image) *image.NRGBA

Grayscale produces grayscale version of the image.

func Histogram 

func Histogram(img image.Image) [256]float64

Histogram returns a normalized histogram of an image.

Resulting histogram is represented as an array of 256 floats, where histogram[i] is a probability of a pixel being of a particular luminance i.

func Invert 

func Invert(img image.Image) *image.NRGBA

Invert produces inverted (negated) version of the image.

func New 

func New(width, height int, fillColor color.Color) *image.NRGBA

New creates a new image with the specified width and height, and fills it with the specified color.

func Open 

func Open(filename string) (image.Image, error)

Open loads an image from file

func Overlay 

func Overlay(background, img image.Image, pos image.Point, opacity float64) *image.NRGBA

Overlay draws the img image over the background image at given position and returns the combined image. Opacity parameter is the opacity of the img image layer, used to compose the images, it must be from 0.0 to 1.0.

Usage examples: 

// draw the sprite over the background at position (50, 50)
dstImage := imaging.Overlay(backgroundImage, spriteImage, image.Pt(50, 50), 1.0)

// blend two opaque images of the same size
dstImage := imaging.Overlay(imageOne, imageTwo, image.Pt(0, 0), 0.5)

func OverlayCenter 

func OverlayCenter(background, img image.Image, opacity float64) *image.NRGBA

OverlayCenter overlays the img image to the center of the background image and returns the combined image. Opacity parameter is the opacity of the img image layer, used to compose the images, it must be from 0.0 to 1.0.

func Paste 

func Paste(background, img image.Image, pos image.Point) *image.NRGBA

Paste pastes the img image to the background image at the specified position and returns the combined image.

func PasteCenter 

func PasteCenter(background, img image.Image) *image.NRGBA

PasteCenter pastes the img image to the center of the background image and returns the combined image.

func Resize 

func Resize(img image.Image, width, height int, filter ResampleFilter) *image.NRGBA

Resize resizes the image to the specified width and height using the specified resampling filter and returns the transformed image. If one of width or height is 0, the image aspect ratio is preserved.

Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali, CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine.

Usage example: 

dstImage := imaging.Resize(srcImage, 800, 600, imaging.Lanczos)

func Rotate180 

func Rotate180(img image.Image) *image.NRGBA

Rotate180 rotates the image 180 degrees counterclockwise and returns the transformed image.

func Rotate270 

func Rotate270(img image.Image) *image.NRGBA

Rotate270 rotates the image 270 degrees counterclockwise and returns the transformed image.

func Rotate90 

func Rotate90(img image.Image) *image.NRGBA

Rotate90 rotates the image 90 degrees counterclockwise and returns the transformed image.

func Save 

func Save(img image.Image, filename string) (err error)

Save saves the image to file with the specified filename. The format is determined from the filename extension: "jpg" (or "jpeg"), "png", "gif", "tif" (or "tiff") and "bmp" are supported.

func Sharpen 

func Sharpen(img image.Image, sigma float64) *image.NRGBA

Sharpen produces a sharpened version of the image. Sigma parameter must be positive and indicates how much the image will be sharpened.

Usage example: 

dstImage := imaging.Sharpen(srcImage, 3.5)

func Thumbnail 

func Thumbnail(img image.Image, width, height int, filter ResampleFilter) *image.NRGBA

Thumbnail scales the image up or down using the specified resample filter, crops it to the specified width and hight and returns the transformed image.

Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali, CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine.

Usage example: 

dstImage := imaging.Thumbnail(srcImage, 100, 100, imaging.Lanczos)

func Transpose 

func Transpose(img image.Image) *image.NRGBA

Transpose flips the image horizontally and rotates 90 degrees counter-clockwise.

func Transverse 

func Transverse(img image.Image) *image.NRGBA

Transverse flips the image vertically and rotates 90 degrees counter-clockwise.

Types

type Anchor 

type Anchor int

Anchor is the anchor point for image alignment. 

const (
	Center Anchor = iota
	TopLeft
	Top
	TopRight
	Left
	Right
	BottomLeft
	Bottom
	BottomRight
)

Anchor point positions.

type ConvolveOptions added in v1.1.0 

type ConvolveOptions struct {
	// If Normalize is true the kernel is normalized before convolution.
	Normalize bool

	// If Abs is true the absolute value of each color channel is taken after convolution.
	Abs bool

	// Bias is added to each color channel value after convolution.
	Bias int
}

ConvolveOptions are convolution parameters.

type Format 

type Format int

Format is an image file format. 

const (
	JPEG Format = iota
	PNG
	GIF
	TIFF
	BMP
)

Image file formats.

func (Format) String 

func (f Format) String() string

type ResampleFilter 

type ResampleFilter struct {
	Support float64
	Kernel  func(float64) float64
}

ResampleFilter is a resampling filter struct. It can be used to define custom filters.

Supported resample filters: NearestNeighbor, Box, Linear, Hermite, MitchellNetravali, CatmullRom, BSpline, Gaussian, Lanczos, Hann, Hamming, Blackman, Bartlett, Welch, Cosine. 

General filter recommendations:

- Lanczos
	Probably the best resampling filter for photographic images yielding sharp results,
	but it's slower than cubic filters (see below).

- CatmullRom
	A sharp cubic filter. It's a good filter for both upscaling and downscaling if sharp results are needed.

- MitchellNetravali
	A high quality cubic filter that produces smoother results with less ringing than CatmullRom.

- BSpline
	A good filter if a very smooth output is needed.

- Linear
	Bilinear interpolation filter, produces reasonably good, smooth output. It's faster than cubic filters.

- Box
	Simple and fast resampling filter appropriate for downscaling.
	When upscaling it's similar to NearestNeighbor.

- NearestNeighbor
	Fastest resample filter, no antialiasing at all. Rarely used.

var BSpline ResampleFilter

BSpline is a smooth cubic filter (BC-spline; B=1; C=0). 

var Bartlett ResampleFilter

Bartlett is a Bartlett-windowed sinc filter (3 lobes). 

var Blackman ResampleFilter

Blackman is a Blackman-windowed sinc filter (3 lobes). 

var Box ResampleFilter

Box filter (averaging pixels). 

var CatmullRom ResampleFilter

CatmullRom is a Catmull-Rom - sharp cubic filter (BC-spline; B=0; C=0.5). 

var Cosine ResampleFilter

Cosine is a Cosine-windowed sinc filter (3 lobes). 

var Gaussian ResampleFilter

Gaussian is a Gaussian blurring Filter. 

var Hamming ResampleFilter

Hamming is a Hamming-windowed sinc filter (3 lobes). 

var Hann ResampleFilter

Hann is a Hann-windowed sinc filter (3 lobes). 

var Hermite ResampleFilter

Hermite cubic spline filter (BC-spline; B=0; C=0). 

var Lanczos ResampleFilter

Lanczos filter (3 lobes). 

var Linear ResampleFilter

Linear filter. 

var MitchellNetravali ResampleFilter

MitchellNetravali is Mitchell-Netravali cubic filter (BC-spline; B=1/3; C=1/3). 

var NearestNeighbor ResampleFilter

NearestNeighbor is a nearest-neighbor filter (no anti-aliasing). 

var Welch ResampleFilter

Welch is a Welch-windowed sinc filter (parabolic window, 3 lobes).

Source Files

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