295 lines
10 KiB
JavaScript
295 lines
10 KiB
JavaScript
// /**
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// * 获取文件大小（Promise封装）
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// * @param {string} filePath
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// * @returns {Promise<number>} 文件字节数
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// */
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// const getFileSize = (filePath) => {
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// return new Promise(resolve => {
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// uni.getFileInfo({
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// filePath,
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// success: (res) => resolve(res.size),
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// fail: () => resolve(Infinity)
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// });
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// });
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// };
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/**
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* 获取文件大小（兼容新版API）
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* @param {string} filePath
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* @returns {Promise<number>} 文件字节数
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*/
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const getFileSize = async (filePath) => {
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try {
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const res = await new Promise((resolve, reject) => {
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wx.getFileSystemManager().getFileInfo({
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filePath,
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success: resolve,
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fail: reject
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});
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});
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return res.size || Infinity;
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} catch (err) {
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console.error('获取文件大小失败:', err);
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return Infinity;
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}
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};
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/**
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* 执行图片压缩（Promise封装）
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* @param {string} src
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* @param {number} quality
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* @returns {Promise<string>} 压缩后的临时路径
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*/
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const doCompressImage = (src, quality) => {
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return new Promise(resolve => {
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uni.compressImage({
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src,
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quality,
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success: (res) => resolve(res.tempFilePath),
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fail: () => resolve(src) // 失败返回原路径
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});
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});
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};
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/**
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* 智能图片压缩（支持多平台）
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* @param {string} tempFilePath - 图片临时路径
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* @param {number} maxSize - 目标最大字节数（默认500KB）
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* @param {number} [initialQuality=80] - 初始压缩质量(1-100)
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* @returns {Promise<string>} 压缩后的临时路径
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*/
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export const compressImage = async (tempFilePath, maxSize = 500 * 1024, initialQuality = 80) => {
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let quality = initialQuality;
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let compressedPath = tempFilePath;
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let currentSize = Infinity;
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// 二分法压缩参数
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let low = 10;
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let high = initialQuality;
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while (low <= high) {
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quality = Math.floor((low + high) / 2);
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// 使用提取的Promise方法
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compressedPath = await doCompressImage(tempFilePath, quality);
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currentSize = await getFileSize(compressedPath);
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if (currentSize <= maxSize) {
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low = quality + 1; // 尝试更高质量
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} else {
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high = quality - 1; // 降低质量
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}
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if (high - low < 5) break; // 安全阀
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}
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// 最终强制压缩（如果仍未达标）
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if (currentSize > maxSize) {
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compressedPath = await doCompressImage(tempFilePath, 10);
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}
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return compressedPath;
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};
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/**
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* 精准图片压缩（优化版）
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* @param {string} tempFilePath - 图片临时路径
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* @param {number} targetSize - 目标字节数（默认500KB）
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* @param {number} [initialQuality=85] - 初始压缩质量(1-100)
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* @returns {Promise<{path: string, quality: number, iterations: number, finalSize: number}>}
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*/
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export const preciseCompress = async (tempFilePath, targetSize = 500 * 1024, initialQuality = 85) => {
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let quality = initialQuality;
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let compressedPath = tempFilePath;
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let currentSize = Infinity;
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let iterations = 0;
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const maxIterations = 10; // 增加最大迭代次数
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const history = []; // 记录每次压缩结果用于分析
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// 首先检查原图大小，如果已经满足直接返回
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const originalSize = await getFileSize(tempFilePath);
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if (originalSize <= targetSize) {
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return { path: tempFilePath, quality: 100, iterations: 0, finalSize: originalSize };
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}
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// 智能预测初始质量范围（新增）
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const predictQualityRange = (originalSize, targetSize) => {
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const ratio = targetSize / originalSize;
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if (ratio > 0.8) return { low: 70, high: 95 };
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if (ratio > 0.5) return { low: 45, high: 75 };
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if (ratio > 0.3) return { low: 25, high: 50 };
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if (ratio > 0.1) return { low: 10, high: 30 };
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return { low: 5, high: 15 }; // 极限压缩
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};
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const { low: predictedLow, high: predictedHigh } = predictQualityRange(originalSize, targetSize);
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let low = predictedLow;
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let high = Math.min(predictedHigh, initialQuality);
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console.log(`预测质量范围: ${low}-${high} (原图${(originalSize/1024).toFixed(2)}KB → 目标${(targetSize/1024).toFixed(2)}KB)`);
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// 动态调整二分法边界（优化版）
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const adjustBounds = (currentQuality, currentSize, targetSize) => {
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const sizeRatio = currentSize / targetSize;
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const qualityDelta = Math.max(2, Math.floor(currentQuality * 0.1)); // 动态调整幅度
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if (sizeRatio > 2.5) {
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return { lowDelta: -qualityDelta * 2, highDelta: -qualityDelta };
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} else if (sizeRatio > 1.5) {
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return { lowDelta: -qualityDelta, highDelta: -Math.floor(qualityDelta / 2) };
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} else if (sizeRatio > 1.1) {
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return { lowDelta: -3, highDelta: -1 };
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} else {
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return { lowDelta: -1, highDelta: 0 };
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}
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};
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let bestResult = null; // 记录最佳结果
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while (iterations < maxIterations && low <= high) {
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iterations++;
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quality = Math.floor((low + high) / 2);
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// 跳过已经测试过的quality值
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if (history.some(item => item.quality === quality)) {
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break;
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}
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compressedPath = await doCompressImage(tempFilePath, quality);
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currentSize = await getFileSize(compressedPath);
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history.push({ quality, size: currentSize });
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console.log(`第${iterations}次尝试: quality=${quality} → ${(currentSize / 1024).toFixed(2)}KB (目标${(targetSize/1024).toFixed(2)}KB)`);
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// 更新最佳结果
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if (!bestResult || Math.abs(currentSize - targetSize) < Math.abs(bestResult.size - targetSize)) {
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bestResult = { quality, size: currentSize, path: compressedPath };
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}
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// 精准匹配检查（容差范围调整为3%）
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if (Math.abs(currentSize - targetSize) < targetSize * 0.03) {
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console.log('✅ 达到精准匹配，提前结束');
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break;
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}
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if (currentSize > targetSize) {
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const { lowDelta, highDelta } = adjustBounds(quality, currentSize, targetSize);
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high = Math.max(5, quality + highDelta); // 确保不会低于最小值
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} else {
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low = quality + 1; // 当小于目标时，尝试更高质量
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}
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// 收敛检查
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if (high - low <= 1) break;
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}
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// 如果最佳结果仍然超标，尝试极限压缩
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if (bestResult && bestResult.size > targetSize * 1.1) {
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console.log('🔥 尝试极限压缩...');
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const extremePath = await doCompressImage(tempFilePath, 5);
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const extremeSize = await getFileSize(extremePath);
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console.log(`极限压缩结果: quality=5 → ${(extremeSize / 1024).toFixed(2)}KB`);
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if (extremeSize < bestResult.size) {
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bestResult = { quality: 5, size: extremeSize, path: extremePath };
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}
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}
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const finalResult = bestResult || { quality: 10, size: currentSize, path: compressedPath };
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console.log(`🎯 最终结果：quality=${finalResult.quality} → ${(finalResult.size / 1024).toFixed(2)}KB` +
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`（迭代${iterations}次，压缩率${((1 - finalResult.size / originalSize) * 100).toFixed(1)}%）`);
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return {
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path: finalResult.path,
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quality: finalResult.quality,
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iterations,
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finalSize: finalResult.size
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};
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};
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/**
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* 图片转Base64（兼容多平台）
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* @param {string} filePath - 图片临时路径
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* @returns {Promise<string>} Base64字符串（带data:image/前缀）
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*/
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export const imageToBase64 = (filePath) => {
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return new Promise((resolve, reject) => {
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// 先获取图片类型
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uni.getImageInfo({
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src: filePath,
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success: (info) => {
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const type = info.type || 'jpeg';
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// 读取文件为Base64
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uni.getFileSystemManager().readFile({
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filePath,
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encoding: 'base64',
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success: (res) => resolve(`data:image/${type};base64,${res.data}`),
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fail: reject
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});
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},
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fail: () => {
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// 类型获取失败时默认jpeg
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uni.getFileSystemManager().readFile({
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filePath,
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encoding: 'base64',
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success: (res) => resolve(`data:image/jpeg;base64,${res.data}`),
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fail: reject
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});
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}
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});
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});
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};
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/**
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* 完整处理流程（智能判断是否压缩）：
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* 选择图片 → 检查大小 → 按需压缩 → 转Base64
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* @returns {Promise<{ base64: string, path: string, compressed: boolean }>}
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*/
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export const processImage = async (maxSize = 500 * 1024) => {
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// 1. 选择图片
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const chooseRes = await new Promise(resolve => {
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uni.chooseImage({
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count: 1,
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sizeType: ['original', 'compressed'],
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success: resolve,
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fail: () => resolve(null)
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});
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});
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if (!chooseRes) throw new Error('选择图片失败');
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const tempFilePath = chooseRes.tempFilePaths[0];
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let finalPath = tempFilePath;
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let isCompressed = false;
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// 2. 检查文件大小
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const fileSize = await getFileSize(tempFilePath);
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console.log(`原图大小: ${(fileSize / 1024).toFixed(2)}KB`);
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// 3. 按需压缩
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if (fileSize > maxSize) {
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console.log('🔄 开始智能压缩...');
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const compressResult = await preciseCompress(tempFilePath, maxSize);
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finalPath = compressResult.path;
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isCompressed = true;
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// 验证压缩结果
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console.log(`✅ 压缩完成: ${(fileSize / 1024).toFixed(2)}KB → ${(compressResult.finalSize / 1024).toFixed(2)}KB` +
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` (节省${((1 - compressResult.finalSize / fileSize) * 100).toFixed(1)}%)`);
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}
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// 4. 转换为Base64
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const base64 = await imageToBase64(finalPath);
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console.log(`📄 Base64长度: ${base64.length} 字符`);
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return {
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base64, // Base64字符串
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path: finalPath, // 最终文件路径（可能是原图或压缩图）
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compressed: isCompressed // 是否经过压缩
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};
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}; |