imaging

KO | EN

gitlite — search

#react #ai #golang #rust #deep-learning #docker #nodejs #macos #java #windows #awesome #kubernetes #pytorch #ios

(★ 10)

simple image processing package in Go

imaging Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

![GitHub](https://img.shields.io/github/license/nao1215/imaging?style=flat-square)
[![Go Reference](https://pkg.go.dev/badge/github.com/nao1215/imaging.svg)](https://pkg.go.dev/github.com/nao1215/imaging)
![Coverage](https://raw.githubusercontent.com/nao1215/octocovs-central-repo/main/badges/nao1215/imaging/coverage.svg)
[![LinuxUnitTest](https://github.com/nao1215/imaging/actions/workflows/linux_test.yml/badge.svg)](https://github.com/nao1215/imaging/actions/workflows/linux_test.yml)
[![MacUnitTest](https://github.com/nao1215/imaging/actions/workflows/mac_test.yml/badge.svg)](https://github.com/nao1215/imaging/actions/workflows/mac_test.yml)
[![WindowsUnitTest](https://github.com/nao1215/imaging/actions/workflows/windows_test.yml/badge.svg)](https://github.com/nao1215/imaging/actions/workflows/windows_test.yml)
[![Go Report Card](https://goreportcard.com/badge/github.com/nao1215/imaging)](https://goreportcard.com/report/github.com/nao1215/imaging)
[![reviewdog](https://github.com/nao1215/imaging/actions/workflows/reviewdog.yml/badge.svg)](https://github.com/nao1215/imaging/actions/workflows/reviewdog.yml)

# Imaging
**This Repository is forked from [disintegration/imaging](https://github.com/disintegration/imaging).** The reason why I forked it is that the original version has been slowly updated. This repository makes bug fixes and multi-platforming.

Package imaging provides basic image processing functions (resize, rotate, crop, brightness/contrast adjustments, etc.).

All the image processing functions provided by the package accept any image type that implements `image.Image` interface
as an input, and return a new image of `*image.NRGBA` type (32bit RGBA colors, non-premultiplied alpha).

## Support OS / Go version
The following platforms and go versions have been unit tested.
- Linux
- Mac
- Windows
- Go ver 1.16 to 1.20

## Documentation

https://pkg.go.dev/github.com/nao1215/imaging

## Usage examples

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

### Sample command: gina
As a sample implementation of the nao1215/imaging package, I have prepared the **[gina](cmd/gina/README.md)** command.

### Image resizing

```go
// 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:
- `Lanczos` - A high-quality resampling filter for photographic images yielding sharp results.
- `CatmullRom` - A sharp cubic filter that is faster than Lanczos filter while providing similar results.
- `MitchellNetravali` - A cubic filter that produces smoother results with less ringing artifacts than CatmullRom.
- `Linear` - Bilinear resampling filter, produces smooth output. Faster than cubic filters.
- `Box` - Simple and fast averaging filter appropriate for downscaling. When upscaling it's similar to NearestNeighbor.
- `NearestNeighbor` - Fastest resampling filter, no antialiasing.

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**

Original image:

![srcImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/branches.png)

The same image resized from 600x400px to 150x100px using different resampling filters.
From faster (lower quality) to slower (higher quality):

Filter                    | Resize result
--------------------------|---------------------------------------------
`imaging.NearestNeighbor` | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_resize_nearest.png)
`imaging.Linear`          | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_resize_linear.png)
`imaging.CatmullRom`      | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_resize_catrom.png)
`imaging.Lanczos`         | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_resize_lanczos.png)

### Gaussian Blur

```go
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](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/flowers_small.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_blur_0.5.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_blur_1.5.png)

### Sharpening

```go
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](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/flowers_small.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_sharpen_0.5.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_sharpen_1.5.png)

### Gamma correction

```go
dstImage := imaging.AdjustGamma(srcImage, 0.75)
```

Original image                     | Gamma = 0.75                             | Gamma = 1.25
-----------------------------------|------------------------------------------|-----------------------------------------
![srcImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/flowers_small.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_gamma_0.75.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_gamma_1.25.png)

### Contrast adjustment

```go
dstImage := imaging.AdjustContrast(srcImage, 20)
```

Original image                     | Contrast = 15                              | Contrast = -15
-----------------------------------|--------------------------------------------|-------------------------------------------
![srcImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/flowers_small.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_contrast_p15.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_contrast_m15.png)

### Brightness adjustment

```go
dstImage := imaging.AdjustBrightness(srcImage, 20)
```

Original image                     | Brightness = 10                              | Brightness = -10
-----------------------------------|----------------------------------------------|---------------------------------------------
![srcImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/flowers_small.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_brightness_p10.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_brightness_m10.png)

### Saturation adjustment

```go
dstImage := imaging.AdjustSaturation(srcImage, 20)
```

Original image                     | Saturation = 30                              | Saturation = -30
-----------------------------------|----------------------------------------------|---------------------------------------------
![srcImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/flowers_small.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_saturation_p30.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_saturation_m30.png)

### Hue adjustment

```go
dstImage := imaging.AdjustHue(srcImage, 20)
```

Original image                     | Hue = 60                                     | Hue = -60
-----------------------------------|----------------------------------------------|---------------------------------------------
![srcImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/flowers_small.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_hue_p60.png) | ![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_hue_m60.png)

## FAQ

### Incorrect image orientation after processing (e.g. an image appears rotated after resizing)

Most probably, the given image contains the EXIF orientation tag.
The standard `image/*` packages do not support loading and saving
this kind of information. To fix the issue, try opening images with
the `AutoOrientation` decode option. If this option is set to `true`,
the image orientation is changed after decoding, according to the
orientation tag (if present). Here's the example:

```go
img, err := imaging.Open("test.jpg", imaging.AutoOrientation(true))
```

## Example code

```go
package main

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

"github.com/nao1215/imaging"
)

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

// Crop the original image to 300x300px size using the center anchor.
	src = imaging.CropAnchor(src, 300, 300, imaging.Center)

// Resize the cropped image to width = 200px preserving the aspect ratio.
	src = imaging.Resize(src, 200, 0, imaging.Lanczos)

// Create a blurred version of the image.
	img1 := imaging.Blur(src, 5)

// 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(400, 400, color.NRGBA{0, 0, 0, 0})
	dst = imaging.Paste(dst, img1, image.Pt(0, 0))
	dst = imaging.Paste(dst, img2, image.Pt(0, 200))
	dst = imaging.Paste(dst, img3, image.Pt(200, 0))
	dst = imaging.Paste(dst, img4, image.Pt(200, 200))

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

Output:

![dstImage](https://raw.githubusercontent.com/nao1215/imaging/main/testdata/out_example.jpg)

## License
The imaging library is licensed under the [MIT License](LICENSE).
Original author: [Disintegration](https://github.com/disintegration)

imaging

imaging Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

imaging

imaging Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README