realsense L515 frame rate start getting slower and slower

[Billccx]

---

Required Info
Camera Model	L515
Operating System & Version	ubunru20.04
Platform	PC
Language	C++

Issue Description

Dear researchers:
I use two realsense L515 to get RGB and depth frames. However, I found that the frame rate start getting slower after running for a while, rather than keeping a constant fps. Why is was so? Here is my code:

#include <iostream>
#include <map>
#include <string>
#include <vector>
#include <librealsense2/rs.hpp>
#include <opencv2/opencv.hpp>
#include <chrono>
#include <time.h>

static cv::Mat frame_to_mat(const rs2::frame& f){
    using namespace cv;
    using namespace rs2;

    auto vf = f.as<video_frame>();
    const int w = vf.get_width();
    const int h = vf.get_height();

    if (f.get_profile().format() == RS2_FORMAT_BGR8){
        return Mat(Size(w, h), CV_8UC3, (void*)f.get_data(), Mat::AUTO_STEP);
    }
    else if (f.get_profile().format() == RS2_FORMAT_RGB8){
        auto r_rgb = Mat(Size(w, h), CV_8UC3, (void*)f.get_data(), Mat::AUTO_STEP);
        Mat r_bgr;
        cvtColor(r_rgb, r_bgr, COLOR_RGB2BGR);
        return r_bgr;
    }
    else if (f.get_profile().format() == RS2_FORMAT_Z16){
        return Mat(Size(w, h), CV_16UC1, (void*)f.get_data(), Mat::AUTO_STEP);
    }
    else if (f.get_profile().format() == RS2_FORMAT_Y8){
        return Mat(Size(w, h), CV_8UC1, (void*)f.get_data(), Mat::AUTO_STEP);
    }
    else if (f.get_profile().format() == RS2_FORMAT_DISPARITY32){
        return Mat(Size(w, h), CV_32FC1, (void*)f.get_data(), Mat::AUTO_STEP);
    }

    throw std::runtime_error("Frame format is not supported yet!");
}


void printIntrinsics(rs2_intrinsics intrin){
    std::cout<<"\ncolor intrinsics: ";
    std::cout<<intrin.width<<"  "<<intrin.height<<"  ";
    std::cout<<intrin.ppx<<"  "<<intrin.ppy<<"  ";
    std::cout<<intrin.fx<<"  "<<intrin.fy<<std::endl;
    std::cout<<"coeffs: ";
    for(auto value : intrin.coeffs)
    std::cout<<value<<"  ";
    std::cout<<std::endl;
    std::cout<<"distortion model: "<<(int)intrin.model<<std::endl;
}

int main(){
    rs2::align align_to_color(RS2_STREAM_COLOR);
    rs2::context ctx;
    std::vector<rs2::pipeline> pipelines;
    std::map<std::string, rs2::colorizer> colorizers;
    std::vector<std::string> serials; //相机id

    auto list = ctx.query_devices(); // Get a snapshot of currently connected devices
    if (list.size() == 0) {
        throw std::runtime_error("No device detected. Is it plugged in?");
    }
    else{
        std::cout<<list.size()<<std::endl;
    }

    for(auto&& item : list){
        std::string serial=item.get_info(RS2_CAMERA_INFO_SERIAL_NUMBER);
        std::cout<<serial<<std::endl;
        serials.push_back(serial);
    } 

    for (auto&& serial : serials){
        rs2::pipeline pipe(ctx);
        rs2::config cfg;
        cfg.enable_device(serial);
        cfg.enable_stream(rs2_stream::RS2_STREAM_DEPTH, 640, 480, rs2_format::RS2_FORMAT_Z16); 
        cfg.enable_stream(rs2_stream::RS2_STREAM_COLOR, 640, 480, rs2_format::RS2_FORMAT_RGB8); 
        pipe.start(cfg);
        pipelines.emplace_back(pipe);
        // Map from each device's serial number to a different colorizer
        colorizers[serial] = rs2::colorizer();
    }

    int cnt=0;
    int validcnt=0;

    std::cout<<"ready to fetch"<<std::endl;

    rs2::frameset prefs0,prefs1;
    prefs0=pipelines[0].wait_for_frames();
    prefs1=pipelines[1].wait_for_frames();
    rs2::video_frame precolor0=prefs0.get_color_frame();
    rs2::depth_frame predepth0=prefs0.get_depth_frame();
    rs2::video_frame precolor1=prefs1.get_color_frame();
    rs2::depth_frame predepth1=prefs1.get_depth_frame();

    rs2::stream_profile dprofile0 =  predepth0.get_profile();
    rs2::stream_profile cprofile0 =  precolor0.get_profile();
    rs2::stream_profile dprofile1 =  predepth1.get_profile();
    rs2::stream_profile cprofile1 =  precolor1.get_profile();

    rs2::video_stream_profile cvsprofile0(cprofile0);
    rs2_intrinsics color_intrin0 =  cvsprofile0.get_intrinsics();
    std::cout<<"for this first camera:"<<std::endl;
    printIntrinsics(color_intrin0);

    std::cout<<"for this second camera:"<<std::endl;
    rs2::video_stream_profile cvsprofile1(cprofile1);
    rs2_intrinsics color_intrin1 =  cvsprofile1.get_intrinsics();
    printIntrinsics(color_intrin1);

    std::chrono::_V2::steady_clock::time_point start,now;

    while (cnt<10000){
        start=now;
        rs2::frameset fs0,fs1;
        fs0=pipelines[0].wait_for_frames();
        fs1=pipelines[1].wait_for_frames();
        rs2::frameset aligned_frames0 = align_to_color.process(fs0);
        rs2::frameset aligned_frames1 = align_to_color.process(fs1);

        rs2::video_frame color0=aligned_frames0.get_color_frame();
        rs2::depth_frame depth0=aligned_frames0.get_depth_frame();

        rs2::video_frame color1=aligned_frames1.get_color_frame();
        rs2::depth_frame depth1=aligned_frames1.get_depth_frame();

        cv::Mat color0_mat=frame_to_mat(color0);
        cv::Mat color1_mat=frame_to_mat(color1);

        cv::Mat depth0_mat=frame_to_mat(depth0);
        cv::Mat depth1_mat=frame_to_mat(depth1);

        now=std::chrono::steady_clock::now();
        std::cout<<cnt<< "--fps:"<<
        1000000/(double)(std::chrono::duration_cast<std::chrono::microseconds>(now - start).count()) 
        << std::endl;
        cnt++;
    }
}

the output of my program is as follows:

2
f1231209
f1230584
ready to fetch
for this first camera:

color intrinsics: 640  480  331.948  248.697  600.764  600.986
coeffs: 0.171335  -0.528704  -0.00208366  2.20354e-05  0.495262  
distortion model: 4
for this second camera:

color intrinsics: 640  480  333.593  244.954  601.325  601.453
coeffs: 0.157447  -0.49804  -0.00211366  -0.00051181  0.47009  
distortion model: 4
0--fps:2.59976e-05
1--fps:21.2902
2--fps:21.5736
3--fps:21.4197
4--fps:17.5349
5--fps:22.6234
6--fps:21.0788
7--fps:21.3456
8--fps:22.4396
9--fps:22.412
10--fps:23.2872
11--fps:23.0378
12--fps:22.3174
13--fps:22.5591
14--fps:17.359
15--fps:22.0965
16--fps:20.9947
17--fps:21.4712
18--fps:15.6191
19--fps:22.6685
20--fps:22.0741
21--fps:21.4601
22--fps:21.8938
23--fps:22.7386
24--fps:21.9804
25--fps:22.8076
26--fps:22.0488
27--fps:22.302
28--fps:22.2881
29--fps:22.2198
30--fps:21.4078
31--fps:20.0856
32--fps:19.2704
33--fps:19.9263
34--fps:22.8352
35--fps:21.9346
36--fps:23.1278
37--fps:18.3311
38--fps:18.405
39--fps:16.9883
40--fps:24.1891
41--fps:22.1754
42--fps:21.9669
43--fps:22.1582
44--fps:22.1897
45--fps:21.6605
46--fps:22.7412
47--fps:23.5283
48--fps:22.1161
49--fps:21.3566
50--fps:22.0868
51--fps:21.3707
52--fps:23.2326
53--fps:22.0697
54--fps:18.1274
55--fps:18.9036
56--fps:18.6296
57--fps:18.4305
58--fps:17.6168
59--fps:18.4635
60--fps:21.5003
61--fps:22.3759
62--fps:21.126
63--fps:22.4926
64--fps:19.2186
65--fps:18.7846
66--fps:22.2846
67--fps:21.9558
68--fps:21.5633
69--fps:21.2875
70--fps:20.1649
71--fps:22.5739
72--fps:21.9433
73--fps:19.0157
74--fps:21.2409
75--fps:20.3331
76--fps:17.7321
77--fps:22.7273
78--fps:21.5517
79--fps:21.8551
80--fps:22.3829
81--fps:22.7485
82--fps:21.6492
83--fps:23.7001
84--fps:19.3904
85--fps:23.7756
86--fps:23.7001
87--fps:22.6608
88--fps:22.7739
89--fps:22.877
90--fps:22.5388
91--fps:21.8188
92--fps:22.3214
93--fps:22.4341
94--fps:23.8095
95--fps:22.5276
96--fps:22.9806
97--fps:22.8802
98--fps:21.3908
99--fps:22.6984
100--fps:21.4261
101--fps:18.8879
102--fps:21.0447
103--fps:23.1166
104--fps:23.0622
105--fps:21.6029
106--fps:23.6485
107--fps:21.9829
108--fps:21.4459
109--fps:21.3456
110--fps:22.9463
111--fps:22.9379
112--fps:23.8203
113--fps:23.0256
114--fps:22.5703
115--fps:16.6606
116--fps:19.2864
117--fps:16.1559
118--fps:16.9477
119--fps:22.6311
120--fps:22.3279
121--fps:21.0633
122--fps:22.7796
123--fps:22.5114
124--fps:22.8269
125--fps:22.409
126--fps:21.2269
127--fps:15.9962
128--fps:21.0766
129--fps:22.5601
130--fps:22.4457
131--fps:21.8522
132--fps:23.1551
133--fps:22.0522
134--fps:21.4105
135--fps:21.2825
136--fps:20.993
137--fps:19.145
138--fps:23.5134
139--fps:22.2163
140--fps:20.5326
141--fps:19.9824
142--fps:19.4609
143--fps:18.9118
144--fps:16.2514
145--fps:15.2607
146--fps:14.5582
147--fps:10.228
148--fps:9.47742
149--fps:13.9016
150--fps:14.1195
151--fps:13.428
152--fps:13.277
153--fps:12.6441
154--fps:9.75467
155--fps:11.5219
156--fps:10.3882
157--fps:10.2305
158--fps:10.5971
159--fps:10.3123
160--fps:10.2783
161--fps:9.28859
162--fps:9.70601
163--fps:7.84406
164--fps:10.4988
165--fps:7.80427
166--fps:7.41955
167--fps:12.2525
168--fps:10.1352
169--fps:10.3779
170--fps:10.0048
171--fps:10.4815
172--fps:6.40381
173--fps:9.93581
174--fps:10.0043
175--fps:9.81354
176--fps:10.0147
177--fps:9.26999
178--fps:10.8329
179--fps:10.5704
180--fps:10.0458
181--fps:9.64757
182--fps:9.69265
183--fps:10.0742
184--fps:10.5025
185--fps:10.0832
186--fps:9.11046
187--fps:10.9327
188--fps:10.1116
189--fps:9.0867
190--fps:9.74592
191--fps:8.61015
192--fps:8.09697
193--fps:8.16287
194--fps:8.46339
195--fps:11.2726
196--fps:12.0825
197--fps:12.9809
198--fps:13.4353
199--fps:12.6891
200--fps:13.6175
201--fps:13.5439
202--fps:11.8837
203--fps:9.36198
204--fps:8.57677
205--fps:8.89047
206--fps:12.2791
207--fps:11.1547
208--fps:10.9517
209--fps:10.3089
210--fps:7.78804
211--fps:7.40565
212--fps:7.83994
213--fps:8.73286
214--fps:11.6545
215--fps:10.7823
216--fps:10.0424
217--fps:10.6197
218--fps:9.42943
219--fps:10.1925
220--fps:10.0284
221--fps:9.88572
222--fps:9.90275
223--fps:8.79995
224--fps:8.50138
225--fps:8.86226
226--fps:9.33001
227--fps:9.1894
228--fps:10.0591
229--fps:10.1393
230--fps:9.53598
231--fps:9.64506
232--fps:7.2794
233--fps:9.19599
234--fps:9.40389
235--fps:7.18716
236--fps:8.28343
237--fps:10.4581
238--fps:9.81017
239--fps:10.3384
240--fps:9.14294
241--fps:8.6143
242--fps:11.2463
243--fps:9.51095
244--fps:10.3261
245--fps:10.4814
246--fps:9.86855
247--fps:9.49677
248--fps:9.83429
249--fps:10.1949
250--fps:8.98545
251--fps:9.52653
252--fps:8.64185
253--fps:9.07211
254--fps:7.97505
255--fps:7.05413
256--fps:6.87129
257--fps:6.89337
258--fps:9.55776
259--fps:12.2407
260--fps:11.6816
261--fps:11.1926
262--fps:9.79231
263--fps:9.5011
264--fps:8.78588
265--fps:9.55941
266--fps:9.5142
267--fps:8.52791
268--fps:9.72091
269--fps:9.70855
270--fps:9.85824
271--fps:10.2905
272--fps:10.3101
273--fps:6.99232
274--fps:8.18049
275--fps:9.20683
276--fps:10.3038
277--fps:9.37981
278--fps:8.83384
279--fps:11.1151
280--fps:10.4648
281--fps:10.1724
282--fps:8.58922
283--fps:10.9966
284--fps:11.0684
285--fps:11.1914
286--fps:10.4979
287--fps:8.86886
288--fps:7.33832
289--fps:9.2377
290--fps:10.7698
291--fps:10.9545
292--fps:10.259
293--fps:9.98652
294--fps:9.00471
295--fps:10.174
296--fps:11.1593
297--fps:9.96582
298--fps:10.6744
299--fps:7.03507
300--fps:9.48452
301--fps:11.2987
302--fps:11.5274
303--fps:10.2836
304--fps:10.0254
305--fps:9.945
306--fps:9.57176

As you can see, the fps slow down from 20 to 10. Besides that, I noticed that realsenseL515 get ‘fever’ after running for a while. Is fps slowing down caused by overheating?

I am really looking forward to you reply and thanks in advance!

[MartyG-RealSense]

Hi @Billccx If performance is slowing down over time then there may be a memory leak, where the memory of the computer is progressively consumed over time and causes the program's performance to degrade and even freeze / crash. In Ubuntu you can use a system monitoring tool such as htop to monitor memory usage whilst your program is running to see whether there is a leak.

If you are using the RealSense Viewer tool then memory leaks can occur for a small number of RealSense users if the GLSL options are enabled. You can disable GLSL in the Viewer's settings interface using instructions at #8110 (comment) to see whether it improves the reliability of performance.

In regard to the L515's temperature, if the casing is hot to the touch only a few minutes after streaming begins then this can indicate that there is an overheating problem related to USB (either a glitch on the USB port or a bad USB cable). The camera's temperatures can be monitored in real-time in the RealSense Viewer under the 'Controls' category of the L500 Depth Sensor options.

You can also unplug the micro-sized end of the USB cable from the base of the L515 camera, turn the connector around the opposite way and re-insert it into the base of the camera (as USB-C cables are two-way insertion at the micro-sized end) to see whether performance improves.

[Billccx]

@MartyG-RealSense
Thanks a lot for such a quick reply!
I tried htop to monitor the memory. However it seems that I failed to find the sign of memory leak?
Here is the htop output when I started to run, the fps (not precise) is around 30-40.

After running for a while, the htop output is as follow, the fps is around 10-15.

Could you please tell me why it was so?
I'd be grateful if you would have a look at my source code.
Thanks!

[MartyG-RealSense]

Thanks very much for testimg memory usage and for your images. Next, please try going to the RGB section of the Viewer's options and disabling an option called Auto-Exposure Priority (whilst keeping Auto-Exposure enabled). If Auto-Exposure is enabled and Auto-Exposure Priority is disabled then the RealSense SDK should try to enforce a constant FPS rate instead of permitting the FPS to vary.

Also, did you find that the camera casing was hot to the touch only a few minutes after streaming began, and did you try reversing the connector?

[Billccx]

@MartyG-RealSense
Thanks for your advice!
I haved disabled the "Auto-Exposure Priority" while keeping "Auto-Exposure" enabled. The fps in realsense-viewer is very stable. (Hardware fps 30/ viewer fps 17-22)

Unfortunately, when I try to run my source code, the problem still exist! Even though I have already set Auto-Exposure Priority off in my code:

for (auto&& serial : serials){
    rs2::pipeline pipe(ctx);
    rs2::config cfg;
    cfg.enable_device(serial);
    cfg.enable_stream(rs2_stream::RS2_STREAM_DEPTH, 640, 480, rs2_format::RS2_FORMAT_Z16); 
    cfg.enable_stream(rs2_stream::RS2_STREAM_COLOR, 640, 480, rs2_format::RS2_FORMAT_RGB8); 
    auto prof=pipe.start(cfg);
    auto sensors = prof.get_device().query_sensors();
    for(auto item:sensors) std::cout<<item.get_info(RS2_CAMERA_INFO_NAME)<<std::endl;

    auto rgb=prof.get_device().first<rs2::color_sensor>();
    rgb.set_option(RS2_OPTION_ENABLE_AUTO_EXPOSURE, 1);
    rgb.set_option(RS2_OPTION_AUTO_EXPOSURE_PRIORITY,0);

    pipelines.emplace_back(pipe);
    // Map from each device's serial number to a different colorizer
    colorizers[serial] = rs2::colorizer();
}

the output of my code are as follows:

~/code/C++/librealsense-2.50.0/examples/rs_bazel$ ./bazel-bin/src4/fps

2
f1231209
f1230584
L500 Depth Sensor
RGB Camera
Motion Module
L500 Depth Sensor
RGB Camera
Motion Module
ready to fetch
for this first camera:

color intrinsics: 640  480  331.948  248.697  600.764  600.986
coeffs: 0.171335  -0.528704  -0.00208366  2.20354e-05  0.495262  
distortion model: 4
for this second camera:

color intrinsics: 640  480  333.593  244.954  601.325  601.453
coeffs: 0.157447  -0.49804  -0.00211366  -0.00051181  0.47009  
distortion model: 4
0--fps:8.02835e-05
1--fps:18.9283
2--fps:18.8002
3--fps:21.9819
4--fps:21.8269
5--fps:18.7547
6--fps:21.034
7--fps:23.6206
8--fps:18.766
9--fps:22.0264
10--fps:23.0489
11--fps:23.5322
12--fps:21.4321
13--fps:21.1721
14--fps:23.3046
15--fps:21.901
16--fps:23.1353
17--fps:23.1455
18--fps:22.9505
19--fps:22.2207
20--fps:22.9437
21--fps:23.561
22--fps:23.1107
23--fps:24.024
24--fps:21.2734
25--fps:17.1942
26--fps:20.1191
27--fps:16.4614
28--fps:18.2202
29--fps:17.2622
30--fps:17.5908
31--fps:17.1057
32--fps:16.7434
33--fps:14.8524
34--fps:11.5517
35--fps:9.47445
36--fps:12.2414
37--fps:10.8074
38--fps:11.5182
39--fps:10.3991
40--fps:10.3449
41--fps:10.4062
42--fps:10.1002
43--fps:9.39761
44--fps:9.38958
45--fps:8.18438
46--fps:8.65816
47--fps:8.57442
48--fps:6.21616
49--fps:6.79297
50--fps:5.96805
51--fps:6.06502
52--fps:7.82473
53--fps:6.97623
54--fps:6.53053
55--fps:6.8645
56--fps:7.46977
57--fps:8.45866
58--fps:7.77454
59--fps:7.35532
60--fps:7.48963
61--fps:6.2007
62--fps:4.05313
63--fps:4.96662
64--fps:5.38497
65--fps:6.30601
66--fps:5.48195
67--fps:6.3937
68--fps:6.50656
69--fps:7.01331
70--fps:6.61892
71--fps:7.2247
72--fps:5.65032
73--fps:5.43877
74--fps:4.93813
75--fps:5.49843
76--fps:5.37285
77--fps:5.71122
78--fps:5.41243
79--fps:6.11247
80--fps:7.28959
81--fps:7.54023
82--fps:7.0368
83--fps:5.5513
84--fps:7.64175
85--fps:7.96324
86--fps:7.00687
87--fps:6.20952
88--fps:5.11949

The fps slow down quickly, from 20 to 5~10, only within 80 iterations.
I think the most likely explanation is there is something wrong with my source code. Unfortunately, I do not know how to correct it. :(
Sorry to have troubled you so much and I am looking forward to your reply.

Here is my source code:

#include <iostream>
#include <map>
#include <string>
#include <vector>
#include <librealsense2/rs.hpp>
#include <opencv2/opencv.hpp>
#include <chrono>
#include <time.h>

static cv::Mat frame_to_mat(const rs2::frame& f){
    using namespace cv;
    using namespace rs2;

    auto vf = f.as<video_frame>();
    const int w = vf.get_width();
    const int h = vf.get_height();

    if (f.get_profile().format() == RS2_FORMAT_BGR8){
        return Mat(Size(w, h), CV_8UC3, (void*)f.get_data(), Mat::AUTO_STEP);
    }
    else if (f.get_profile().format() == RS2_FORMAT_RGB8){
        auto r_rgb = Mat(Size(w, h), CV_8UC3, (void*)f.get_data(), Mat::AUTO_STEP);
        Mat r_bgr;
        cvtColor(r_rgb, r_bgr, COLOR_RGB2BGR);
        return r_bgr;
    }
    else if (f.get_profile().format() == RS2_FORMAT_Z16){
        return Mat(Size(w, h), CV_16UC1, (void*)f.get_data(), Mat::AUTO_STEP);
    }
    else if (f.get_profile().format() == RS2_FORMAT_Y8){
        return Mat(Size(w, h), CV_8UC1, (void*)f.get_data(), Mat::AUTO_STEP);
    }
    else if (f.get_profile().format() == RS2_FORMAT_DISPARITY32){
        return Mat(Size(w, h), CV_32FC1, (void*)f.get_data(), Mat::AUTO_STEP);
    }

    throw std::runtime_error("Frame format is not supported yet!");
}


void printIntrinsics(rs2_intrinsics intrin){
    std::cout<<"\ncolor intrinsics: ";
    std::cout<<intrin.width<<"  "<<intrin.height<<"  ";
    std::cout<<intrin.ppx<<"  "<<intrin.ppy<<"  ";
    std::cout<<intrin.fx<<"  "<<intrin.fy<<std::endl;
    std::cout<<"coeffs: ";
    for(auto value : intrin.coeffs)
    std::cout<<value<<"  ";
    std::cout<<std::endl;
    std::cout<<"distortion model: "<<(int)intrin.model<<std::endl;
}

int main(){
    rs2::align align_to_color(RS2_STREAM_COLOR);
    rs2::context ctx;
    std::vector<rs2::pipeline> pipelines;
    std::map<std::string, rs2::colorizer> colorizers;
    std::vector<std::string> serials;

    auto list = ctx.query_devices(); // Get a snapshot of currently connected devices
    if (list.size() == 0) {
        throw std::runtime_error("No device detected. Is it plugged in?");
    }
    else{
        std::cout<<list.size()<<std::endl;
    }

    for(auto&& item : list){
        std::string serial=item.get_info(RS2_CAMERA_INFO_SERIAL_NUMBER);
        std::cout<<serial<<std::endl;
        serials.push_back(serial);
    } 

    for (auto&& serial : serials){
        rs2::pipeline pipe(ctx);
        rs2::config cfg;
        cfg.enable_device(serial);
        cfg.enable_stream(rs2_stream::RS2_STREAM_DEPTH, 640, 480, rs2_format::RS2_FORMAT_Z16); 
        cfg.enable_stream(rs2_stream::RS2_STREAM_COLOR, 640, 480, rs2_format::RS2_FORMAT_RGB8); 
        auto prof=pipe.start(cfg);
        auto sensors = prof.get_device().query_sensors();
        for(auto item:sensors) std::cout<<item.get_info(RS2_CAMERA_INFO_NAME)<<std::endl;

        auto rgb=prof.get_device().first<rs2::color_sensor>();
        rgb.set_option(RS2_OPTION_ENABLE_AUTO_EXPOSURE, 1);
        rgb.set_option(RS2_OPTION_AUTO_EXPOSURE_PRIORITY,0);

        pipelines.emplace_back(pipe);
        // Map from each device's serial number to a different colorizer
        colorizers[serial] = rs2::colorizer();
    }

    int cnt=0;
    int validcnt=0;
    
    std::cout<<"ready to fetch"<<std::endl;

    rs2::frameset prefs0,prefs1;
    prefs0=pipelines[0].wait_for_frames();
    prefs1=pipelines[1].wait_for_frames();
    rs2::video_frame precolor0=prefs0.get_color_frame();
    rs2::depth_frame predepth0=prefs0.get_depth_frame();
    rs2::video_frame precolor1=prefs1.get_color_frame();
    rs2::depth_frame predepth1=prefs1.get_depth_frame();

    rs2::stream_profile dprofile0 =  predepth0.get_profile();
    rs2::stream_profile cprofile0 =  precolor0.get_profile();
    rs2::stream_profile dprofile1 =  predepth1.get_profile();
    rs2::stream_profile cprofile1 =  precolor1.get_profile();

    rs2::video_stream_profile cvsprofile0(cprofile0);
    rs2_intrinsics color_intrin0 =  cvsprofile0.get_intrinsics();
    std::cout<<"for this first camera:"<<std::endl;
    printIntrinsics(color_intrin0);

    std::cout<<"for this second camera:"<<std::endl;
    rs2::video_stream_profile cvsprofile1(cprofile1);
    rs2_intrinsics color_intrin1 =  cvsprofile1.get_intrinsics();
    printIntrinsics(color_intrin1);

    std::chrono::_V2::steady_clock::time_point start,now;

    while (cnt<10000){
        start=now;
        rs2::frameset fs0,fs1;
        fs0=pipelines[0].wait_for_frames();
        fs1=pipelines[1].wait_for_frames();
        rs2::frameset aligned_frames0 = align_to_color.process(fs0);
        rs2::frameset aligned_frames1 = align_to_color.process(fs1);

        rs2::video_frame color0=aligned_frames0.get_color_frame();
        rs2::depth_frame depth0=aligned_frames0.get_depth_frame();

        rs2::video_frame color1=aligned_frames1.get_color_frame();
        rs2::depth_frame depth1=aligned_frames1.get_depth_frame();

        cv::Mat color0_mat=frame_to_mat(color0);
        cv::Mat color1_mat=frame_to_mat(color1);

        cv::Mat depth0_mat=frame_to_mat(depth0);
        cv::Mat depth1_mat=frame_to_mat(depth1);

        now=std::chrono::steady_clock::now();

        std::cout<<cnt<< "--fps:"<<
        1000000/(double)(std::chrono::duration_cast<std::chrono::microseconds>(now - start).count()) 
        << std::endl;
        cnt++;
    }

    return 0;
}

[MartyG-RealSense]

I see that you are using multicam code in your project to access two L515 cameras. It is recommended though to use poll_for_frames() instead of wait_for_frames() for an application that is accessing multiple cameras, like the SDK's rs-multicam example program does.

[Billccx]

@MartyG-RealSense
Thanks for your advice!
I think I have already found what leads to program slowing down. It is rs2::align.
It seems that after hundreds of iterations, the time cost on RGB and depth alignment grow larger and larger.
here is my code:

#include <iostream>
#include <map>
#include <string>
#include <vector>
#include <librealsense2/rs.hpp>
#include <opencv2/opencv.hpp>
#include <chrono>
#include <time.h>

int main(){
    rs2::align align_to_color(RS2_STREAM_COLOR);
    rs2::context ctx;
    std::vector<rs2::pipeline> pipelines;
    std::map<std::string, rs2::colorizer> colorizers;
    std::vector<std::string> serials;

    auto list = ctx.query_devices(); // Get a snapshot of currently connected devices
    if (list.size() == 0) {
        throw std::runtime_error("No device detected. Is it plugged in?");
    }
    else{
        std::cout<<list.size()<<std::endl;
    }

    for(auto&& item : list){
        std::string serial=item.get_info(RS2_CAMERA_INFO_SERIAL_NUMBER);
        std::cout<<serial<<std::endl;
        serials.push_back(serial);
    } 

    for (auto&& serial : serials){
        rs2::pipeline pipe(ctx);
        rs2::config cfg;
        cfg.enable_device(serial);
        cfg.enable_stream(rs2_stream::RS2_STREAM_DEPTH, 640, 480, rs2_format::RS2_FORMAT_Z16); 
        cfg.enable_stream(rs2_stream::RS2_STREAM_COLOR, 640, 480, rs2_format::RS2_FORMAT_RGB8); 
        auto prof=pipe.start(cfg);
        auto sensors = prof.get_device().query_sensors();
        for(auto item:sensors) std::cout<<item.get_info(RS2_CAMERA_INFO_NAME)<<std::endl;

        auto rgb=prof.get_device().first<rs2::color_sensor>();
        rgb.set_option(RS2_OPTION_ENABLE_AUTO_EXPOSURE, 1);
        rgb.set_option(RS2_OPTION_AUTO_EXPOSURE_PRIORITY,0);

        pipelines.emplace_back(pipe);
        // Map from each device's serial number to a different colorizer
        colorizers[serial] = rs2::colorizer();
    }

    int cnt=0;   
    std::cout<<"ready to fetch"<<std::endl;

    std::chrono::_V2::steady_clock::time_point start,now;
    std::chrono::_V2::steady_clock::time_point r,l;

    while (cnt<10000){
        start=now;
        rs2::frameset fs0,fs1;
        fs0=pipelines[0].wait_for_frames();
        fs1=pipelines[1].wait_for_frames();


        l=std::chrono::steady_clock::now();

        rs2::frameset aligned_frames0 = align_to_color.process(fs0);
        rs2::frameset aligned_frames1 = align_to_color.process(fs1);


        r=std::chrono::steady_clock::now();

        std::cout<<cnt<< "-RGB depth alignment time cost: "<<
        (double)(std::chrono::duration_cast<std::chrono::duration<double>>(r - l).count()) 
        <<" seconds       ";

        rs2::video_frame color0=fs0.get_color_frame();
        rs2::depth_frame depth0=fs0.get_depth_frame();

        rs2::video_frame color1=fs1.get_color_frame();
        rs2::depth_frame depth1=fs1.get_depth_frame();

        now=std::chrono::steady_clock::now();

        std::cout<<cnt<< "--fps:"<<
        1000000/(double)(std::chrono::duration_cast<std::chrono::microseconds>(now - start).count()) 
        << std::endl;
        cnt++;
    }

    return 0;
}

the output of the program is as follow:

2
f1231209
f1230584
L500 Depth Sensor
RGB Camera
Motion Module
L500 Depth Sensor
RGB Camera
Motion Module
ready to fetch
0-RGB depth alignment time cost: 0.229177 seconds       0--fps:4.24504e-05
1-RGB depth alignment time cost: 0.038753 seconds       1--fps:25.6984
2-RGB depth alignment time cost: 0.0390417 seconds       2--fps:25.5323
3-RGB depth alignment time cost: 0.0389218 seconds       3--fps:25.6174
4-RGB depth alignment time cost: 0.03765 seconds       4--fps:26.4823
5-RGB depth alignment time cost: 0.0386433 seconds       5--fps:25.7951
6-RGB depth alignment time cost: 0.0388555 seconds       6--fps:25.5598
7-RGB depth alignment time cost: 0.0375068 seconds       7--fps:26.5936
8-RGB depth alignment time cost: 0.0374081 seconds       8--fps:26.6574
9-RGB depth alignment time cost: 0.0379117 seconds       9--fps:26.2992
10-RGB depth alignment time cost: 0.0387661 seconds       10--fps:25.7215
11-RGB depth alignment time cost: 0.0379902 seconds       11--fps:26.2502
12-RGB depth alignment time cost: 0.0387106 seconds       12--fps:25.7639
13-RGB depth alignment time cost: 0.0375177 seconds       13--fps:26.5315
14-RGB depth alignment time cost: 0.0367369 seconds       14--fps:27.1518
15-RGB depth alignment time cost: 0.0364953 seconds       15--fps:27.3299
16-RGB depth alignment time cost: 0.0366364 seconds       16--fps:27.2227
17-RGB depth alignment time cost: 0.0366454 seconds       17--fps:27.2057
18-RGB depth alignment time cost: 0.0361884 seconds       18--fps:27.5452
19-RGB depth alignment time cost: 0.0360009 seconds       19--fps:27.6909
20-RGB depth alignment time cost: 0.03593 seconds       20--fps:27.7493
21-RGB depth alignment time cost: 0.0369931 seconds       21--fps:26.9564
22-RGB depth alignment time cost: 0.0400367 seconds       22--fps:24.8558
23-RGB depth alignment time cost: 0.0371478 seconds       23--fps:26.8492
24-RGB depth alignment time cost: 0.036921 seconds       24--fps:27.0161
25-RGB depth alignment time cost: 0.0365378 seconds       25--fps:27.2881
26-RGB depth alignment time cost: 0.0356602 seconds       26--fps:27.9345
27-RGB depth alignment time cost: 0.036634 seconds       27--fps:27.2146
28-RGB depth alignment time cost: 0.0369219 seconds       28--fps:26.9942
29-RGB depth alignment time cost: 0.0367923 seconds       29--fps:27.0981
30-RGB depth alignment time cost: 0.0382679 seconds       30--fps:26.0559
31-RGB depth alignment time cost: 0.0371203 seconds       31--fps:26.8075
32-RGB depth alignment time cost: 0.0370518 seconds       32--fps:26.9193
33-RGB depth alignment time cost: 0.036352 seconds       33--fps:27.4363
34-RGB depth alignment time cost: 0.0364952 seconds       34--fps:27.3246
35-RGB depth alignment time cost: 0.037499 seconds       35--fps:26.5774
36-RGB depth alignment time cost: 0.0364835 seconds       36--fps:27.3276
37-RGB depth alignment time cost: 0.0360367 seconds       37--fps:27.6732
38-RGB depth alignment time cost: 0.035875 seconds       38--fps:27.7708
39-RGB depth alignment time cost: 0.0354098 seconds       39--fps:28.1468
40-RGB depth alignment time cost: 0.0383673 seconds       40--fps:25.9632
41-RGB depth alignment time cost: 0.0373736 seconds       41--fps:26.6596
42-RGB depth alignment time cost: 0.0357121 seconds       42--fps:27.922
43-RGB depth alignment time cost: 0.0347376 seconds       43--fps:28.7043
44-RGB depth alignment time cost: 0.0344683 seconds       44--fps:28.9243
45-RGB depth alignment time cost: 0.0348688 seconds       45--fps:28.5976
46-RGB depth alignment time cost: 0.0375928 seconds       46--fps:26.5189
47-RGB depth alignment time cost: 0.0383193 seconds       47--fps:26.0125
48-RGB depth alignment time cost: 0.0370604 seconds       48--fps:26.8861
49-RGB depth alignment time cost: 0.037458 seconds       49--fps:26.6219
50-RGB depth alignment time cost: 0.0379696 seconds       50--fps:26.2619
51-RGB depth alignment time cost: 0.0374925 seconds       51--fps:26.5632
52-RGB depth alignment time cost: 0.0366939 seconds       52--fps:27.1769
53-RGB depth alignment time cost: 0.0401451 seconds       53--fps:24.8429
54-RGB depth alignment time cost: 0.0458157 seconds       54--fps:21.7467
55-RGB depth alignment time cost: 0.0378522 seconds       55--fps:26.3442
56-RGB depth alignment time cost: 0.0364481 seconds       56--fps:27.3388
57-RGB depth alignment time cost: 0.0362236 seconds       57--fps:27.527
58-RGB depth alignment time cost: 0.0355616 seconds       58--fps:28.0458
59-RGB depth alignment time cost: 0.0349894 seconds       59--fps:28.4835
60-RGB depth alignment time cost: 0.0345176 seconds       60--fps:28.8942
61-RGB depth alignment time cost: 0.0353968 seconds       61--fps:28.1738
62-RGB depth alignment time cost: 0.0364978 seconds       62--fps:27.3082
63-RGB depth alignment time cost: 0.0355464 seconds       63--fps:28.0426
64-RGB depth alignment time cost: 0.0357885 seconds       64--fps:27.8489
65-RGB depth alignment time cost: 0.0439528 seconds       65--fps:22.6896
66-RGB depth alignment time cost: 0.0461307 seconds       66--fps:21.6146
67-RGB depth alignment time cost: 0.0462508 seconds       67--fps:21.5773
68-RGB depth alignment time cost: 0.0474853 seconds       68--fps:21.0133
69-RGB depth alignment time cost: 0.0452652 seconds       69--fps:22.0313
70-RGB depth alignment time cost: 0.0450759 seconds       70--fps:22.1107
71-RGB depth alignment time cost: 0.0475847 seconds       71--fps:20.8459
72-RGB depth alignment time cost: 0.0470258 seconds       72--fps:21.2197
73-RGB depth alignment time cost: 0.0427415 seconds       73--fps:23.334
74-RGB depth alignment time cost: 0.0439944 seconds       74--fps:22.6511
75-RGB depth alignment time cost: 0.0439473 seconds       75--fps:22.6727
76-RGB depth alignment time cost: 0.0460091 seconds       76--fps:21.6109
77-RGB depth alignment time cost: 0.0428149 seconds       77--fps:23.2975
78-RGB depth alignment time cost: 0.041497 seconds       78--fps:24.0327
79-RGB depth alignment time cost: 0.039585 seconds       79--fps:25.156
80-RGB depth alignment time cost: 0.0430873 seconds       80--fps:23.1444
81-RGB depth alignment time cost: 0.0524004 seconds       81--fps:19.0161
82-RGB depth alignment time cost: 0.0352922 seconds       82--fps:28.2382
83-RGB depth alignment time cost: 0.0384508 seconds       83--fps:25.9336
84-RGB depth alignment time cost: 0.0400018 seconds       84--fps:24.854
85-RGB depth alignment time cost: 0.0376006 seconds       85--fps:26.5238
86-RGB depth alignment time cost: 0.0382437 seconds       86--fps:26.0824
87-RGB depth alignment time cost: 0.0374226 seconds       87--fps:26.6283
88-RGB depth alignment time cost: 0.0370726 seconds       88--fps:26.894
89-RGB depth alignment time cost: 0.0376059 seconds       89--fps:26.5196
90-RGB depth alignment time cost: 0.0365395 seconds       90--fps:27.2866
91-RGB depth alignment time cost: 0.049035 seconds       91--fps:20.2996
92-RGB depth alignment time cost: 0.0449439 seconds       92--fps:22.202
93-RGB depth alignment time cost: 0.0346676 seconds       93--fps:28.7588
94-RGB depth alignment time cost: 0.0354643 seconds       94--fps:28.1136
95-RGB depth alignment time cost: 0.0351765 seconds       95--fps:28.3286
96-RGB depth alignment time cost: 0.0380442 seconds       96--fps:26.1897
97-RGB depth alignment time cost: 0.0356227 seconds       97--fps:27.9634
98-RGB depth alignment time cost: 0.0350188 seconds       98--fps:28.4819
99-RGB depth alignment time cost: 0.0354095 seconds       99--fps:28.1698
100-RGB depth alignment time cost: 0.0379055 seconds       100--fps:26.3137
101-RGB depth alignment time cost: 0.0376058 seconds       101--fps:26.5154
102-RGB depth alignment time cost: 0.0360134 seconds       102--fps:27.6909
103-RGB depth alignment time cost: 0.0358949 seconds       103--fps:27.7847
104-RGB depth alignment time cost: 0.0340729 seconds       104--fps:29.2646
105-RGB depth alignment time cost: 0.0341763 seconds       105--fps:29.1783
106-RGB depth alignment time cost: 0.034211 seconds       106--fps:29.1426
107-RGB depth alignment time cost: 0.0353568 seconds       107--fps:28.1833
108-RGB depth alignment time cost: 0.0360751 seconds       108--fps:27.6373
109-RGB depth alignment time cost: 0.0362327 seconds       109--fps:27.4937
110-RGB depth alignment time cost: 0.0371576 seconds       110--fps:26.8276
111-RGB depth alignment time cost: 0.0361254 seconds       111--fps:27.6144
112-RGB depth alignment time cost: 0.0359273 seconds       112--fps:27.7639
113-RGB depth alignment time cost: 0.0359461 seconds       113--fps:27.7454
114-RGB depth alignment time cost: 0.0368952 seconds       114--fps:27.0285
115-RGB depth alignment time cost: 0.035713 seconds       115--fps:27.9174
116-RGB depth alignment time cost: 0.0361523 seconds       116--fps:27.5786
117-RGB depth alignment time cost: 0.0363171 seconds       117--fps:27.4589
118-RGB depth alignment time cost: 0.035671 seconds       118--fps:27.9501
119-RGB depth alignment time cost: 0.0361547 seconds       119--fps:27.5748
120-RGB depth alignment time cost: 0.0402642 seconds       120--fps:24.7476
121-RGB depth alignment time cost: 0.0370244 seconds       121--fps:26.9411
122-RGB depth alignment time cost: 0.036121 seconds       122--fps:27.6159
123-RGB depth alignment time cost: 0.0357106 seconds       123--fps:27.9322
124-RGB depth alignment time cost: 0.0371894 seconds       124--fps:26.7989
125-RGB depth alignment time cost: 0.0335211 seconds       125--fps:29.7292
126-RGB depth alignment time cost: 0.0338834 seconds       126--fps:29.4178
127-RGB depth alignment time cost: 0.0341402 seconds       127--fps:29.1877
128-RGB depth alignment time cost: 0.0337455 seconds       128--fps:29.5377
129-RGB depth alignment time cost: 0.034029 seconds       129--fps:29.2997
130-RGB depth alignment time cost: 0.0342637 seconds       130--fps:29.1036
131-RGB depth alignment time cost: 0.0345705 seconds       131--fps:28.845
132-RGB depth alignment time cost: 0.0343628 seconds       132--fps:29.0217
133-RGB depth alignment time cost: 0.0349068 seconds       133--fps:28.5665
134-RGB depth alignment time cost: 0.0349418 seconds       134--fps:28.5356
135-RGB depth alignment time cost: 0.035893 seconds       135--fps:27.7731
136-RGB depth alignment time cost: 0.037325 seconds       136--fps:26.7023
137-RGB depth alignment time cost: 0.0366887 seconds       137--fps:27.1621
138-RGB depth alignment time cost: 0.0356441 seconds       138--fps:27.9712
139-RGB depth alignment time cost: 0.0359116 seconds       139--fps:27.777
140-RGB depth alignment time cost: 0.0362882 seconds       140--fps:27.4839
141-RGB depth alignment time cost: 0.0365751 seconds       141--fps:27.2405
142-RGB depth alignment time cost: 0.0361893 seconds       142--fps:27.549
143-RGB depth alignment time cost: 0.0360251 seconds       143--fps:27.6771
144-RGB depth alignment time cost: 0.0347014 seconds       144--fps:28.7373
145-RGB depth alignment time cost: 0.0345373 seconds       145--fps:28.8717
146-RGB depth alignment time cost: 0.0351559 seconds       146--fps:28.3656
147-RGB depth alignment time cost: 0.0349089 seconds       147--fps:28.5551
148-RGB depth alignment time cost: 0.0356571 seconds       148--fps:27.9509
149-RGB depth alignment time cost: 0.0368198 seconds       149--fps:27.0504
150-RGB depth alignment time cost: 0.0364547 seconds       150--fps:27.3321
151-RGB depth alignment time cost: 0.0362116 seconds       151--fps:27.5399
152-RGB depth alignment time cost: 0.0360712 seconds       152--fps:27.6518
153-RGB depth alignment time cost: 0.0353502 seconds       153--fps:28.2095
154-RGB depth alignment time cost: 0.0351051 seconds       154--fps:28.3881
155-RGB depth alignment time cost: 0.0359895 seconds       155--fps:27.7001
156-RGB depth alignment time cost: 0.0356472 seconds       156--fps:27.9767
157-RGB depth alignment time cost: 0.035621 seconds       157--fps:28.0034
158-RGB depth alignment time cost: 0.0353614 seconds       158--fps:28.1976
159-RGB depth alignment time cost: 0.0355789 seconds       159--fps:28.0285
160-RGB depth alignment time cost: 0.0350453 seconds       160--fps:28.4544
161-RGB depth alignment time cost: 0.0355389 seconds       161--fps:28.0568
162-RGB depth alignment time cost: 0.0374026 seconds       162--fps:26.6581
163-RGB depth alignment time cost: 0.035893 seconds       163--fps:27.7616
164-RGB depth alignment time cost: 0.0364089 seconds       164--fps:27.3928
165-RGB depth alignment time cost: 0.0353866 seconds       165--fps:28.1889
166-RGB depth alignment time cost: 0.0353572 seconds       166--fps:28.2111
167-RGB depth alignment time cost: 0.0357489 seconds       167--fps:27.9002
168-RGB depth alignment time cost: 0.0364735 seconds       168--fps:27.3276
169-RGB depth alignment time cost: 0.0360188 seconds       169--fps:27.6801
170-RGB depth alignment time cost: 0.0359551 seconds       170--fps:27.7385
171-RGB depth alignment time cost: 0.0354704 seconds       171--fps:28.1152
172-RGB depth alignment time cost: 0.0360648 seconds       172--fps:27.6518
173-RGB depth alignment time cost: 0.0353631 seconds       173--fps:28.1984
174-RGB depth alignment time cost: 0.0359651 seconds       174--fps:27.7108
175-RGB depth alignment time cost: 0.0363636 seconds       175--fps:27.3943
176-RGB depth alignment time cost: 0.0361137 seconds       176--fps:27.5961
177-RGB depth alignment time cost: 0.03548 seconds       177--fps:28.1152
178-RGB depth alignment time cost: 0.0355816 seconds       178--fps:28.034
179-RGB depth alignment time cost: 0.0355926 seconds       179--fps:28.023
180-RGB depth alignment time cost: 0.035871 seconds       180--fps:27.7731
181-RGB depth alignment time cost: 0.0357328 seconds       181--fps:27.9018
182-RGB depth alignment time cost: 0.0358823 seconds       182--fps:27.7924
183-RGB depth alignment time cost: 0.0357085 seconds       183--fps:27.9267
184-RGB depth alignment time cost: 0.0357664 seconds       184--fps:26.4187
185-RGB depth alignment time cost: 0.0357718 seconds       185--fps:27.8761
186-RGB depth alignment time cost: 0.037065 seconds       186--fps:26.8991
187-RGB depth alignment time cost: 0.0368756 seconds       187--fps:27.0051
188-RGB depth alignment time cost: 0.0353386 seconds       188--fps:28.2271
189-RGB depth alignment time cost: 0.034645 seconds       189--fps:28.7869
190-RGB depth alignment time cost: 0.0374528 seconds       190--fps:26.6297
191-RGB depth alignment time cost: 0.0392348 seconds       191--fps:25.4026
192-RGB depth alignment time cost: 0.0361018 seconds       192--fps:27.6136
193-RGB depth alignment time cost: 0.0363525 seconds       193--fps:27.4273
194-RGB depth alignment time cost: 0.0358939 seconds       194--fps:27.7909
195-RGB depth alignment time cost: 0.0360104 seconds       195--fps:27.6932
196-RGB depth alignment time cost: 0.0384635 seconds       196--fps:25.9269
197-RGB depth alignment time cost: 0.0361913 seconds       197--fps:27.5346
198-RGB depth alignment time cost: 0.0362965 seconds       198--fps:27.4816
199-RGB depth alignment time cost: 0.035934 seconds       199--fps:27.7608
200-RGB depth alignment time cost: 0.0361629 seconds       200--fps:27.5824
201-RGB depth alignment time cost: 0.0361536 seconds       201--fps:27.5778
202-RGB depth alignment time cost: 0.0357427 seconds       202--fps:27.9018
203-RGB depth alignment time cost: 0.0359624 seconds       203--fps:27.7362
204-RGB depth alignment time cost: 0.0360876 seconds       204--fps:27.6388
205-RGB depth alignment time cost: 0.0361865 seconds       205--fps:27.5626
206-RGB depth alignment time cost: 0.0362339 seconds       206--fps:27.5247
207-RGB depth alignment time cost: 0.0370391 seconds       207--fps:26.9041
208-RGB depth alignment time cost: 0.0364076 seconds       208--fps:27.3471
209-RGB depth alignment time cost: 0.0359292 seconds       209--fps:27.7577
210-RGB depth alignment time cost: 0.0360615 seconds       210--fps:27.6625
211-RGB depth alignment time cost: 0.035988 seconds       211--fps:27.7177
212-RGB depth alignment time cost: 0.0360075 seconds       212--fps:27.6962
213-RGB depth alignment time cost: 0.0357431 seconds       213--fps:27.8901
214-RGB depth alignment time cost: 0.0357377 seconds       214--fps:27.8979
215-RGB depth alignment time cost: 0.0361632 seconds       215--fps:27.5824
216-RGB depth alignment time cost: 0.0362977 seconds       216--fps:27.4748
217-RGB depth alignment time cost: 0.0366142 seconds       217--fps:27.2383
218-RGB depth alignment time cost: 0.0398418 seconds       218--fps:25.0269
219-RGB depth alignment time cost: 0.0402586 seconds       219--fps:24.7727
220-RGB depth alignment time cost: 0.042275 seconds       220--fps:23.5983
221-RGB depth alignment time cost: 0.0433863 seconds       221--fps:22.9906
222-RGB depth alignment time cost: 0.0476642 seconds       222--fps:20.9266
223-RGB depth alignment time cost: 0.0476839 seconds       223--fps:20.9205
224-RGB depth alignment time cost: 0.0504138 seconds       224--fps:19.7902
225-RGB depth alignment time cost: 0.0496984 seconds       225--fps:20.0747
226-RGB depth alignment time cost: 0.0530068 seconds       226--fps:18.8179
227-RGB depth alignment time cost: 0.0534609 seconds       227--fps:18.6522
228-RGB depth alignment time cost: 0.0551169 seconds       228--fps:18.0819
229-RGB depth alignment time cost: 0.057613 seconds       229--fps:17.3139
230-RGB depth alignment time cost: 0.0573502 seconds       230--fps:17.3916
231-RGB depth alignment time cost: 0.0589014 seconds       231--fps:16.9222
232-RGB depth alignment time cost: 0.0599539 seconds       232--fps:16.6367
233-RGB depth alignment time cost: 0.0612367 seconds       233--fps:16.292
234-RGB depth alignment time cost: 0.0634953 seconds       234--fps:15.7099
235-RGB depth alignment time cost: 0.0631687 seconds       235--fps:15.7913
236-RGB depth alignment time cost: 0.0640505 seconds       236--fps:15.5771
237-RGB depth alignment time cost: 0.0691937 seconds       237--fps:14.4209
238-RGB depth alignment time cost: 0.0706561 seconds       238--fps:14.1161
239-RGB depth alignment time cost: 0.0694268 seconds       239--fps:14.3664
240-RGB depth alignment time cost: 0.0687614 seconds       240--fps:14.5062
241-RGB depth alignment time cost: 0.0687726 seconds       241--fps:14.5045
242-RGB depth alignment time cost: 0.0678698 seconds       242--fps:14.6964
243-RGB depth alignment time cost: 0.068217 seconds       243--fps:14.6239
244-RGB depth alignment time cost: 0.0701592 seconds       244--fps:14.2201
245-RGB depth alignment time cost: 0.0714898 seconds       245--fps:13.954
246-RGB depth alignment time cost: 0.0756127 seconds       246--fps:13.1808
247-RGB depth alignment time cost: 0.0744754 seconds       247--fps:13.3924
248-RGB depth alignment time cost: 0.0743576 seconds       248--fps:13.4162
249-RGB depth alignment time cost: 0.0761368 seconds       249--fps:13.101
250-RGB depth alignment time cost: 0.0754748 seconds       250--fps:13.2045
251-RGB depth alignment time cost: 0.0742685 seconds       251--fps:13.4277
252-RGB depth alignment time cost: 0.0736638 seconds       252--fps:13.5421
253-RGB depth alignment time cost: 0.0762429 seconds       253--fps:13.0822
254-RGB depth alignment time cost: 0.0752997 seconds       254--fps:13.2382
255-RGB depth alignment time cost: 0.0741932 seconds       255--fps:13.4443
256-RGB depth alignment time cost: 0.0742841 seconds       256--fps:13.4291
257-RGB depth alignment time cost: 0.0760248 seconds       257--fps:13.1211
258-RGB depth alignment time cost: 0.0897253 seconds       258--fps:11.1144
259-RGB depth alignment time cost: 0.073125 seconds       259--fps:13.6394
260-RGB depth alignment time cost: 0.0736016 seconds       260--fps:13.552
261-RGB depth alignment time cost: 0.0744919 seconds       261--fps:13.3776
262-RGB depth alignment time cost: 0.0728621 seconds       262--fps:13.6906
263-RGB depth alignment time cost: 0.0725256 seconds       263--fps:13.7546
264-RGB depth alignment time cost: 0.0775168 seconds       264--fps:12.8682
265-RGB depth alignment time cost: 0.0793255 seconds       265--fps:12.5649
266-RGB depth alignment time cost: 0.076653 seconds       266--fps:13.012
267-RGB depth alignment time cost: 0.0795302 seconds       267--fps:12.5411
268-RGB depth alignment time cost: 0.0778435 seconds       268--fps:12.8162
269-RGB depth alignment time cost: 0.0737549 seconds       269--fps:13.523
270-RGB depth alignment time cost: 0.0748183 seconds       270--fps:13.3308
271-RGB depth alignment time cost: 0.0740825 seconds       271--fps:13.4568
272-RGB depth alignment time cost: 0.0748294 seconds       272--fps:13.3248
273-RGB depth alignment time cost: 0.0773406 seconds       273--fps:12.8984
274-RGB depth alignment time cost: 0.0818149 seconds       274--fps:12.1941
275-RGB depth alignment time cost: 0.0791071 seconds       275--fps:12.6127
276-RGB depth alignment time cost: 0.08064 seconds       276--fps:12.3706
277-RGB depth alignment time cost: 0.0738759 seconds       277--fps:13.4902
278-RGB depth alignment time cost: 0.0717763 seconds       278--fps:13.8953
279-RGB depth alignment time cost: 0.0730709 seconds       279--fps:13.6519
280-RGB depth alignment time cost: 0.072188 seconds       280--fps:13.819
281-RGB depth alignment time cost: 0.0746569 seconds       281--fps:13.3611
282-RGB depth alignment time cost: 0.0793603 seconds       282--fps:12.5606
283-RGB depth alignment time cost: 0.0772265 seconds       283--fps:12.9169
284-RGB depth alignment time cost: 0.0793632 seconds       284--fps:12.5694
285-RGB depth alignment time cost: 0.0768992 seconds       285--fps:12.9455
286-RGB depth alignment time cost: 0.0766701 seconds       286--fps:13.0115
287-RGB depth alignment time cost: 0.0751535 seconds       287--fps:13.2709
288-RGB depth alignment time cost: 0.0745802 seconds       288--fps:13.3656
289-RGB depth alignment time cost: 0.0743019 seconds       289--fps:13.4277
290-RGB depth alignment time cost: 0.09542 seconds       290--fps:10.4529
291-RGB depth alignment time cost: 0.0776479 seconds       291--fps:12.8327
292-RGB depth alignment time cost: 0.073763 seconds       292--fps:13.5216
293-RGB depth alignment time cost: 0.0710003 seconds       293--fps:14.0463
294-RGB depth alignment time cost: 0.0762975 seconds       294--fps:13.0727
295-RGB depth alignment time cost: 0.0769347 seconds       295--fps:12.9685
296-RGB depth alignment time cost: 0.0745512 seconds       296--fps:13.3783
297-RGB depth alignment time cost: 0.0786076 seconds       297--fps:12.6904
298-RGB depth alignment time cost: 0.0734689 seconds       298--fps:13.5788
299-RGB depth alignment time cost: 0.0718114 seconds       299--fps:13.8906
300-RGB depth alignment time cost: 0.0722875 seconds       300--fps:13.7988
301-RGB depth alignment time cost: 0.0743864 seconds       301--fps:13.3774
302-RGB depth alignment time cost: 0.0746394 seconds       302--fps:13.3515
303-RGB depth alignment time cost: 0.0737597 seconds       303--fps:13.5241
304-RGB depth alignment time cost: 0.0699076 seconds       304--fps:14.2694

The time cost of the code below grow from 0.03 seconds to 0.07 seconds

rs2::frameset aligned_frames0 = align_to_color.process(fs0);
rs2::frameset aligned_frames1 = align_to_color.process(fs1);

Besides that, I have also noticed that my CPU usage is quite heavy after running for a while.

What should I do? I do not understand why 'RGB-depth alignment' operation takes more and more time.

I am looking forward to your reply. Thanks a lot！

[MartyG-RealSense]

I have not seen your particular approach in your script before. It looks as though it could be very costly in terms of processing burden.

A RealSense team member provides a C++ multicam script that uses pipelines at #2219 (comment) that you could compare to your own approach.

[MartyG-RealSense]

Hi @Billccx Do you require further assistance with this case, please? Thanks!

[MartyG-RealSense]

Case closed due to no further comments received.