基于Serverless架构的图片处理服务实战：灰度化转换实现

// 图片灰度化处理函数
async function convertToGrayscale(file) {
  const image = await createImageBitmap(file);
  const canvas = document.createElement('canvas');
  canvas.width = image.width;
  canvas.height = image.height;
  
  const ctx = canvas.getContext('2d');
  ctx.drawImage(image, 0, 0);
  
  const imageData = ctx.getImageData(0, 0, canvas.width, canvas.height);
  const data = imageData.data;

  // 使用Luma算法计算灰度值
  for (let i = 0; i < data.length; i += 4) {
    const gray = 0.299 * data[i] + 0.587 * data[i + 1] + 0.114 * data[i + 2];
    data[i] = data[i + 1] = data[i + 2] = gray;
  }

  ctx.putImageData(imageData, 0, 0);
  return canvas.toDataURL('image/jpeg');
}

// 云函数入口文件
const sharp = require('sharp');

exports.main_handler = async (event) => {
  try {
    const { body } = event;
    const buffer = Buffer.from(body, 'base64');
    
    const processedImage = await sharp(buffer)
      .grayscale()
      .toBuffer();
    
    return {
      statusCode: 200,
      headers: {'Content-Type': 'image/jpeg'},
      body: processedImage.toString('base64'),
      isBase64Encoded: true
    };
  } catch (err) {
    return {
      statusCode: 500,
      body: JSON.stringify({error: err.message})
    };
  }
};

// 使用sharp库进行图片压缩
await sharp(inputBuffer)
  .resize(800)  // 限制宽度
  .jpeg({ quality: 80 }) // 质量压缩
  .toBuffer();