Image 如何发现检测到的斑点/对象重叠，以及如何将其分组？

如何发现检测到的斑点/对象重叠，以及如何将其分组？ 例如，我有标记的blob坐标

**检测到的斑点数-5** 我的Blob坐标如下：

bool valueInRange(int value, int min, int max)
{ return (value >= min) && (value <= max); }

bool RectOverlap(Rect A, Rect B)
{
    bool xOverlap = valueInRange(A.x, B.x, B.x + B.width) ||
                    valueInRange(B.x, A.x, A.x + A.width);

    bool yOverlap = valueInRange(A.y, B.y, B.y + B.height) ||
                    valueInRange(B.y, A.y, A.y + A.height);

    return xOverlap && yOverlap;
}

起始X、起始Y-水滴宽度-水滴高度

100 100  100 100
125 125  80  90
80  80   70  50
130 130  10  10

10 10 5 8 

--如何找到重叠的对象/矩形？ --如何分组

**我们的结果应该是**** **检测到2个水滴-2**

80 80 205 210
10 10 5 8 

---

---

如何实现这一点？？？

如果我理解正确，您的blob可以被视为

cv:：Rect（StartingX、StartingY、BlobWidth、BlobHeight）

在opencv

c++

中，检查这样的矩形重叠是否容易：

rectA&rectB=rectcoverlap

其中rectcoverlap是两个矩形覆盖的矩形区域，因此如果rectcoverlap具有

.width>0

和

c.height>0

，则斑点/矩形重叠

下面是创建一些矩形并计算它们是否重叠的示例代码：

int main()
{
cv::Mat sample = cv::Mat(512,512,CV_8UC3, cv::Scalar(0,0,0));

// create sample rectangles: positionsX, positionY, width, height
cv::Rect rectA(100,50,50,200);
cv::Rect rectB(50,100,200,50);
cv::Rect rectC(400,50,100,100);

// draw in different colors:
cv::rectangle(sample, rectA, cv::Scalar(0,0,255));
cv::rectangle(sample, rectB, cv::Scalar(255,0,0));
cv::rectangle(sample, rectC, cv::Scalar(0,255,0));

// create output
cv::Mat result = cv::Mat(512,512,CV_8UC3, cv::Scalar(0,0,0));

// compute overlap with overloaded & operator for cv::Rect
cv::Rect overlapAB = rectA & rectB;
cv::Rect overlapAC = rectA & rectC;

// test for overlap and draw or terminal output
if(overlapAB.width && overlapAB.height) cv::rectangle(result, overlapAB, cv::Scalar(255,0,255), -1);
else std::cout << " no overlap between rectA and rectB" << std::endl;

if(overlapAC.width && overlapAC.height) cv::rectangle(result, overlapAC, cv::Scalar(0,255,255), -1);
else std::cout << " no overlap between rectA and rectC" << std::endl;


cv::imshow("rects", sample);
cv::imshow("overlap", result);

cv::imwrite("RectOverlapInput.png", sample);
cv::imwrite("RectOverlapOutput.png", result);

cv::waitKey(-1);


}

intmain（）
{
cv:：Mat样本=cv:：Mat（512512，cv_8UC3，cv:：Scalar（0,0,0））；
//创建示例矩形：位置X、位置Y、宽度、高度
cv:：Rect rectA（100,50,50200）；
cv：：Rect rectB（50100200,50）；
cv：：Rect rectC（400,50100100）；
//用不同的颜色绘制：
cv：：矩形（样本，矩形，cv：：标量（0,0255））；
cv:：rectangle（示例，rectB，cv:：Scalar（255,0,0））；
cv:：矩形（样本，rectC，cv:：标量（0255,0））；
//创建输出
cv:：Mat结果=cv:：Mat（512512，cv_8UC3，cv:：Scalar（0,0,0））；
//对cv:：Rect使用重载的&运算符计算重叠
cv:：Rect overlaab=rectA&rectB；
cv:：Rect overlaac=rectA&rectC；
//测试重叠和拉伸或端子输出
if（overlapAB.width和&overlapAB.height）cv:：rectangle（result，overlapAB，cv:：Scalar（255,0255），-1）；
else std:：cout如果我理解正确，您的blob可以被视为
cv:：Rect（StartingX、StartingY、BlobWidth、BlobHeight）

在opencv
c++
中，检查这样的矩形重叠是否容易：
rectA&rectB=rectcoverlap
其中rectcoverlap是两个矩形覆盖的矩形区域，因此如果rectcoverlap具有
.width>0
和
c.height>0
，则斑点/矩形重叠

下面是创建一些矩形并计算它们是否重叠的示例代码：

int main()
{
cv::Mat sample = cv::Mat(512,512,CV_8UC3, cv::Scalar(0,0,0));

// create sample rectangles: positionsX, positionY, width, height
cv::Rect rectA(100,50,50,200);
cv::Rect rectB(50,100,200,50);
cv::Rect rectC(400,50,100,100);

// draw in different colors:
cv::rectangle(sample, rectA, cv::Scalar(0,0,255));
cv::rectangle(sample, rectB, cv::Scalar(255,0,0));
cv::rectangle(sample, rectC, cv::Scalar(0,255,0));

// create output
cv::Mat result = cv::Mat(512,512,CV_8UC3, cv::Scalar(0,0,0));

// compute overlap with overloaded & operator for cv::Rect
cv::Rect overlapAB = rectA & rectB;
cv::Rect overlapAC = rectA & rectC;

// test for overlap and draw or terminal output
if(overlapAB.width && overlapAB.height) cv::rectangle(result, overlapAB, cv::Scalar(255,0,255), -1);
else std::cout << " no overlap between rectA and rectB" << std::endl;

if(overlapAC.width && overlapAC.height) cv::rectangle(result, overlapAC, cv::Scalar(0,255,255), -1);
else std::cout << " no overlap between rectA and rectC" << std::endl;


cv::imshow("rects", sample);
cv::imshow("overlap", result);

cv::imwrite("RectOverlapInput.png", sample);
cv::imwrite("RectOverlapOutput.png", result);

cv::waitKey(-1);


}

intmain（）
{
cv:：Mat样本=cv:：Mat（512512，cv_8UC3，cv:：Scalar（0,0,0））；
//创建示例矩形：位置X、位置Y、宽度、高度
cv:：Rect rectA（100,50,50200）；
cv：：Rect rectB（50100200,50）；
cv：：Rect rectC（400,50100100）；
//用不同的颜色绘制：
cv：：矩形（样本，矩形，cv：：标量（0,0255））；
cv:：rectangle（示例，rectB，cv:：Scalar（255,0,0））；
cv:：矩形（样本，rectC，cv:：标量（0255,0））；
//创建输出
cv:：Mat结果=cv:：Mat（512512，cv_8UC3，cv:：Scalar（0,0,0））；
//对cv:：Rect使用重载的&运算符计算重叠
cv:：Rect overlaab=rectA&rectB；
cv:：Rect overlaac=rectA&rectC；
//测试重叠和拉伸或端子输出
if（overlapAB.width和&overlapAB.height）cv:：rectangle（result，overlapAB，cv:：Scalar（255,0255），-1）；
else std:：cout与类似，您可以按如下方式检查两个矩形是否重叠：

bool valueInRange(int value, int min, int max)
{ return (value &gt;= min) && (value &lt;= max); }

bool RectOverlap(Rect A, Rect B)
{
    bool xOverlap = valueInRange(A.x, B.x, B.x + B.width) ||
                    valueInRange(B.x, A.x, A.x + A.width);

    bool yOverlap = valueInRange(A.y, B.y, B.y + B.height) ||
                    valueInRange(B.y, A.y, A.y + A.height);

    return xOverlap && yOverlap;
}

在此之后，您应该将所有覆盖的矩形组合并为大矩形（一组对一）以获得最终结果。
类似于，您可以检查两个矩形是否重叠，如下所示：

bool valueInRange(int value, int min, int max)
{ return (value &gt;= min) && (value &lt;= max); }

bool RectOverlap(Rect A, Rect B)
{
    bool xOverlap = valueInRange(A.x, B.x, B.x + B.width) ||
                    valueInRange(B.x, A.x, A.x + A.width);

    bool yOverlap = valueInRange(A.y, B.y, B.y + B.height) ||
                    valueInRange(B.y, A.y, A.y + A.height);

    return xOverlap && yOverlap;
}

在此之后，您应该将所有覆盖的矩形组合并为大矩形（一组对一）以获得最终结果。
第一组应为
80 80 205 215
，对吗？是的，第一组由四个矩形组成是
80 80 205 210
是应该查找和分组的第一个矩形。第一个组应该是
80 80 80 205 215
，对吗？是第一个组由四个矩形组成是的，
8080205210
是应该查找和分组的第一个矩形。请详细解释。
rectA&rectB=rectC
**这里发生了什么**我不明白。请详细解释。
rectA&rectB=rectC
**这里发生了什么**我不明白。