mirror of
https://github.com/gohugoio/hugo.git
synced 2024-12-24 02:11:05 +00:00
104 lines
2.9 KiB
Go
104 lines
2.9 KiB
Go
// Copyright 2019 The Hugo Authors. All rights reserved.
|
|
//
|
|
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
// you may not use this file except in compliance with the License.
|
|
// You may obtain a copy of the License at
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
//
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
// See the License for the specific language governing permissions and
|
|
// limitations under the License.
|
|
|
|
package images
|
|
|
|
import (
|
|
"image"
|
|
"math"
|
|
|
|
"github.com/disintegration/gift"
|
|
|
|
"github.com/muesli/smartcrop"
|
|
)
|
|
|
|
const (
|
|
// Do not change.
|
|
smartCropIdentifier = "smart"
|
|
|
|
// This is just a increment, starting on 1. If Smart Crop improves its cropping, we
|
|
// need a way to trigger a re-generation of the crops in the wild, so increment this.
|
|
smartCropVersionNumber = 1
|
|
)
|
|
|
|
func (p *ImageProcessor) newSmartCropAnalyzer(filter gift.Resampling) smartcrop.Analyzer {
|
|
return smartcrop.NewAnalyzer(imagingResizer{p: p, filter: filter})
|
|
}
|
|
|
|
// Needed by smartcrop
|
|
type imagingResizer struct {
|
|
p *ImageProcessor
|
|
filter gift.Resampling
|
|
}
|
|
|
|
func (r imagingResizer) Resize(img image.Image, width, height uint) image.Image {
|
|
// See https://github.com/gohugoio/hugo/issues/7955#issuecomment-861710681
|
|
scaleX, scaleY := calcFactorsNfnt(width, height, float64(img.Bounds().Dx()), float64(img.Bounds().Dy()))
|
|
if width == 0 {
|
|
width = uint(math.Ceil(float64(img.Bounds().Dx()) / scaleX))
|
|
}
|
|
if height == 0 {
|
|
height = uint(math.Ceil(float64(img.Bounds().Dy()) / scaleY))
|
|
}
|
|
result, _ := r.p.Filter(img, gift.Resize(int(width), int(height), r.filter))
|
|
return result
|
|
}
|
|
|
|
func (p *ImageProcessor) smartCrop(img image.Image, width, height int, filter gift.Resampling) (image.Rectangle, error) {
|
|
if width <= 0 || height <= 0 {
|
|
return image.Rectangle{}, nil
|
|
}
|
|
|
|
srcBounds := img.Bounds()
|
|
srcW := srcBounds.Dx()
|
|
srcH := srcBounds.Dy()
|
|
|
|
if srcW <= 0 || srcH <= 0 {
|
|
return image.Rectangle{}, nil
|
|
}
|
|
|
|
if srcW == width && srcH == height {
|
|
return srcBounds, nil
|
|
}
|
|
|
|
smart := p.newSmartCropAnalyzer(filter)
|
|
|
|
rect, err := smart.FindBestCrop(img, width, height)
|
|
if err != nil {
|
|
return image.Rectangle{}, err
|
|
}
|
|
|
|
return img.Bounds().Intersect(rect), nil
|
|
}
|
|
|
|
// Calculates scaling factors using old and new image dimensions.
|
|
// Code borrowed from https://github.com/nfnt/resize/blob/83c6a9932646f83e3267f353373d47347b6036b2/resize.go#L593
|
|
func calcFactorsNfnt(width, height uint, oldWidth, oldHeight float64) (scaleX, scaleY float64) {
|
|
if width == 0 {
|
|
if height == 0 {
|
|
scaleX = 1.0
|
|
scaleY = 1.0
|
|
} else {
|
|
scaleY = oldHeight / float64(height)
|
|
scaleX = scaleY
|
|
}
|
|
} else {
|
|
scaleX = oldWidth / float64(width)
|
|
if height == 0 {
|
|
scaleY = scaleX
|
|
} else {
|
|
scaleY = oldHeight / float64(height)
|
|
}
|
|
}
|
|
return
|
|
}
|