130 lines
3.5 KiB
JavaScript
130 lines
3.5 KiB
JavaScript
// 图片优化脚本 - 使用sharp压缩PNG图片
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const sharp = require('sharp');
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const fs = require('fs');
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const path = require('path');
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// 需要优化的大图片列表 (> 500KB)
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const LARGE_IMAGES = [
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'CoverImage.png',
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'BasicImage.png',
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'teams-image.png',
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'hand-background.png',
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'basic-auth.png',
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'BgMusicCard.png',
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'Landing2.png',
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'Landing3.png',
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'Landing1.png',
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'smart-home.png',
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'automotive-background-card.png'
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];
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const IMG_DIR = path.join(__dirname, 'src/assets/img');
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const BACKUP_DIR = path.join(IMG_DIR, 'original-backup');
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// 确保备份目录存在
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if (!fs.existsSync(BACKUP_DIR)) {
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fs.mkdirSync(BACKUP_DIR, { recursive: true });
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}
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console.log('🎨 开始优化图片...');
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console.log('================================\n');
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let totalBefore = 0;
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let totalAfter = 0;
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let optimizedCount = 0;
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async function optimizeImage(filename) {
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const srcPath = path.join(IMG_DIR, filename);
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const backupPath = path.join(BACKUP_DIR, filename);
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if (!fs.existsSync(srcPath)) {
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console.log(`⚠️ 跳过: ${filename} (文件不存在)`);
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return;
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}
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try {
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// 获取原始大小
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const beforeStats = fs.statSync(srcPath);
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const beforeSize = beforeStats.size;
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totalBefore += beforeSize;
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// 备份原始文件
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if (!fs.existsSync(backupPath)) {
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fs.copyFileSync(srcPath, backupPath);
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}
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// 读取图片元数据
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const metadata = await sharp(srcPath).metadata();
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// 优化策略：
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// 1. 如果宽度 > 2000px，缩放到 2000px
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// 2. 压缩质量到 85
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// 3. 使用 pngquant 算法压缩
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let pipeline = sharp(srcPath);
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if (metadata.width > 2000) {
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pipeline = pipeline.resize(2000, null, {
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withoutEnlargement: true,
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fit: 'inside'
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});
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}
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// PNG优化
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pipeline = pipeline.png({
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quality: 85,
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compressionLevel: 9,
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adaptiveFiltering: true,
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force: true
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});
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// 保存优化后的图片
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await pipeline.toFile(srcPath + '.tmp');
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// 替换原文件
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fs.renameSync(srcPath + '.tmp', srcPath);
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// 获取优化后的大小
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const afterStats = fs.statSync(srcPath);
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const afterSize = afterStats.size;
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totalAfter += afterSize;
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// 计算节省的大小
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const saved = beforeSize - afterSize;
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const percent = Math.round((saved / beforeSize) * 100);
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if (saved > 0) {
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optimizedCount++;
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console.log(`✅ ${filename}`);
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console.log(` ${Math.round(beforeSize/1024)} KB → ${Math.round(afterSize/1024)} KB`);
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console.log(` 节省: ${Math.round(saved/1024)} KB (-${percent}%)\n`);
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} else {
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console.log(`ℹ️ ${filename} - 已经是最优化状态\n`);
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}
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} catch (error) {
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console.error(`❌ ${filename} 优化失败:`, error.message);
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}
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}
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async function main() {
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// 依次优化每个图片
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for (const img of LARGE_IMAGES) {
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await optimizeImage(img);
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}
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console.log('================================');
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console.log('📊 优化总结:\n');
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console.log(` 优化前总大小: ${Math.round(totalBefore/1024/1024)} MB`);
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console.log(` 优化后总大小: ${Math.round(totalAfter/1024/1024)} MB`);
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const totalSaved = totalBefore - totalAfter;
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const totalPercent = Math.round((totalSaved / totalBefore) * 100);
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console.log(` 节省空间: ${Math.round(totalSaved/1024/1024)} MB (-${totalPercent}%)`);
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console.log(` 成功优化: ${optimizedCount}/${LARGE_IMAGES.length} 个文件\n`);
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console.log('✅ 图片优化完成！');
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console.log(`📁 原始文件已备份到: ${BACKUP_DIR}\n`);
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}
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main().catch(console.error);
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