opencv对roi区域执行hog.detectmultiscale()

这里用到的roi是在原视频上读取每帧图片，对前景进行轮廓检测，将检测到的行人目标用矩形标注出来。

利用roi=frame（rect（x0，y0，w0，z0））进行的roi标定。

希望利用detectanddraw（hog,img）对img区域进行行人检测

代码运行到hog.detectmultiscale（img）

这个时候运行到这里出现

OpenCV Error: Assertion failed (y == 0 || (data && dims >= 1 && (unsigned)y < (unsigned)size.p[0])) in cv::Mat::ptr

这报错应该是你哪个参数为空或者维度不够的问题。打个断点看看函数里面的参数哪个是不对的。

vector<Mat> roi(contours.size());这句话，你怎么能用一个整数来初始化一个mat数组。。。。。

参考：https://blog.csdn.net/yangtrees/article/details/7544401

//复原原轮廓
vector<Mat> roi(contours.size());
for (int i = 0; i < contours.size(); i++) {
				
//计算凸包和轮廓面积
double cntarea = contourArea(contours[i]);
double hullarea = contourArea(hull[i]);
Scalar color_contours = Scalar(0, 255, 0);// green - color for contours
Scalar color = Scalar(255, 0, 0); // blue - color for convex hull

//跳过轮廓面积远小于轮廓面积的目标轮廓
if (cntarea < hullarea / 5.0)
    continue;
				
//将轮廓*K,复原轮廓
for (int j = 0; j < contours[i].size(); j++)
 {
    //cout << "contour:" << i << "==" << contours[i] << endl;
    contours[i][j].x *= K;
    contours[i][j].y *= K;
 }
				
vector<Rect>boundRect(contours.size());
int x0 = 0, y0 = 0, w0 = 0, h0 = 0;
//画原视频轮廓
				
boundRect[i] = boundingRect(contours[i]);
x0 = boundRect[i].x;
y0 = boundRect[i].y;
w0 = boundRect[i].width;
h0 = boundRect[i].height;
					
if (w0 < 64 && h0 < 128)
continue;

			
					
rectangle(frame, Point(x0, y0), Point(x0 + w0, y0 + h0), Scalar(255, 0, 0), 1, 8);
/*这里就是我要圈定的ROI,是希望用前景检测的方法先圈定粘连的行人再对这部分区域进行检测*/	
roi[i] = frame(boundRect[i]);
imageROI[framenum] = roi;

//imageROI[framenum][i] = frame(boundRect[i]);
					detectanddraw(hog, imageROI[framenum][i]);

					imshow("mask", mask);
					imshow("imageROI", imageROI[framenum][i]);
					
					//保存ROI为图片
					//char save_image_name[128];
					////CvArr* s = (CvArr*)&imageROI[i];
					//sprintf_s(save_image_name, "rect_%d.jpg", i);
					//imwrite(save_image_name, imageROI[framenum][i]);
					
					//imageROI[i]=frame(Range(x0, w0), Range(y0, h0));
				//imshow("o1", Vibe_Bgs.getMask());
				//imshow("drawing", drawing);
			}

void detectanddraw(HOGDescriptor&hog, Mat&img)
{
	//矩形框数组
	vector<Rect> found, found_filtered;
	//调用gettickcount()
	//double t = (double)getTickCount();
	
	Mat gray_pic,binary_pic;
	cvtColor(img, gray_pic,CV_BGR2GRAY);
	//threshold(gray_pic, binary_pic, 10, 1, CV_THRESH_BINARY);
	//报错的地方
	hog.detectMultiScale(img, found, 0, Size(8, 8), Size(32, 32), 1.05, 2);
	
	/*t = (double)getTickCount() - t;
	cout << "dection time=" << (t * 1000 / cvGetTickFrequency()) <<" ms" << endl;
	cout << "dection result=" << found.size() << "rects" << endl;*/

	for (int i = 0; i < found.size(); i++)
	{
		Rect r = found[i];
		int j = 0;
		for (; j < found.size(); j++)
		{
			if (j != i && ((r&found[j]) == r))
				break;
		}
		if (j == found.size())
			found_filtered.push_back(r);

		for (int i = 0; i < found_filtered.size(); i++)
		{
			Rect r = found[i];
			rectangle(img, r.tl(), r.br(), Scalar(0, 255, 0), 3);
		}
	}
	//cout << "real detection result:" << found_filtered.size() << "rects" << endl;
}

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