我在Mac OS X 10.10.2上使用opencv c ++来处理视频帧并显示它们。用waitKey显示视频的imshow的性能非常慢。
我有以下代码正确显示HD（1920x1080）灰度帧，但它运行速度大约10倍太慢（即每秒2到3帧而不是每秒30帧）。
cv::Mat framebuf[TEST_COUNT];
//--- Code here to allocate and fill the frame buffer with about 4 seconds of video. This part works correctly.
//--- This loop runs too slow by factor of approximately 10x
for (int f = 0; f < TEST_COUNT; f++)
{
cv::imshow(windowName, framebuf[f]);
cv::waitKey(33);
}
有人可以建议如何从opencv imshow（）获得实时或接近实时的性能吗？我看过很多帖子说它们实时显示视频甚至比实时更快，所以我不确定我做错了什么。任何帮助将不胜感激。
答案 0 :(得分：1)
我可能错了，但对我来说，问题不在于您的代码，而在于您的操作系统/配置。我写过一个小测试：
import cv2
import numpy as np
from random import randrange
img = np.zeros((1920, 1080), dtype = np.uint8)
counter = 0
while counter < 1000:
cv2.line(img, (randrange(0, 1920), randrange(0, 1080)), (randrange(0, 1920), randrange(0, 1080)), (randrange(0, 255)))
cv2.imshow('test', img)
temp = cv2.waitKey(1)
counter += 1
print counter
在我的机器上（Core 2 duo 2,6Ghz x64,8gb ram，ssd）完成此测试需要大约30秒。运行它，如果你得到比definitelly更大的时间你的笔记本电脑/ opencv配置错误。我在Mac OS X上使用过OpenCV 2.4.x（我觉得它是10.9）并且运行正常。重新安装OpenCV是我脑海中最明显的解决方案。当你删除OpenCV时，使用brew再次安装它 - brew install opencv --with-tbb --with-python --with-ffpmeg（或类似的东西 - 使用brew options opencv检查）应该没问题。第一个选项告诉brew使用tbb构建opencv（线程构建块 - 用于多线程的库，有时可以显着提高速度），第二个用于安装python包装器，最后一个用于安装ffmpeg（处理编解码器等）。
答案 1 :(得分：0)
您必须减少功能等待键的输入。尝试使用2-5范围内的较小数字。它还取决于您同时运行的其他进程，尝试关闭其他进程并查看是否有所改进
答案 2 :(得分：0)
您可以创建自己的窗口以显示图像。将MyWindow.m MyWindow.h文件添加到项目中。
MyWindow.h
#ifndef MY_WINDOW_H
#define MY_WINDOW_H
#ifdef __cplusplus
extern "C" {
#endif
void* createNSWindow(int x, int y, int w, int h);
void renderNSWindow(void* inwindow, void* data, int w, int h, int c);
void processNSEvent();
#ifdef __cplusplus
}
#endif
#endif
在main.cpp中的用法不要忘了waitKey
#include "MyWindow.h"
// need create a cv window and do nothing
cv::namedWindow("xxx", 1);
// create window
void* w = createNSWindow(0, 0, 0, 0);
// frame image
cv::Mat frameImage;
// render loop
renderNSWindow(w, frameImage.data, frameImage.cols, frameImage.rows, frameImage.channels());
// need waitKey to display window
processNSEvent();
实现，在MyWindow.m中，删除导入“ MyWindow.h”
#import <Cocoa/Cocoa.h>
@interface MyWindow : NSWindow
@property(nonatomic, strong) NSImageView *imgv;
@end
@implementation MyWindow
@end
static NSImage* _createNSImage(void* data, int w, int h, int c);
void* createNSWindow(int x, int y, int w, int h) {
NSRect screenFrame = [[NSScreen mainScreen] frame];
NSRect frame = NSMakeRect(x, y, w, h);
if (w == 0 || h == 0) {
frame = screenFrame;
}
MyWindow* window = [[MyWindow alloc] initWithContentRect:frame
styleMask:NSWindowStyleMaskBorderless
backing:NSBackingStoreBuffered
defer:NO] ;
//_initApp(window);
[window makeKeyAndOrderFront:NSApp];
window.titleVisibility = TRUE;
window.styleMask = NSWindowStyleMaskResizable | NSWindowStyleMaskTitled |NSWindowStyleMaskFullSizeContentView;
window.imgv = [[NSImageView alloc] initWithFrame:NSMakeRect(0, 0, frame.size.width, frame.size.height)];
[window.contentView addSubview:window.imgv];
return (void*)CFBridgingRetain(window);
}
static NSImage* _createNSImage(void* data, int w, int h, int c) {
size_t bufferLength = w * h * c;
CGDataProviderRef provider = CGDataProviderCreateWithData(NULL, data, bufferLength, NULL);
size_t bitsPerComponent = 8;
size_t bitsPerPixel = c * bitsPerComponent;
size_t bytesPerRow = c * w;
CGColorSpaceRef colorSpaceRef = CGColorSpaceCreateDeviceRGB();
CGBitmapInfo bitmapInfo = kCGBitmapByteOrder32Little | kCGImageAlphaPremultipliedLast;
if (c < 4) {
bitmapInfo = kCGBitmapByteOrderDefault | kCGImageAlphaNone;
unsigned char* buf = data;
for(int i = 0; i < w*h; i++) {
unsigned char temp = buf[i*c];
buf[i*c] = buf[i*c+c-1];
buf[i*c+c-1] = temp;
}
}
CGColorRenderingIntent renderingIntent = kCGRenderingIntentDefault;
CGImageRef iref = CGImageCreate(w,
h,
bitsPerComponent,
bitsPerPixel,
bytesPerRow,
colorSpaceRef,
bitmapInfo,
provider, // data provider
NULL, // decode
YES, // should interpolate
renderingIntent);
NSImage* image = [[NSImage alloc] initWithCGImage:iref size:NSMakeSize(w, h)];
return image;
}
void renderNSWindow(void* inwindow, void* data, int w, int h, int c) {
MyWindow* window = (__bridge MyWindow*)inwindow;
window.imgv.image = _createNSImage(data, w, h, c);
}
void processNSEvent() {
for (;;)
{
NSEvent* event = [NSApp nextEventMatchingMask:NSEventMaskAny
untilDate:[NSDate distantPast]
inMode:NSDefaultRunLoopMode
dequeue:YES];
if (event == nil)
break;
[NSApp sendEvent:event];
}
}
其他事情，waitKey现在大约需要20毫秒，您可以在后台线程中执行OpenCV，并在主线程中显示窗口。还可以使用processNSEvent代替仅耗时约10ms的waitKey。
完整的源代码：
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <dispatch/dispatch.h>
#include "MyWindow.h"
using namespace std;
using namespace cv;
int opencvfunc(int argc, const char *argv[]);
bool newFrame = false;
cv::Mat back_frame;
int main(int argc, const char * argv[]) {
cv::namedWindow("render", 1);
void* w = createNSWindow(0, 0, 0, 0);
dispatch_queue_t opencvq = dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_LOW, 0);
dispatch_async(opencvq, ^{
opencvfunc(argc, argv);
});
while(true) {
usleep(3*1000);
if(newFrame) {
std::chrono::system_clock::time_point starttime = std::chrono::system_clock::now();
renderNSWindow(w, back_frame.data, back_frame.cols, back_frame.rows, back_frame.channels());
newFrame = false;
//auto key = cv::waitKey(1);
//if (key == 'q') {
// break;
//}
processNSEvent();
std::chrono::system_clock::time_point endtime = std::chrono::system_clock::now();
std::cout << "imshow:" << std::chrono::duration_cast<std::chrono::duration<double>>(endtime-starttime).count()*1000 << std::endl;
}
}
return 0;
}
int opencvfunc(int argc, const char *argv[]) {
cv::VideoCapture cap;
cap.open(0);
if (!cap.isOpened()) {
std::cout << "Couldn't open camera 0." << endl;
return EXIT_FAILURE;
}
Mat frame, unmodified_frame;
for (;;) {
cap >> frame; // get a new frame from camera
if (frame.empty()) { // stop if we're at the end of the video
break;
}
//unmodified_frame = frame.clone();
// ...
back_frame = frame.clone();
newFrame = true;
}
return EXIT_SUCCESS;
}
答案 3 :(得分：0)
OpenCV 4已解决此问题，请更新到新版本。
还有一件事情，处理视频并在两个线程中显示视频。
#include <stdio.h>
#include <iostream>
#include <opencv2/opencv.hpp>
#include <dispatch/dispatch.h>
using namespace cv;
using namespace std;
bool newFrame = false;
Mat back_frame;
int opencvmain(int argc, char** argv ) {
// open camear
cv::VideoCapture cap;
cap.open(0);
if (!cap.isOpened()) {
std::cout << "Couldn't open camera 0." << std::endl;
return EXIT_FAILURE;
}
// define frame images
cv::Mat frame;
// frame loop
for (;;) {
// get video frame
cap >> frame;
if (frame.empty()) {
break;
}
// render
back_frame = frame.clone();
newFrame = true;
}
return 0;
}
int main(int argc, char** argv ) {
namedWindow("video", WINDOW_AUTOSIZE );
dispatch_queue_t opencvq = dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_HIGH, 0);
dispatch_async(opencvq, ^{
opencvmain(argc, argv);
});
while(true) {
usleep(3*1000);
if(newFrame) {
imshow("video", back_frame);
auto key = cv::waitKey(1);
if (key == ' ') {
break;
}
newFrame = false;
}
}
return 0;
}