告别 HSV 红色死区：用 Lab 色空间重新设计工业级颜色检测

Core.inRange(hsvImage, new Scalar(0, 100, 100), new Scalar(10, 255, 255), mask1);
Core.inRange(hsvImage, new Scalar(170, 100, 100), new Scalar(180, 255, 255), mask2);
Core.add(mask1, mask2, redMask);

a*: 负值=绿  ←  0(中性)  →  正值=红
b*: 负值=蓝  ←  0(中性)  →  正值=黄
L*:  0(黑)  →  100(白)

// 预计算一次
try (ColorImageAnalyzer analyzer = ColorDetector.prepare(image)) {

    // 查询多次，每次只做轻量操作
    List<ColorResult> r1 = analyzer.detect(polygon1, 3, 0.05, SortOrder.BY_PERCENT);
    List<ColorResult> r2 = analyzer.detect(polygon2, 5, 0.02, SortOrder.LEFT_TO_RIGHT);
    List<ColorResult> r3 = analyzer.detect(polygon3, 10, 0.01, SortOrder.TOP_TO_BOTTOM);
}

Map<String, List<Point2D>> regions = Map.of("zone1", poly1, "zone2", poly2);
Map<String, List<ColorResult>> batch = ColorDetector.detectColors(image, regions, 3, 0.05, BY_PERCENT);

ColorFilter filter = ColorFilter.builder()
    .includeColors(Set.of("blue"))
    .hsvRanges(List.of(HSVColorRange.of(100, 130, 80, 255, 50, 255)))
    .hexMatch(HexColorMatch.of("#0066FF", 15.0))
    .build();

List<ColorResult> results = ColorDetector.detectColors(image, polygon,
    3, 0.05, SortOrder.BY_PERCENT, filter);

double delta = ColorDetector.colorDifference(resultA, resultB);

double sim = ColorDetector.shapeSimilarity(contourA, contourB);
// 返回值越小越相似：<0.1 几乎一致，>1.0 完全不同
// 平移、缩放、旋转不变——10×5 和 100×50 的矩形判定为相同形状

ColorComparator cmp = ColorComparator.builder()
    .proportionTolerance(0.15)
    .maxDeltaE(15.0)
    .missingColorPenalty()
    .scoreThreshold(0.7)
    .build();

ColorMatchResult result = cmp.compare(templateColors, targetColors);

result.isPassed();           // true/false
result.getScore();           // 0.0 ~ 1.0 综合评分
result.getDetails();         // 每种颜色的匹配细节
result.getRuleScores();      // 每条规则的得分
result.getTemplateCoverage();// 模板覆盖率

// 1. 读取图片
Mat image = imread("pcb_board.jpg");

// 2. 定义 3 个指示灯的多边形区域
Map<String, List<Point2D>> leds = Map.of(
    "LED1", List.of(p(100,50), p(120,50), p(120,70), p(100,70)),
    "LED2", List.of(p(200,50), p(220,50), p(220,70), p(200,70)),
    "LED3", List.of(p(300,50), p(320,50), p(320,70), p(300,70))
);

// 3. 过滤条件：只看红/绿/蓝，忽略黑白灰，且 ΔE ≤ 20
ColorFilter filter = ColorFilter.builder()
    .includeColors(Set.of("red", "green", "blue"))
    .hexMatch(HexColorMatch.of("#FF0000", 20.0))
    .hexMatch(HexColorMatch.of("#00FF00", 20.0))
    .hexMatch(HexColorMatch.of("#0000FF", 20.0))
    .build();

// 4. 批量检测
Map<String, List<ColorResult>> results = ColorDetector.detectColors(
    image, leds, 1, 0.10, SortOrder.BY_PERCENT, filter);

// 5. 判断每个灯的状态
for (var entry : results.entrySet()) {
    String led = entry.getKey();
    List<ColorResult> colors = entry.getValue();
    if (colors.isEmpty()) {
        System.out.println(led + ": 灭");
    } else {
        ColorResult c = colors.get(0);
        System.out.printf("%s: %s %s (%.0f%%)%n",
            led, c.getColorName(), c.getHexColor(), c.getPercent() * 100);
    }
}

LED1: red #D42A2A (92%)
LED2: green #22CC44 (88%)
LED3: 灭

List<ColorResult> template = ColorDetector.detectColors(tplImage, tplPoly, 3, 0.05, BY_PERCENT);
List<ColorResult> product  = ColorDetector.detectImages(prodImage, prodPoly, 3, 0.05, BY_PERCENT);

ColorComparator cmp = ColorComparator.builder()
    .proportionTolerance(0.10)
    .maxDeltaE(10.0)
    .failOnMissingColor()
    .scoreThreshold(0.75)
    .build();

ColorMatchResult result = cmp.compare(template, product);
if (result.isPassed()) {
    System.out.println("颜色合格，评分: " + result.getScore());
} else {
    System.out.println("颜色不合格，查看差异:");
    for (ColorMatchDetail d : result.getDetails()) {
        System.out.printf("  %s: ΔE=%.1f, 占比差=%.1f%%, 状态=%s%n",
            d.getColorName(), d.getDeltaE(), d.getProportionDiff() * 100, d.getStatus());
    }
}