133 lines
4.7 KiB
JavaScript
133 lines
4.7 KiB
JavaScript
import sharp from 'sharp';
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import { promises as fs } from 'fs';
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import path from 'path';
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import { fileURLToPath } from 'url';
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import { glob } from 'glob';
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import os from 'os';
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const __filename = fileURLToPath(import.meta.url);
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const __dirname = path.dirname(__filename);
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const sourceDir = 'public/images';
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const outputDir = 'dist/images';
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// 统计数据
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let totalFiles = 0;
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let totalOriginalSize = 0;
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let totalOptimizedSize = 0;
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let successCount = 0;
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let failCount = 0;
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let startTime = Date.now();
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// 文件大小阈值（字节）
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const SMALL_FILE_THRESHOLD = 5 * 1024; // 5KB
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async function optimizeImage(inputPath) {
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const relativePath = path.relative(sourceDir, inputPath);
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const outputPath = path.join(outputDir, relativePath);
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const outputDirPath = path.dirname(outputPath);
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await fs.mkdir(outputDirPath, { recursive: true });
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try {
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const inputStats = await fs.stat(inputPath);
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const isSmallFile = inputStats.size < SMALL_FILE_THRESHOLD;
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// 根据文件大小选择不同的压缩策略
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let sharpInstance = sharp(inputPath);
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if (isSmallFile) {
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// 小文件使用无损压缩策略
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await sharpInstance
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.png({
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compressionLevel: 9,
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effort: 10,
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palette: false // 不使用调色板模式
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})
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.toFile(outputPath);
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} else {
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// 大文件使用有损压缩策略
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await sharpInstance
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.png({
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quality: 80,
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compressionLevel: 9,
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palette: true,
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colors: 256,
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dither: 0.5,
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effort: 10
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})
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.toFile(outputPath);
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}
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const outputStats = await fs.stat(outputPath);
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const savings = ((inputStats.size - outputStats.size) / inputStats.size * 100).toFixed(2);
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// 如果优化后文件更大，使用原始文件
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if (outputStats.size > inputStats.size) {
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await fs.copyFile(inputPath, outputPath);
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console.log(`⚠️ ${relativePath} (使用原始文件)`);
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} else {
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console.log(`✓ ${relativePath}`);
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}
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// 更新统计数据
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totalOriginalSize += inputStats.size;
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totalOptimizedSize += Math.min(inputStats.size, outputStats.size);
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successCount++;
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console.log(` 原始大小: ${(inputStats.size / 1024).toFixed(2)}KB`);
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console.log(` 优化大小: ${(Math.min(inputStats.size, outputStats.size) / 1024).toFixed(2)}KB`);
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console.log(` 节省: ${((inputStats.size - Math.min(inputStats.size, outputStats.size)) / inputStats.size * 100).toFixed(2)}%\n`);
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} catch (error) {
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console.error(`✗ 处理 ${relativePath} 时出错:`, error);
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failCount++;
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}
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}
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function printReport() {
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const endTime = Date.now();
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const duration = ((endTime - startTime) / 1000).toFixed(2);
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const totalSavings = ((totalOriginalSize - totalOptimizedSize) / totalOriginalSize * 100).toFixed(2);
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console.log('\n========== 优化结果报告 ==========');
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console.log(`处理总文件数: ${totalFiles}`);
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console.log(`成功处理: ${successCount} 个文件`);
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console.log(`处理失败: ${failCount} 个文件`);
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console.log(`原始总大小: ${(totalOriginalSize / 1024 / 1024).toFixed(2)}MB`);
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console.log(`优化后总大小: ${(totalOptimizedSize / 1024 / 1024).toFixed(2)}MB`);
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console.log(`总体积减少: ${totalSavings}%`);
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console.log(`处理耗时: ${duration}秒`);
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console.log(`CPU核心数: ${os.cpus().length}`);
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console.log('================================\n');
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}
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async function processImages() {
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try {
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// 清空输出目录
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await fs.rm(outputDir, { recursive: true, force: true });
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await fs.mkdir(outputDir, { recursive: true });
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// 获取所有PNG文件
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const files = await glob(path.join(sourceDir, '**/*.png'));
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totalFiles = files.length;
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console.log(`找到 ${files.length} 个PNG文件需要优化\n`);
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// 使用工作池并行处理图片，限制并发数为CPU核心数
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const concurrency = os.cpus().length;
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const chunks = [];
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for (let i = 0; i < files.length; i += concurrency) {
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chunks.push(files.slice(i, i + concurrency));
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}
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for (const chunk of chunks) {
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await Promise.all(chunk.map(file => optimizeImage(file)));
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}
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printReport();
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} catch (error) {
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console.error('处理过程中发生错误:', error);
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}
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}
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processImages();
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