本文整理汇总了C++中cv::imshow方法的典型用法代码示例。如果您正苦于以下问题：C++ cv::imshow方法的具体用法？C++ cv::imshow怎么用？C++ cv::imshow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::imshow方法的4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: Display
void FingerTracker::Display(Mat frame, Candidate candidate) const
{
if (candidate.m_found)
{
rectangle(frame, candidate.m_windowRect.tl(), candidate.m_windowRect.br(), Scalar(0, 255, 255));
rectangle(frame, candidate.m_fingerPosition - Point(2,2), candidate.m_fingerPosition + Point(2,2), Scalar(255, 0, 0), 2);
}
#if ENABLE_LINE_DRAWING
Point prev(-1,-1);
for (auto point : m_points)
{
if (prev.x != -1)
{
line(frame, prev, point, Scalar(0, 255, 0));
}
prev = point;
}
#endif
imshow("Camera", frame);
}示例2: capture
//.........这里部分代码省略.........
bottomReady = true;
c3 = Scalar(0, 255, 255);
}
else
{
c3 = Scalar(0, 0, 255);
}
bool readyToGo = false;
if (middleReady && topReady && bottomReady)
{
c1 = Scalar(0, 255, 0);
c2 = Scalar(0, 255, 0);
c3 = Scalar(0, 255, 0);
if (!ticking)
{
start = std::chrono::system_clock::now();
ticking = true;
}
if (std::chrono::system_clock::now() - start > std::chrono::seconds(1))
{
readyToGo = true;
}
}
else
{
ticking = false;
}
#if ENABLE_DEBUG_WINDOWS
std::stringstream ss;
ss << percentageTop << ", " << percentageMiddle << ", " << percentageBottom;
putText(frame, ss.str(), Point(0, getTextSize(ss.str(), 0, 0.5, 1, nullptr).height), 0, 0.5, Scalar::all(255), 1);
cv::imshow("Thresholded", thd);
#endif
if (percentageTop >= m_calibrationTopUpperThd && percentageBottom >= m_calibrationBottomUpperThd && percentageMiddle >= m_calibrationMiddleUppperThd)
{
putText(frame, "Move finger away from camera", Point(0, getTextSize("Move finger away from camera", 0, 0.5, 1, nullptr).height), 0, 0.5, Scalar::all(255), 1);
}
else if (percentageTop <= m_calibrationTopLowerThd && percentageBottom <= m_calibrationBottomLowerThd && percentageMiddle <= m_calibrationMiddleLowerThd)
{
putText(frame, "Move finger closer to camera", Point(0, getTextSize("Move finger closer to camera", 0, 0.5, 1, nullptr).height), 0, 0.5, Scalar::all(255), 1);
}
if (readyToGo)
{
Mat framePatchHSV;
cvtColor(frame(fingerWindow), framePatchHSV, CV_BGR2HSV);
cvtColor(frame, frameHSV, CV_BGR2HSV);
MatND hist;
calcHist(&framePatchHSV, 1, m_calibrationData->m_channels, thd, hist, 2, m_calibrationData->m_histSize, (const float**)m_calibrationData->m_ranges, true, false);
m_calibrationData->m_hist = hist;
normalize(m_calibrationData->m_hist, m_calibrationData->m_hist, 0, 255, NORM_MINMAX, -1, Mat());
#if ENABLE_DEBUG_WINDOWS
double maxVal=0;
minMaxLoc(m_calibrationData->m_hist, 0, &maxVal, 0, 0);
int scale = 10;
Mat histImg = Mat::zeros(m_calibrationData->m_sbins*scale, m_calibrationData->m_hbins*10, CV_8UC3);
for( int h = 0; h < m_calibrationData->m_hbins; h++)
{
for( int s = 0; s < m_calibrationData->m_sbins; s++ )
{示例3: Process
void FingerTracker::Process(Mat frame)
{
#if ENABLE_DEBUG_WINDOWS
Mat img_display;
frame.copyTo(img_display);
#endif
// Process only Region of Interest i.e. region around current finger position
Rect roi = Rect(
Point(std::max(m_currentCandidate.m_windowRect.tl().x - m_roiSpanX, 0), std::max(m_currentCandidate.m_windowRect.tl().y - m_roiSpanY, 0)),
Point(std::min(m_currentCandidate.m_windowRect.tl().x + m_roiSpanX + m_calibrationData->m_fingerPatch.cols, frame.cols),
std::min(m_currentCandidate.m_windowRect.tl().y + m_roiSpanY + m_calibrationData->m_fingerPatch.rows, frame.rows)));
Mat frameRoi;
frame(roi).copyTo(frameRoi);
//================TEMPLATE MATCHING
int result_cols = frameRoi.cols - m_calibrationData->m_fingerPatch.cols + 1;
int result_rows = frameRoi.rows - m_calibrationData->m_fingerPatch.rows + 1;
assert(result_cols > 0 && result_rows > 0);
Mat scoreMap;
scoreMap.create(result_cols, result_rows, CV_32FC1);
// Compare current frame roi region to known candidate
// Using OpenCV matchTemplate function with correlation coefficient matching method
matchTemplate(frameRoi, m_calibrationData->m_fingerPatch, scoreMap, 3);
//================HISTOGRAM BACK PROJECTION
MatND backProjection;
Mat frameHSV;
cvtColor(frameRoi, frameHSV, CV_BGR2HSV);
calcBackProject(&frameHSV, 1, m_calibrationData->m_channels, m_calibrationData->m_hist, backProjection, (const float**)(m_calibrationData->m_ranges), 1, true);
Mat backProjectionThresholded;
threshold(backProjection, backProjectionThresholded, m_backProjectionThreshold, 255, 0);
erode(backProjectionThresholded, backProjectionThresholded, getStructuringElement(MORPH_RECT, Size(2 * m_erosionSize + 1, 2 * m_erosionSize + 1), Point(m_erosionSize, m_erosionSize)));
dilate(backProjectionThresholded, backProjectionThresholded, getStructuringElement(MORPH_RECT, Size(2 * m_dilationSize + 1, 2 * m_dilationSize + 1), Point(m_dilationSize, m_dilationSize)));
Mat backProjectionThresholdedShifted;
Rect shifted(Rect(m_calibrationData->m_fingerPatch.cols - 1, m_calibrationData->m_fingerPatch.rows - 1, scoreMap.cols, scoreMap.rows));
backProjectionThresholded(shifted).copyTo(backProjectionThresholdedShifted);
Mat maskedOutScoreMap(scoreMap.size(), CV_8U);
scoreMap.copyTo(maskedOutScoreMap, backProjectionThresholdedShifted);
//====================Localizing the best match with minMaxLoc
double minVal; double maxVal; Point minLoc; Point maxLoc;
Point matchLoc;
minMaxLoc(maskedOutScoreMap, &minVal, &maxVal, &minLoc, &maxLoc, Mat());
matchLoc = maxLoc + roi.tl();
m_currentCandidate.m_confidence = static_cast<float>(maxVal);
if (maxVal > m_candidateDetecionConfidenceThreshold)
{
m_currentCandidate.m_found = true;
m_currentCandidate.m_windowRect = Rect(matchLoc, Point(matchLoc.x + m_calibrationData->m_fingerPatch.cols , matchLoc.y + m_calibrationData->m_fingerPatch.rows));
//================Find finger position
Mat fingerWindowThresholded;
backProjectionThresholded(Rect(maxLoc, Point(maxLoc.x + m_calibrationData->m_fingerPatch.cols , maxLoc.y + m_calibrationData->m_fingerPatch.rows))).copyTo(fingerWindowThresholded);
m_currentCandidate.m_fingerPosition = GetFingerTopPosition(fingerWindowThresholded) + matchLoc;
#if ENABLE_DEBUG_WINDOWS
rectangle(img_display, m_currentCandidate.m_windowRect.tl(), m_currentCandidate.m_windowRect.br(), Scalar(255,0,0), 2, 8, 0 );
rectangle(scoreMap, m_currentCandidate.m_windowRect.tl(), m_currentCandidate.m_windowRect.br(), Scalar::all(0), 2, 8, 0 );
rectangle(img_display, m_currentCandidate.m_fingerPosition, m_currentCandidate.m_fingerPosition + Point(5,5), Scalar(255,0,0));
#endif
}
else
{
m_currentCandidate.m_found = false;
}
#if ENABLE_DEBUG_WINDOWS
std::stringstream ss;
ss << maxVal;
putText(img_display, ss.str(), Point(50, 50), 0, 0.5, Scalar(255,255,255), 1);
imshow("Overlays", img_display);
imshow("Results", scoreMap);
imshow("ResultMasked", maskedOutScoreMap);
#endif
}示例4: main
//.........这里部分代码省略.........
{
cout << static_cast<int>(id) << " ";
}
cout << endl;
for (const auto &id : ids)
{
vector<uint8_t> raw;
PacketType type;
cout << "examining " << static_cast<int>(id) << endl;
for (const auto &pkt : pkts)
{
if (pkt.getID() == id)
{
size_t new_length = pkt.getOffset() +
static_cast<size_t>(pkt.getLength());
type = pkt.getType();
if (new_length > raw.size())
{
raw.resize(new_length, 0);
}
for (size_t k = 0; k < pkt.getLength(); k++)
{
raw[pkt.getOffset() + k] = pkt.getData()[k];
}
}
}
cout << "type: " << type << endl;
cout << hex;
for (size_t j = 0; j < 512; j++)
{
if (j > 0 && (j % 32) == 0)
{
cout << endl;
}
cout << (static_cast<unsigned int>(raw[j]) & 0xFF) << " ";
}
cout << endl;
Mat img{Size(160, 120), CV_8UC3, raw.data()};
Mat dst;
//cvtColor(img, dst, CV_YUV2GRAY_UYVY);
//cvtColor(img, dst, CV_YUV2GRAY_YUY2);
//cvtColor(img, dst, CV_YUV2BGR_UYVY);
//cvtColor(img, dst, CV_YUV2BGRA_UYVY);
//cvtColor(img, dst, CV_YUV2BGR_YUY2);
//cvtColor(img, dst, CV_YUV2BGR_YVYU);
//cvtColor(img, dst, CV_YUV2BGRA_YUY2);
//cvtColor(img, dst, CV_YUV2BGRA_YVYU);
//cvtColor(img, dst, CV_YUV2GRAY_NV12);
//cvtColor(img, dst, CV_YUV2BGR_NV12);
cvtColor(img, dst, CV_YCrCb2BGR);
imshow("Police Video", dst);
waitKey(0);
ofstream out_jpeg{"out.jpg", ofstream::binary};
for (size_t j = 0; j < raw.size(); j++)
{
if (raw[j] == 0xFF && raw[j + 1] == 0xD8)
{
cout << "hit the start" << endl;
out_jpeg.write(reinterpret_cast<char *>(raw.data() + j), 2);
j++;
}
else if (raw[j] == 0xFF && raw[j + 1] == 0xDB)
{
cout << "hit the start 2" << endl;
out_jpeg.write(reinterpret_cast<char *>(raw.data() + j), 2);
j++;
}
else if (raw[j] == 0xFF && raw[j + 1] == 0xC0)
{
cout << "hit the start 3" << endl;
out_jpeg.write(reinterpret_cast<char *>(raw.data() + j), 2);
j++;
}
else if (raw[j] == 0xFF && raw[j + 1] == 0xD9)
{
cout << "hit the end" << endl;
out_jpeg.write(reinterpret_cast<char *>(raw.data() + j), 2);
return 0;
}
else
{
out_jpeg.write(reinterpret_cast<char *>(raw.data() + j), 1);
}
}
}
return 0;
}