我的问题与this one重复。那里没有解决方案。为了找到解决方案并详细说明我的具体设置，下面显示了用于从.oni文件中读取帧的函数。如果使用Type == 2运行此函数（即运行RGBD图像的＃，其中Criteria为＃），则在for循环中运行此函数应该允许用户访问每个图像。但是，彩色图像和深度图像的索引不匹配且无序。这将继续，直到waitForAnyStream超时，以便对IMG_pipeline :: listen（...）进行以下所有调用。
void IMG_pipeline::listen(int Type, int Criteria){
int exitNumber;
clock_t start = clock();
double elapsedtime;
openni::VideoFrameRef frame;
int CurrentIMGCount=0;
switch (Type){
case 0:
{
exitNumber = -1;
break;
}
case 1:
{
exitNumber = Criteria;
break;
}
case 2:
{
exitNumber = -1;
break;
}
}
for (int i = 0;i!=exitNumber;i++){
readyStream = -1;
rc = openni::OpenNI::waitForAnyStream(streams, 2, &readyStream, SAMPLE_READ_WAIT_TIMEOUT);
if (rc != openni::STATUS_OK)
{
printf("Wait failed! (timeout is %d ms)\n%s\n", SAMPLE_READ_WAIT_TIMEOUT, openni::OpenNI::getExtendedError());
//break;
}
switch (readyStream)
{
case 0:
{
// Depth
depth.readFrame(&frame);
break;
}
case 1:
{
// Color
color.readFrame(&frame);
break;
}
default:
{
printf("Unexpected stream: %i\n", readyStream);
continue;
}
}
int Height = frame.getHeight();
int Width = frame.getWidth();
cvColor.release();
cvX.release();
cvY.release();
cvZ.release();
cvColor = cv::Mat(Height, Width, CV_8UC3);
cvX = cv::Mat(Height, Width, CV_32F);
cvY = cv::Mat(Height, Width, CV_32F);
cvZ = cv::Mat(Height, Width, CV_32F);
switch (frame.getVideoMode().getPixelFormat())
{
case openni::PIXEL_FORMAT_DEPTH_1_MM:
case openni::PIXEL_FORMAT_DEPTH_100_UM:
{
openni::DepthPixel* pDepth = (openni::DepthPixel*)frame.getData();
int k =0;
for (int ri = 0; ri<Height; ri++)
{
for (int ci = 0; ci<Width; ci++)
{
float pdepth_val = pDepth[k];
openni::CoordinateConverter::convertDepthToWorld(depth, (float)ri, (float)ci, pdepth_val, &cvX.at<float>(ri,ci), &cvY.at<float>(ri,ci), &cvZ.at<float>(ri,ci));
k++;
}
}
TotalFrames[0]++;
XYZCaptured = true;
printf("Frame Index: %i \n", frame.getFrameIndex());
printf("Depth Captured. \n");
break;
}
case openni::PIXEL_FORMAT_RGB888:
{
cvColor.data = (uchar*)frame.getData();
TotalFrames[1]++;
ColorCaptured = true;
printf("Frame Index: %i \n", frame.getFrameIndex());
printf("Color Captured. \n");
break;
}
default:
printf("Unknown format \n");
}
printf("Frame extracted. \n");
if (ColorCaptured && XYZCaptured){
if (NewButNotRead == true){
IMGsMissed++;
}
else
NewButNotRead = true;
ColorCaptured = false;
XYZCaptured = false;
RGBD_out.clear();
RGBD_out.push_back(cvX);
RGBD_out.push_back(cvY);
RGBD_out.push_back(cvZ);
RGBD_out.push_back(cvColor);
CurrentIMGCount++;
printf("Image overwritten. \n");
}
elapsedtime=(clock()-start)/((double)CLOCKS_PER_SEC);
printf("Time since listen initiation: %f \n \n", elapsedtime);
if (CurrentIMGCount ==Criteria && Type == 2)
return;
else if (elapsedtime>(double)Criteria && Type==0)
return;
}
frame.release();
}
这是一个控制台输出示例：
Frame Index: 1
Depth Captured.
Frame extracted.
Time since listen initiation: 0.004846
Frame Index: 2
Depth Captured.
Frame extracted.
Time since listen initiation: 0.011601
Frame Index: 1
Color Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.012640
Depth frame count: 3
Color frame count: 2
Frame Index: 54
Color Captured.
Frame extracted.
Time since listen initiation: 0.000067
Frame Index: 57
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.005878
Depth frame count: 4
Color frame count: 3
Frame Index: 96
Color Captured.
Frame extracted.
Time since listen initiation: 0.000079
Frame Index: 99
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.003628
Depth frame count: 5
Color frame count: 4
Frame Index: 126
Color Captured.
Frame extracted.
Time since listen initiation: 0.000048
Frame Index: 130
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.004782
Depth frame count: 6
Color frame count: 5
Frame Index: 152
Color Captured.
Frame extracted.
Time since listen initiation: 0.000065
Frame Index: 156
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.008294
Depth frame count: 7
Color frame count: 6
Frame Index: 181
Color Captured.
Frame extracted.
Time since listen initiation: 0.000045
Frame Index: 185
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.004095
Depth frame count: 8
Color frame count: 7
Frame Index: 208
Color Captured.
Frame extracted.
Time since listen initiation: 0.000054
Frame Index: 212
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.004242
Depth frame count: 9
Color frame count: 8
Frame Index: 236
Color Captured.
Frame extracted.
Time since listen initiation: 0.000092
Frame Index: 240
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.005918
Depth frame count: 10
Color frame count: 9
Frame Index: 261
Color Captured.
Frame extracted.
Time since listen initiation: 0.000731
Frame Index: 262
Color Captured.
Frame extracted.
Time since listen initiation: 0.000877
Frame Index: 266
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.009347
Depth frame count: 11
Color frame count: 11
Frame Index: 286
Color Captured.
Frame extracted.
Time since listen initiation: 0.000047
Frame Index: 290
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.006080
Depth frame count: 12
Color frame count: 12
Frame Index: 311
Color Captured.
Frame extracted.
Time since listen initiation: 0.000072
Frame Index: 315
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.006453
Depth frame count: 13
Color frame count: 13
Frame Index: 337
Color Captured.
Frame extracted.
Time since listen initiation: 0.000062
Frame Index: 341
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.007485
Depth frame count: 14
Color frame count: 14
Frame Index: 367
Color Captured.
Frame extracted.
Time since listen initiation: 0.000042
Frame Index: 371
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.003758
Depth frame count: 15
Color frame count: 15
Frame Index: 390
Color Captured.
Frame extracted.
Time since listen initiation: 0.000073
Frame Index: 395
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.007917
Depth frame count: 16
Color frame count: 16
Frame Index: 416
Color Captured.
Frame extracted.
Time since listen initiation: 0.000105
Frame Index: 421
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.007554
Depth frame count: 17
Color frame count: 17
Frame Index: 453
Color Captured.
Frame extracted.
Time since listen initiation: 0.000060
Frame Index: 458
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.006150
Depth frame count: 18
Color frame count: 18
Frame Index: 481
Color Captured.
Frame extracted.
Time since listen initiation: 0.000074
Frame Index: 486
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.007169
Depth frame count: 19
Color frame count: 19
Frame Index: 517
Color Captured.
Frame extracted.
Time since listen initiation: 0.000045
Frame Index: 522
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.004196
Depth frame count: 20
Color frame count: 20
Frame Index: 547
Color Captured.
Frame extracted.
Time since listen initiation: 0.000071
Frame Index: 552
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.007375
Depth frame count: 21
Color frame count: 21
Frame Index: 625
Color Captured.
Frame extracted.
Time since listen initiation: 0.000179
Frame Index: 631
Depth Captured.
Frame extracted.
Image overwritten.
Time since listen initiation: 0.007922
Depth frame count: 22
Color frame count: 22
Wait failed! (timeout is 2000 ms)
waitForStreams: timeout reached
Unexpected stream: -1
Wait failed! (timeout is 2000 ms)
waitForStreams: timeout reached
Unexpected stream: -1
Wait failed! (timeout is 2000 ms)
waitForStreams: timeout reached
Unexpected stream: -1
Wait failed! (timeout is 2000 ms)
waitForStreams: timeout reached
Unexpected stream: -1
Wait failed! (timeout is 2000 ms)
waitForStreams: timeout reached
Unexpected stream: -1
Wait failed! (timeout is 2000 ms)
waitForStreams: timeout reached
Unexpected stream: -1
Wait failed! (timeout is 2000 ms)
waitForStreams: timeout reached
Unexpected stream: -1
这是对IMG_pipeline :: listen（...）的调用：
IMG_pipeline pip_inst;
std::string FileName = "/home/derek/Test Data/RGBD/RGBD_S2_R1";
int Type = 2;
int Criteria = 1;
std::vector<cv::Mat> OUT;
int NumMissedIMGs;
int Start;
int Stop;
pip_inst.connect(FileName);
while (true)
{
pip_inst.listen(Type, Criteria);
if (pip_inst.IsNewIMG()){
OUT = pip_inst.GetImage();
cv::imshow("Current Frame", OUT.at(3));
char c = cv::waitKey(0);
if (c == 'f')
{
printf("Depth frame count: %i \n", pip_inst.GetDepthFrameCount());
printf("Color frame count: %i \n", pip_inst.GetColorFrameCount());
}
else
{
Start = pip_inst.GetColorFrameCount();
break;
}
cv::destroyWindow("Current Frame");
}
}
彩色图像也交替出现R，G，B色调。我确信这是数据在cv :: Mat中的顺序的问题。
更有趣的是，对通过多帧的IMG_pipeline :: listen（...）的调用具有不同的索引结果，然后多次运行IMG_pipeline :: listen（...），通过.oni文件递增。
答案 0 :(得分：1)
您可以使用setSpeed命令从oni文件控制播放速度。将速度设置为-1将确保可以从oni流按顺序手动读取帧，即每次调用waitForAnyStream时，都可以保证获得流中的下一帧。请参阅＆＃34;播放速度＆＃34; here了解更多详情。
答案 1 :(得分：0)
因为uchar从编译器到编译器的差异，所以RGB信息没有被正确复制。所以RGB信息的case语句改为：
// grid class
initComponent: function() {
...
this.on('sortchange', this.onSortChange, this);
},
onSortChange: function(container, column, direction, eOpts) {
// check for dayColumnIndex
if (column && column.dayColumnIndex !== undefined) {
this.sortColumnByIndex(column.dayColumnIndex, direction);
}
},
sortColumnByIndex: function(columnIndex, direction) {
var store = this.getStore();
if (store) {
var sorterFn = function(rec1, rec2) {
var sortValue = false;
if (rec1 && rec2) {
var day1;
var daysStore1 = rec1.getDaysStore();
if (daysStore1) {
day1 = daysStore1.getAt(columnIndex);
}
var day2;
var daysStore2 = rec2.getDaysStore();
if (daysStore2) {
day2 = daysStore2.getAt(columnIndex);
}
if (day1 && day2) {
var val1 = day1.get('value');
var val2 = day2.get('value');
sortValue = val1 > val2 ? 1 : val1 === val2 ? 0 : -1;
}
}
return sortValue;
};
if (direction !== 'ASC') {
sorterFn = function(rec1, rec2) {
var sortValue = false;
if (rec1 && rec2) {
var day1;
var daysStore1 = rec1.getDaysStore();
if (daysStore1) {
day1 = daysStore1.getAt(columnIndex);
}
var day2;
var daysStore2 = rec2.getDaysStore();
if (daysStore2) {
day2 = daysStore2.getAt(columnIndex);
}
if (day1 && day2) {
var val1 = day1.get('value');
var val2 = day2.get('value');
sortValue = val1 < val2 ? 1 : val1 === val2 ? 0 : -1;
}
}
return sortValue;
};
}
store.setSorters([{
sorterFn: sorterFn
}]);
}
}
另外，为了确保我能够捕获每一帧，我放慢了文件播放速度。有趣的是打开一个.oni文件以一定的速度播放而不是抓住帧索引（我只能假设这是捕获它的速度）。无论如何，这是通过
完成的case openni::PIXEL_FORMAT_RGB888:
{
openni::RGB888Pixel* imgbuffer = (openni::RGB888Pixel*)frame.getData();
//cvColor.data = (uchar*)imgbuffer;
memcpy( cvColor.data, imgbuffer, 3*frame.getHeight()*frame.getWidth()*sizeof(uint8_t));
cv::cvtColor(cvColor,cvColor,cv::COLOR_BGR2RGB);
TotalFrames[1]++;
ColorCaptured = true;
printf("Frame Index: %i \n", frame.getFrameIndex());
printf("Color Captured. \n");
break;
}
其中Source是我的设备，而Ratio是用户指定的浮点数。希望这可以帮助将来的某个人。