288 lines
9.1 KiB
TypeScript
288 lines
9.1 KiB
TypeScript
import sharp from 'sharp'
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import { withImageProcessingSlot } from '@/lib/image-processing-limiter'
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import { configureSharpRuntime } from '@/lib/sharp-runtime'
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configureSharpRuntime()
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const IMAGE_PROCESSING_MAX_PIXELS = 60_000_000
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const IMAGE_PROCESSING_MAX_DIMENSION = 20_000
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const IMAGE_PROCESSING_MAX_SLICES = 60
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function createSharpInput(buffer: Buffer) {
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return sharp(buffer, {
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limitInputPixels: IMAGE_PROCESSING_MAX_PIXELS,
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sequentialRead: true,
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failOn: 'error',
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})
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}
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export function assertProcessableMetadata(
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metadata: sharp.Metadata,
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options: {
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allowAnimatedFirstFrame?: boolean
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maxInputWidth?: number
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maxInputHeight?: number
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maxInputPixels?: number
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} = {},
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) {
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if (!metadata.width || !metadata.height) {
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throw new Error('无法获取图片尺寸')
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}
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const maxInputWidth = options.maxInputWidth || IMAGE_PROCESSING_MAX_DIMENSION
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const maxInputHeight = options.maxInputHeight || IMAGE_PROCESSING_MAX_DIMENSION
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const maxInputPixels = options.maxInputPixels || IMAGE_PROCESSING_MAX_PIXELS
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if (metadata.width > maxInputWidth || metadata.height > maxInputHeight) {
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throw new Error('图片尺寸过大')
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}
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if (metadata.width * metadata.height > maxInputPixels) {
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throw new Error('图片像素总量过大')
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}
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if (!options.allowAnimatedFirstFrame && Number(metadata.pages || 1) > 1) {
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throw new Error('不支持动图或多页图片')
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}
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}
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interface ProcessImageOptions {
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maxSizeKB?: number // 最大文件大小（KB）
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maxWidth?: number // 最大宽度（像素）
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maxHeight?: number // 最大高度（像素）
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format?: 'webp' | 'jpeg' | 'png'
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// 仅用于已有独立安全门禁的调用链路，默认仍拒绝动图和超长维度。
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allowAnimatedFirstFrame?: boolean
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maxInputWidth?: number
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maxInputHeight?: number
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maxInputPixels?: number
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}
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/**
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* 处理图片：压缩、调整尺寸、转换格式
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* @param buffer 原始图片buffer
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* @param options 处理选项
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* @returns 处理后的图片buffer
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*/
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export async function processImage(
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buffer: Buffer,
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options: ProcessImageOptions = {}
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): Promise<Buffer> {
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const {
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maxSizeKB = 300, // 默认300KB
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maxWidth = 600, // 默认600像素
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maxHeight = 800, // 默认800像素（适配300x400显示）
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format = 'webp', // 默认webP格式
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allowAnimatedFirstFrame = false,
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maxInputWidth = IMAGE_PROCESSING_MAX_DIMENSION,
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maxInputHeight = IMAGE_PROCESSING_MAX_DIMENSION,
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maxInputPixels = IMAGE_PROCESSING_MAX_PIXELS,
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} = options
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return withImageProcessingSlot(async () => {
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try {
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// 获取原始图片信息
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const image = createSharpInput(buffer)
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const metadata = await image.metadata()
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assertProcessableMetadata(metadata, {
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allowAnimatedFirstFrame,
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maxInputWidth,
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maxInputHeight,
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maxInputPixels,
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})
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// 计算新尺寸（保持比例，同时限制宽度和高度）
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let width = metadata.width || maxWidth
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let height = metadata.height || maxHeight
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// 如果宽度超过限制
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if (width > maxWidth) {
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const ratio = maxWidth / width
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width = maxWidth
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height = Math.round(height * ratio)
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}
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// 如果高度超过限制，再次调整
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if (height > maxHeight) {
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const ratio = maxHeight / height
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height = maxHeight
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width = Math.round(width * ratio)
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}
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// 优化：初始质量从80降到70，在保证视觉质量的前提下减少文件大小
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let quality = 70
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let processedBuffer: Buffer
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// 第一次处理
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processedBuffer = await createSharpInput(buffer)
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.resize(width, height, {
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fit: 'inside',
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withoutEnlargement: true,
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})
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.webp({ quality })
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.toBuffer()
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// 如果文件还是太大，逐步降低质量
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const maxBytes = maxSizeKB * 1024
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while (processedBuffer.length > maxBytes && quality > 20) {
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quality -= 10
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processedBuffer = await createSharpInput(buffer)
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.resize(width, height, {
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fit: 'inside',
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withoutEnlargement: true,
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})
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.webp({ quality })
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.toBuffer()
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}
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console.log(`图片处理完成: ${metadata.width}x${metadata.height} -> ${width}x${height}, ${(buffer.length / 1024).toFixed(2)}KB -> ${(processedBuffer.length / 1024).toFixed(2)}KB, 质量: ${quality}`)
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return processedBuffer
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} catch (error) {
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console.error('图片处理失败:', error)
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throw new Error('图片处理失败')
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}
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})
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}
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/**
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* 获取处理后的文件名（添加.webp扩展名）
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*/
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export function getProcessedFileName(originalName: string): string {
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const nameWithoutExt = originalName.replace(/\.[^/.]+$/, '')
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return `${nameWithoutExt}.webp`
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}
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/**
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* 切割长图片为多个最高1500px的图片片段，并压缩到指定大小
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* @param buffer 原始图片buffer
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* @param maxHeight 每个片段的最大高度（默认1500px）
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* @param maxSizeKB 每个切片的最大文件大小（默认500KB）
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* @param maxWidth 可选的切片最大宽度；会先等比缩放再按输出高度切片
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* @returns 切割后的图片buffer数组
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*/
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export async function sliceImage(
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buffer: Buffer,
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maxHeight: number = 1500,
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maxSizeKB: number = 500,
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maxWidth?: number,
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options: {
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allowAnimatedFirstFrame?: boolean
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maxInputWidth?: number
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maxInputHeight?: number
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maxInputPixels?: number
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} = {},
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): Promise<Buffer[]> {
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return withImageProcessingSlot(async () => {
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try {
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const image = createSharpInput(buffer)
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const metadata = await image.metadata()
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assertProcessableMetadata(metadata, options)
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const { width, height } = metadata
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const outputScale = maxWidth && width > maxWidth ? maxWidth / width : 1
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const outputWidth = Math.max(1, Math.round(width * outputScale))
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const outputHeight = Math.max(1, Math.round(height * outputScale))
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const slices: Buffer[] = []
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const maxBytes = maxSizeKB * 1024
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const createOutputPipeline = () => {
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const pipeline = createSharpInput(buffer)
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return outputScale < 1
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? pipeline.resize({ width: outputWidth, withoutEnlargement: true })
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: pipeline
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}
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// 如果图片高度不超过maxHeight，直接返回原图（压缩处理）
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if (outputHeight <= maxHeight) {
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let quality = 90
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let processedBuffer = await createOutputPipeline()
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.webp({ quality })
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.toBuffer()
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// 如果文件还是太大，逐步降低质量
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while (processedBuffer.length > maxBytes && quality > 20) {
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quality -= 10
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processedBuffer = await createOutputPipeline()
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.webp({ quality })
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.toBuffer()
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}
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console.log(`图片无需切割: ${width}x${height} -> ${outputWidth}x${outputHeight}, 压缩到 ${(processedBuffer.length / 1024).toFixed(2)}KB, 质量: ${quality}`)
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return [processedBuffer]
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}
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// 计算需要切割的片数
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const sliceCount = Math.ceil(outputHeight / maxHeight)
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if (sliceCount > IMAGE_PROCESSING_MAX_SLICES) {
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throw new Error(`图片过长，最多支持 ${IMAGE_PROCESSING_MAX_SLICES} 个切片`)
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}
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console.log(`开始切割图片: ${width}x${height} -> ${outputWidth}x${outputHeight}, ${sliceCount}个片段，每片限制${maxSizeKB}KB`)
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// 切割图片
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for (let i = 0; i < sliceCount; i++) {
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const top = i * maxHeight
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const extractHeight = Math.min(maxHeight, outputHeight - top)
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// 初始质量
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let quality = 90
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let sliceBuffer = await createOutputPipeline()
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.extract({
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left: 0,
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top: top,
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width: outputWidth,
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height: extractHeight
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})
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.webp({ quality })
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.toBuffer()
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// 如果文件还是太大，逐步降低质量
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while (sliceBuffer.length > maxBytes && quality > 20) {
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quality -= 10
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sliceBuffer = await createOutputPipeline()
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.extract({
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left: 0,
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top: top,
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width: outputWidth,
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height: extractHeight
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})
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.webp({ quality })
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.toBuffer()
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}
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slices.push(sliceBuffer)
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console.log(`切割片段 ${i + 1}/${sliceCount}: 高度 ${extractHeight}px, 大小 ${(sliceBuffer.length / 1024).toFixed(2)}KB, 质量: ${quality}`)
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}
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return slices
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} catch (error) {
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console.error('图片切割失败:', error)
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throw new Error('图片切割失败')
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}
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})
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}
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/**
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* 压缩图片（简化版，用于 API 路由）
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* @param buffer 原始图片buffer
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* @param options 压缩选项
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* @returns 压缩后的图片buffer
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*/
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export async function compressImage(
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buffer: Buffer,
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options: ProcessImageOptions = {}
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): Promise<Buffer> {
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return processImage(buffer, options);
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}
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/**
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* 清理文件名（移除特殊字符）
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* @param fileName 原始文件名
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* @returns 清理后的文件名
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*/
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export function sanitizeFileName(fileName: string): string {
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// 移除路径分隔符和特殊字符
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return fileName
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.replace(/[\/\\]/g, '-')
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.replace(/[<>:"|?*]/g, '')
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.replace(/\s+/g, '-')
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.trim();
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}
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