本文整理汇总了C++中cv::getTickCount方法的典型用法代码示例。如果您正苦于以下问题：C++ cv::getTickCount方法的具体用法？C++ cv::getTickCount怎么用？C++ cv::getTickCount使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类cv的用法示例。
在下文中一共展示了cv::getTickCount方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: srcGray
/*
* Class: io_github_melvincabatuan_fullbodydetection_MainActivity
* Method: predict
* Signature: (Landroid/graphics/Bitmap;[B)V
*/
JNIEXPORT void JNICALL Java_io_github_melvincabatuan_fullbodydetection_MainActivity_predict
(JNIEnv * pEnv, jobject clazz, jobject pTarget, jbyteArray pSource){
AndroidBitmapInfo bitmapInfo;
uint32_t* bitmapContent; // Links to Bitmap content
if(AndroidBitmap_getInfo(pEnv, pTarget, &bitmapInfo) < 0) abort();
if(bitmapInfo.format != ANDROID_BITMAP_FORMAT_RGBA_8888) abort();
if(AndroidBitmap_lockPixels(pEnv, pTarget, (void**)&bitmapContent) < 0) abort();
/// Access source array data... OK
jbyte* source = (jbyte*)pEnv->GetPrimitiveArrayCritical(pSource, 0);
if (source == NULL) abort();
/// cv::Mat for YUV420sp source and output BGRA
Mat srcGray(bitmapInfo.height, bitmapInfo.width, CV_8UC1, (unsigned char *)source);
Mat mbgra(bitmapInfo.height, bitmapInfo.width, CV_8UC4, (unsigned char *)bitmapContent);
/***********************************************************************************************/
/// Native Image Processing HERE...
if(DEBUG){
LOGI("Starting native image processing...");
}
if (full_body_cascade.empty()){
t = (double)getTickCount();
sprintf( full_body_cascade_path, "%s/%s", getenv("ASSETDIR"), "haarcascade_fullbody.xml");
/* Load the face cascades */
if( !full_body_cascade.load(full_body_cascade_path) ){
LOGE("Error loading cat face cascade");
abort();
};
t = 1000*((double)getTickCount() - t)/getTickFrequency();
if(DEBUG){
LOGI("Loading full body cascade took %lf milliseconds.", t);
}
}
std::vector<Rect> fbody;
//-- Detect full body
t = (double)getTickCount();
/// Detection took cat_face_cascade.detectMultiScale() time = 655.334471 ms
// cat_face_cascade.detectMultiScale( srcGray, faces, 1.1, 2 , 0 , Size(30, 30) ); // Scaling factor = 1.1; minNeighbors = 2 ; flags = 0; minimumSize = 30,30
// cat_face_cascade.detectMultiScale() time = 120.117185 ms
// cat_face_cascade.detectMultiScale( srcGray, faces, 1.2, 3 , 0 , Size(64, 64));
full_body_cascade.detectMultiScale( srcGray, fbody, 1.2, 2 , 0 , Size(14, 28)); // Size(double width, double height)
// scalingFactor parameters determine how much the classifier will be scaled up after each run.
// minNeighbors parameter specifies how many positive neighbors a positive face rectangle should have to be considered a possible match;
// when a potential face rectangle is moved a pixel and does not trigger the classifier any more, it is most likely that it’s a false positive.
// Face rectangles with fewer positive neighbors than minNeighbors are rejected.
// If minNeighbors is set to zero, all potential face rectangles are returned.
// The flags parameter is from the OpenCV 1.x API and should always be 0.
// minimumSize specifies the smallest face rectangle we’re looking for.
t = 1000*((double)getTickCount() - t)/getTickFrequency();
if(DEBUG){
LOGI("full_body_cascade.detectMultiScale() time = %lf milliseconds.", t);
}
// Iterate through all faces and detect eyes
t = (double)getTickCount();
for( size_t i = 0; i < fbody.size(); i++ )
{
Point center(fbody[i].x + fbody[i].width / 2, fbody[i].y + fbody[i].height / 2);
ellipse(srcGray, center, Size(fbody[i].width / 2, fbody[i].height / 2), 0, 0, 360, Scalar(255, 0, 255), 4, 8, 0);
}//endfor
t = 1000*((double)getTickCount() - t)/getTickFrequency();
if(DEBUG){
LOGI("Iterate through all faces and detecting eyes took %lf milliseconds.", t);
}
/// Display to Android
cvtColor(srcGray, mbgra, CV_GRAY2BGRA);
if(DEBUG){
LOGI("Successfully finished native image processing...");
}
/************************************************************************************************/
//.........这里部分代码省略.........