Update dependencies (#1610)

* Update dependencies

* Update module to go 1.17

1 files changed, 0 insertions, 226 deletions

diff --git a/vendor/github.com/disintegration/imaging/README.md b/vendor/github.com/disintegration/imaging/README.md
deleted file mode 100644
index a1fd764d..00000000
--- a/vendor/github.com/disintegration/imaging/README.md
+++ /dev/null
@@ -1,226 +0,0 @@
-# Imaging

-

-[![GoDoc](https://godoc.org/github.com/disintegration/imaging?status.svg)](https://godoc.org/github.com/disintegration/imaging)

-[![Build Status](https://travis-ci.org/disintegration/imaging.svg?branch=master)](https://travis-ci.org/disintegration/imaging)

-[![Coverage Status](https://coveralls.io/repos/github/disintegration/imaging/badge.svg?branch=master&service=github)](https://coveralls.io/github/disintegration/imaging?branch=master)

-[![Go Report Card](https://goreportcard.com/badge/github.com/disintegration/imaging)](https://goreportcard.com/report/github.com/disintegration/imaging)

-

-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).

-

-## Installation

-

-    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:

-- `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](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](testdata/out_resize_nearest.png)

-`imaging.Linear`          | ![dstImage](testdata/out_resize_linear.png)

-`imaging.CatmullRom`      | ![dstImage](testdata/out_resize_catrom.png)

-`imaging.Lanczos`         | ![dstImage](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](testdata/flowers_small.png) | ![dstImage](testdata/out_blur_0.5.png) | ![dstImage](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](testdata/flowers_small.png) | ![dstImage](testdata/out_sharpen_0.5.png) | ![dstImage](testdata/out_sharpen_1.5.png)

-

-### Gamma correction

-

-```go

-dstImage := imaging.AdjustGamma(srcImage, 0.75)

-```

-

-Original image                     | Gamma = 0.75                             | Gamma = 1.25

------------------------------------|------------------------------------------|-----------------------------------------

-![srcImage](testdata/flowers_small.png) | ![dstImage](testdata/out_gamma_0.75.png) | ![dstImage](testdata/out_gamma_1.25.png)

-

-### Contrast adjustment

-

-```go

-dstImage := imaging.AdjustContrast(srcImage, 20)

-```

-

-Original image                     | Contrast = 15                              | Contrast = -15

------------------------------------|--------------------------------------------|-------------------------------------------

-![srcImage](testdata/flowers_small.png) | ![dstImage](testdata/out_contrast_p15.png) | ![dstImage](testdata/out_contrast_m15.png)

-

-### Brightness adjustment

-

-```go

-dstImage := imaging.AdjustBrightness(srcImage, 20)

-```

-

-Original image                     | Brightness = 10                              | Brightness = -10

------------------------------------|----------------------------------------------|---------------------------------------------

-![srcImage](testdata/flowers_small.png) | ![dstImage](testdata/out_brightness_p10.png) | ![dstImage](testdata/out_brightness_m10.png)

-

-### Saturation adjustment

-

-```go

-dstImage := imaging.AdjustSaturation(srcImage, 20)

-```

-

-Original image                     | Saturation = 30                              | Saturation = -30

------------------------------------|----------------------------------------------|---------------------------------------------

-![srcImage](testdata/flowers_small.png) | ![dstImage](testdata/out_saturation_p30.png) | ![dstImage](testdata/out_saturation_m30.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 stadard `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))

-```

-

-### What's the difference between `imaging` and `gift` packages?

-

-[imaging](https://github.com/disintegration/imaging)

-is designed to be a lightweight and simple image manipulation package.

-It provides basic image processing functions and a few helper functions

-such as `Open` and `Save`. It consistently returns *image.NRGBA image 

-type (8 bits per channel, RGBA).

-

-[gift](https://github.com/disintegration/gift)

-supports more advanced image processing, for example, sRGB/Linear color

-space conversions. It also supports different output image types

-(e.g. 16 bits per channel) and provides easy-to-use API for chaining

-multiple processing steps together.

-

-## Example code

-

-```go

-package main

-

-import (

-	"image"

-	"image/color"

-	"log"

-

-	"github.com/disintegration/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](testdata/out_example.jpg)