python3+openCV 获取图片中文本区域的最小外接矩形实例

print("thresh =",thresh)
coords = np.column_stack(np.where(thresh > 0))//获取thresh二值灰度图片中的白色文字区域的点
print("coords =",coords)

min_rect = cv2.minAreaRect(coords)//由点集获取最小矩形（包含中心坐标点、宽和高、偏转角度）
print("min_rec =",min_rect)
box = cv2.boxPoints(min_rect)//获取最小矩形的4个顶点坐标。

# 　根据四点画原矩形
def drawRect(img, pt1, pt2, pt3, pt4, color, lineWidth):
  cv2.line(img, tuple(pt1), tuple(pt2), color, lineWidth)
  cv2.line(img, tuple(pt2), tuple(pt3), color, lineWidth)
  cv2.line(img, tuple(pt3), tuple(pt4), color, lineWidth)
  cv2.line(img, tuple(pt1), tuple(pt4), color, lineWidth)

#include<iostream>
#include<opencv2/core/core.hpp>
#include<opencv2/highgui/highgui.hpp>
using namespace std;
using namespace cv;

class ColorDetector{

private:
int maxDist; //最小差距
Vec3b target ; //目标颜色
Mat result;
public:
ColorDetector():maxDist(100),target(0,0,0)
{

}
void setColorDistanceThreshold(int distance) //设置颜色差距的阈值
{
if(distance<0)
distance=0;
maxDist=distance;
}
int getColorDistanceThreshold() const //取得颜色差距的阈值
{
return maxDist;
}

void setTargetColor(uchar blue,uchar green,uchar red) //设置需要检测的颜色
{
target=Vec3b(blue,green,red);
}

void setTargetColor(Vec3b color)
{
target=color;
}

Vec3b getTargetColor() const
{
return target;
}
Mat process(const cv::Mat &image) ;
int getDistance(const Vec3b &color) ;
};

Mat ColorDetector::process(const cv::Mat &image) 
{
result.create(image.rows,image.cols,CV_8U);
Mat_<Vec3b>::const_iterator it=image.begin<Vec3b>();
Mat_<Vec3b>::const_iterator itend=image.end<Vec3b>();
Mat_<uchar>::iterator itout=result.begin<uchar>();
for ( ; it!= itend; ++it, ++itout) 
{
if (getDistance(*it)<maxDist) 
{
*itout=255;
} 
else 
{
*itout=0;
}
}
return result;
}

int ColorDetector::getDistance(const Vec3b &color) 
{
return abs(color[0]-target[0])+
abs(color[1]-target[1])+
abs(color[2]-target[2]);
}
void main()
{
ColorDetector cdetect;
Mat img=imread("C:\\Users\\Administrator\\Desktop\\工作\\testp\\boldt.jpg");
if(img.empty())
return;

cdetect.setTargetColor(230,190,130);

imshow("original",img);
imshow("result",cdetect.process(img));
waitKey(0);
}