CvRect* r = (CvRect*)cvGetSeqElem( objects, i ); CvPoint center; int radius; center.x = cvRound((r->x + r->width*0.5)*scale); center.y = cvRound((r->y + r->height*0.5)*scale); radius = cvRound((r->width + r->height)*0.25*scale); cvCircle( img, center, radius, col...
printf( "detection time = %gms/n", t/((double)cvGetTickFrequency()*1000.) ); for( i = 0; i < (faces ? faces->total : 0); i++ ) { CvRect* r = (CvRect*)cvGetSeqElem( faces, i ); CvPoint center; int radius; center.x = cvRound((r->x + r->width*0.5)*scale); cent...
corners = np.rint(detection.corners) # 获取四个角点 cv2.drawContours(img, [np.array(corners, np.int)], -1, (0, 255, 255), 2) tag_family = str(detection.tag_family, encoding='utf-8') # 获取tag_family tag_id = int(detection.tag_id) # 获取tag_id object_center_x, object_center...
printf("detection time = %gms/n", t/((double)cvGetTickFrequency()*1000.) ); for( i = 0; i < (faces ? faces->total : 0); i++ ) { CvRect* r = (CvRect*)cvGetSeqElem( faces, i ); CvPoint center; int radius; center.x = cvRound((r->x + r->width*0.5)*scale); center...
{intcamera = inputName.empty() ?0: inputName[0] -'0';if(!capture.open(camera)) { cout <<"Capture from camera #"<< camera <<" didn't work"<< endl;return1; } }elseif(!inputName.empty()) { image =imread(samples::findFileOrKeep(inputName), IMREAD_COLOR);if(image.empty()) ...
circle( frame, eye_center, radius, Scalar( 255, 0, 0 ), 4 ); } } //-- Show what you got imshow( "Capture - Face detection", frame ); } 实际中,循环读摄像头并用这个detectAndDisplay函数进行检测的代码可以这么写。 Mat frame;//存放摄像头捕获图像的frame变量,它是个Mat数据 ...
frame = cv.circle(frame, eye_center, radius, (255, 0, 0 ), 4) cv.imshow('Capture - Face detection', frame) parser = argparse.ArgumentParser(description='Code for Cascade Classifier tutorial.') parser.add_argument('--face_cascade', help='Path to face cascade.', default='data/haarcasca...
confidence=scores[classID]# 过滤掉那些置信度较小的检测结果ifconfidence>0.5:# 框后接框的宽度和高度box=detection[0:4]*np.array([W,H,W,H])(centerX,centerY,width,height)=box.astype("int")# 边框的左上角x=int(centerX-(width/2))y=int(centerY-(height/2))# 更新检测出来的框boxes....
{devices=WebCamTexture.devices;cameraName=devices[0].name;cameraTexture=newWebCamTexture(cameraName,mPreviewWidth,mPreviewHeight,30);cameraTexture.Play();isPlay=true;}}Mat haarResult;byte[]bs;Mat result;OpenCvSharp.Rect[]faces;Mat src;Mat gray=newMat();Size axes=newSize();Point center=newPoint...
3. Testing Your Camera 一旦你在RPi中安装了OpenCV,让我们测试你的相机是否正常工作。 我假设您的Raspberry Pi上已经安装了PiCam。 在IDE上输入以下Python代码: import numpy as np import cv2 cap = cv2.VideoCapture(0)while(True): ret, frame = cap.read() ...