diff options
Diffstat (limited to 'Godeps/_workspace/src/github.com/disintegration/imaging/README.md')
| -rw-r--r-- | Godeps/_workspace/src/github.com/disintegration/imaging/README.md | 194 |
1 files changed, 0 insertions, 194 deletions
diff --git a/Godeps/_workspace/src/github.com/disintegration/imaging/README.md b/Godeps/_workspace/src/github.com/disintegration/imaging/README.md deleted file mode 100644 index 25d836cef..000000000 --- a/Godeps/_workspace/src/github.com/disintegration/imaging/README.md +++ /dev/null @@ -1,194 +0,0 @@ -# Imaging
-
-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
-```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:
-- `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**
-
-Original image. Will be resized from 512x512px to 128x128px.
-
-
-
-Filter | Resize result
----|---
-`imaging.NearestNeighbor` | 
-`imaging.Box` | 
-`imaging.Linear` | 
-`imaging.MitchellNetravali` | 
-`imaging.CatmullRom` | 
-`imaging.Gaussian` | 
-`imaging.Lanczos` | 
-
-**Resize functions comparison**
-
-Original image:
-
-
-
-Resize the image to width=100px and height=100px:
-
-```go
-dstImage := imaging.Resize(srcImage, 100, 100, imaging.Lanczos)
-```
-
-
-Resize the image to width=100px preserving the aspect ratio:
-
-```go
-dstImage := imaging.Resize(srcImage, 100, 0, imaging.Lanczos)
-```
-
-
-Resize the image to fit the 100x100px boundng box preserving the aspect ratio:
-
-```go
-dstImage := imaging.Fit(srcImage, 100, 100, imaging.Lanczos)
-```
-
-
-Resize and crop the image with a center anchor point to fill the 100x100px area:
-
-```go
-dstImage := imaging.Fill(srcImage, 100, 100, imaging.Center, imaging.Lanczos)
-```
-
-
-### 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
----|---|---
- |  | 
-
-### Sharpening
-```go
-dstImage := imaging.Sharpen(srcImage, 0.5)
-```
-
-Uses gaussian function internally. Sigma parameter allows to control the strength of the sharpening effect.
-
-Original image | Sigma = 0.5 | Sigma = 1.5
----|---|---
- |  | 
-
-### Gamma correction
-```go
-dstImage := imaging.AdjustGamma(srcImage, 0.75)
-```
-
-Original image | Gamma = 0.75 | Gamma = 1.25
----|---|---
- |  | 
-
-### Contrast adjustment
-```go
-dstImage := imaging.AdjustContrast(srcImage, 20)
-```
-
-Original image | Contrast = 20 | Contrast = -20
----|---|---
- |  | 
-
-### Brightness adjustment
-```go
-dstImage := imaging.AdjustBrightness(srcImage, 20)
-```
-
-Original image | Brightness = 20 | Brightness = -20
----|---|---
- |  | 
-
-
-### Complete code example
-Here is the code example that loads several images, makes thumbnails of them
-and combines them together side-by-side.
-
-```go
-package main
-
-import (
- "image"
- "image/color"
-
- "github.com/disintegration/imaging"
-)
-
-func main() {
-
- // input files
- files := []string{"01.jpg", "02.jpg", "03.jpg"}
-
- // load images and make 100x100 thumbnails of them
- var thumbnails []image.Image
- for _, file := range files {
- img, err := imaging.Open(file)
- if err != nil {
- panic(err)
- }
- thumb := imaging.Thumbnail(img, 100, 100, imaging.CatmullRom)
- thumbnails = append(thumbnails, thumb)
- }
-
- // create a new blank image
- dst := imaging.New(100*len(thumbnails), 100, color.NRGBA{0, 0, 0, 0})
-
- // paste thumbnails into the new image side by side
- for i, thumb := range thumbnails {
- dst = imaging.Paste(dst, thumb, image.Pt(i*100, 0))
- }
-
- // save the combined image to file
- err := imaging.Save(dst, "dst.jpg")
- if err != nil {
- panic(err)
- }
-}
-```
|