nanocode/web-opencv/miniappB/test_real_images.js

/**
 * test_real_images.js — 使用真实试纸图片验证 PaperRecognizer
 *
 * 用法: node test_real_images.js [image_path]
 *       不带参数则处理 /home/ubuntu/nanocode/web-opencv/cpp/images/ 下所有图片
 *       带参数则只处理指定图片
 *
 * 依赖: npm install canvas
 */

const { createCanvas, loadImage } = require('canvas');
const fs = require('fs');
const path = require('path');
const { PaperRecognizer, PST_NAMES } = require('./paper-recognizer.js');

const IMAGE_DIR = '/home/ubuntu/nanocode/web-opencv/cpp/images/';
const OUTPUT_DIR = '/home/ubuntu/nanocode/web-opencv/miniappB/samples/';

// Ensure output dir
if (!fs.existsSync(OUTPUT_DIR)) fs.mkdirSync(OUTPUT_DIR, { recursive: true });

const LOCATOR_COLORS = ['Unknown', 'Red', 'Green', 'Blue'];
const BLUR_NAMES = ['None', 'Slight', 'Severe'];

async function processImage(imagePath) {
  const fname = path.basename(imagePath);
  console.log(`\n▶ ${fname}`);

  const t0 = performance.now();

  // Load image
  const img = await loadImage(imagePath);
  console.log(`  尺寸: ${img.width}×${img.height}`);

  // Draw to canvas to get RGBA pixels
  const canvas = createCanvas(img.width, img.height);
  const ctx = canvas.getContext('2d');
  ctx.drawImage(img, 0, 0);
  const imageData = ctx.getImageData(0, 0, img.width, img.height);
  const pixels = new Uint8Array(imageData.data.buffer);

  // Recognize
  const recognizer = new PaperRecognizer();
  const result = recognizer.recognize(pixels, img.width, img.height);
  const elapsed = (performance.now() - t0).toFixed(0);

  const paperType = PST_NAMES[result.paperType] || 'UNKNOWN';
  const color = LOCATOR_COLORS[result.locatorColor] || '?';
  const blur = BLUR_NAMES[result.blurLevel] || '?';

  if (result.success) {
    console.log(`  ✅ 成功 | 类型: ${paperType} | 色块: ${result.itemCount} | 定位块颜色: ${color} | 小在左: ${result.smallLocatorOnLeft} | 模糊: ${blur}(${(result.blurScore||0).toFixed(0)}) | 耗时: ${elapsed}ms`);

    // Save annotated image
    if (recognizer.annotatedPixels) {
      const outCanvas = createCanvas(img.width, img.height);
      const outCtx = outCanvas.getContext('2d');
      const outData = outCtx.createImageData(img.width, img.height);
      // annotatedPixels is BGRA, need to convert to RGBA for canvas
      const ap = recognizer.annotatedPixels;
      for (let i = 0; i < ap.length; i += 4) {
        outData.data[i] = ap[i + 2];     // R
        outData.data[i + 1] = ap[i + 1]; // G
        outData.data[i + 2] = ap[i];     // B
        outData.data[i + 3] = ap[i + 3]; // A
      }
      outCtx.putImageData(outData, 0, 0);
      const outName = fname.replace(/\.(jpg|jpeg|png|JPG|JPEG|PNG)$/, '_annotated.png');
      const outPath = path.join(OUTPUT_DIR, outName);
      const buf = outCanvas.toBuffer('image/png');
      fs.writeFileSync(outPath, buf);
      console.log(`  标注图: ${outPath}`);
    }

    // Print first 3 colors
    if (result.colors && result.colors.length > 0) {
      const preview = result.colors.slice(0, 3).map(c =>
        `RGB(${c.r.toFixed(0)},${c.g.toFixed(0)},${c.b_val.toFixed(0)})`
      ).join(', ');
      console.log(`  前3色块: ${preview}${result.colors.length > 3 ? ' ...' : ''}`);
    }
  } else {
    const errCode = result.errorCode;
    const errMsg = result.errorMessage || '';
    console.log(`  ❌ 失败 | 错误码: ${errCode} | ${errMsg} | 耗时: ${elapsed}ms`);
  }

  recognizer.free();
  return { fname, result, elapsed };
}

async function main() {
  const args = process.argv.slice(2);
  let files;

  if (args.length > 0) {
    files = args.filter(f => {
      const ext = path.extname(f).toLowerCase();
      return ['.jpg', '.jpeg', '.png'].includes(ext);
    });
  } else {
    files = fs.readdirSync(IMAGE_DIR)
      .filter(f => /\.(jpg|jpeg|png|JPG)$/i.test(f))
      .map(f => path.join(IMAGE_DIR, f));
  }

  if (files.length === 0) {
    console.log('未找到图片文件');
    process.exit(1);
  }

  console.log(`═══════════════════════════════════════════`);
  console.log(`PaperRecognizer 真实图片测试`);
  console.log(`共 ${files.length} 张图片`);
  console.log(`═══════════════════════════════════════════`);

  const results = [];
  for (const f of files) {
    try {
      const r = await processImage(f);
      results.push(r);
    } catch (e) {
      console.log(`\n▶ ${path.basename(f)}`);
      console.log(`  💥 异常: ${e.message}`);
      results.push({ fname: path.basename(f), result: null, error: e.message });
    }
  }

  // Summary
  const success = results.filter(r => r.result && r.result.success).length;
  const failed = results.filter(r => r.result && !r.result.success).length;
  const errors = results.filter(r => !r.result).length;
  const total = results.length;

  console.log(`\n═══════════════════════════════════════════`);
  console.log(`汇总: ${total} 张 | ✅ ${success} | ❌ ${failed} | 💥 ${errors}`);
  console.log(`成功率: ${(success / total * 100).toFixed(1)}%`);

  // Print failures detail
  const failures = results.filter(r => r.result && !r.result.success);
  if (failures.length > 0) {
    console.log(`\n失败详情:`);
    for (const f of failures) {
      console.log(`  ${f.fname}: [${f.result.errorCode}] ${f.result.errorMessage}`);
    }
  }

  process.exit(0);
}

main();