Method findColorEx

utils.cpp:732–801

在图像中查找指定颜色

// 在图像中查找指定颜色
bool Utils::findColorEx(const cv::Mat& image, int x1, int y1, int x2, int y2, const QString& hexColor, double tolerance, int& outX, int& outY) {
    // 检查 tolerance 是否在有效范围 [0, 1]
    if (tolerance < 0.0 || tolerance > 1.0) {
        qWarning() << "Tolerance should be between 0 and 1.";
        outX = -1;
        outY = -1;
        return false;
    }


    // 转换颜色
    cv::Vec3b targetColor;
    bool isConvertColor = Utils::hexToBGR(hexColor, targetColor);
    if (!isConvertColor) {
        qWarning() << "Failed to convert hex color to BGR.";
        outX = -1;
        outY = -1;
        return false;
    }

    // 限制搜索区域，确保区域在图像范围内
    x1 = std::max(0, x1);
    y1 = std::max(0, y1);
    x2 = std::min(image.cols, x2);
    y2 = std::min(image.rows, y2);

    if (x2 <= x1 || y2 <= y1) {
        qWarning() << "Invalid search region.";
        outX = -1;
        outY = -1;
        return false;
    }

    cv::Rect searchRegion(x1, y1, x2 - x1, y2 - y1);
    cv::Mat region = image(searchRegion);

    // 计算最大可能的颜色距离
    const double max_distance = std::sqrt(3.0 * 255.0 * 255.0); // ~441.67

    // 计算允许的最大距离，根据 tolerance 反转逻辑
    double allowed_distance = (1.0 - tolerance) * max_distance;

    // 遍历搜索区域内的所有像素
    for (int y = 0; y < region.rows; ++y) {
        for (int x = 0; x < region.cols; ++x) {
            cv::Vec3b pixelColor = region.at<cv::Vec3b>(y, x);

            // 计算颜色差异（欧几里得距离）
            double distance = std::sqrt(
                        std::pow(static_cast<double>(pixelColor[0]) - targetColor[0], 2) + // B
                    std::pow(static_cast<double>(pixelColor[1]) - targetColor[1], 2) + // G
                    std::pow(static_cast<double>(pixelColor[2]) - targetColor[2], 2)   // R
                    );

            // 判断是否满足容忍误差
            if (distance <= allowed_distance) {
                outX = x1 + x; // 转换为原图的坐标
                outY = y1 + y;