# Three cameras on Jetson Nano

**URL:** <https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052>\
**Category:** Jetson Nano\
**Tags:** camera\
**Created:** [January 16, 2021, 6:12pm UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052 "2021-01-16T18:12:12Z")\
**Posts on this page:** 20\
**Page:** 1

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 16, 2021, 6:12pm UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/1 "2021-01-16T18:12:12Z")

</div>

I’m trying to use three web cams on a Jetson Nano for inference. While it seems to be possible to use MJPG and/or H.264 @ 640 x 280, I’m running into

```
GStreamer warning: Embedded video playback halted; module v4l2src2 reported: Failed to allocate required memory.

```

when I try to open the cameras in YUV (x-raw), even in the lowest resolution (320x240). I already tried to follow this gist in order to allow for four cameras, to no avial.

> **[Birds Eye View Building and Installation Guide](https://developer.ridgerun.com/wiki/index.php?title=Birds_Eye_View%2FGetting_the_Code%2FBuilding_and_Installation_Guide#Patch_to_support_4_USB_cameras)**
>
> RidgeRun Developer's detailed guide for the Birds Eye View project.

I know it is not related to NVIDEA, but maybe somebody has a hint how to make 3 cams running using uncompressed raw video input.

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 16, 2021, 6:31pm UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/2 "2021-01-16T18:31:41Z")

</div>

It turns out, that it is not even possible to use three cams with MJPEG encoding :(

Error is

gst\_v4l2\_buffer\_pool\_streamon:v4l2src2:pool:src error with STREAMON 28 (No space left on device)

On whatever device…

---

<div class="post-metadata">

**Author:** ![DaneLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/danelll/32/14043_2.png) [@DaneLLL](https://forums.developer.nvidia.com/u/DaneLLL)\
**Post date:** [January 18, 2021, 3:14am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/5 "2021-01-18T03:14:58Z")

</div>

Hi,  
Suggest you use USB3 cameras to get 5Gbps. Please take a look at

> [@connected more than two usb cameras problem on deepstream-app (Jetson Nano Dev Kit)](https://forums.developer.nvidia.com/t/connected-more-than-two-usb-cameras-problem-on-deepstream-app-jetson-nano-dev-kit/108585/12):
>
> Hi, With further investigation, we found bandwidth limitation is hit in using USB2(High-Speed) cameras. High-Speed limit is 480Mbps. In the [test](https://forums.developer.nvidia.com/t/deepstream4-jetson-nano-multiple-webcams-issue/79030/12), two E-Con See3CAM\_CU135 are USB3(Super-Speed) cameras. Please use USB3 cameras to get 5Gbps bandwidth.

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 18, 2021, 8:44am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/6 "2021-01-18T08:44:10Z")

</div>

Thanks for the reply. I’m not sure I understand: You say, it could be a “bandwidth limitation problem”, whereas the error message clearly talks about memory issues?

I’m having here this simple Python3 OpenCV script with runs into this problem too:

```auto
import cv2

streams = []
indexes = [0, 1, 2]

for index in indexes:
    stream = cv2.VideoCapture(index)
    stream.set(cv2.CAP_PROP_FOURCC, cv2.VideoWriter_fourcc(*"MJPG"))
    stream.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
    stream.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
    streams.append(stream)

while True:
    i = 0
    for index in indexes:
        _, frame = streams[i].read()
        frame = cv2.resize(frame, (320, 240))
        cv2.imshow("Display "+str(index), frame)
       
        i = i + 1
    
    if cv2.waitKey(1) & 0xFF == ord('q'):
          break

```

On the Jetson already the attempt to re-configure the capture to MJPG fails in the GStreamer log (setProperty, unhandled property):

```auto
neil@jetson:~/jetson-inference/build/aarch64/bin$ python3 test.py
[WARN:0] global /home/nvidia/host/build_opencv/nv_opencv/modules/videoio/src/cap_gstreamer.cpp (933) open OpenCV | GStreamer warning: Cannot query video position: status=0, value=-1, duration=-1
[WARN:0] global /home/nvidia/host/build_opencv/nv_opencv/modules/videoio/src/cap_gstreamer.cpp (1184) setProperty OpenCV | GStreamer warning: GStreamer: unhandled property
[WARN:0] global /home/nvidia/host/build_opencv/nv_opencv/modules/videoio/src/cap_gstreamer.cpp (933) open OpenCV | GStreamer warning: Cannot query video position: status=0, value=-1, duration=-1
[WARN:0] global /home/nvidia/host/build_opencv/nv_opencv/modules/videoio/src/cap_gstreamer.cpp (1184) setProperty OpenCV | GStreamer warning: GStreamer: unhandled property
[WARN:0] global /home/nvidia/host/build_opencv/nv_opencv/modules/videoio/src/cap_gstreamer.cpp (1757) handleMessage OpenCV | GStreamer warning: Embedded video playback halted; module v4l2src2 reported: Failed to allocate required memory.
[WARN:0] global /home/nvidia/host/build_opencv/nv_opencv/modules/videoio/src/cap_gstreamer.cpp (886) open OpenCV | GStreamer warning: unable to start pipeline
[WARN:0] global /home/nvidia/host/build_opencv/nv_opencv/modules/videoio/src/cap_gstreamer.cpp (480) isPipelinePlaying OpenCV | GStreamer warning: GStreamer: pipeline have not been created
VIDIOC_STREAMON: No space left on device
Traceback (most recent call last):
  File "test.py", line 22, in <module>
    frame = cv2.resize(frame, (320, 240))
cv2.error: OpenCV(4.1.1) /home/nvidia/host/build_opencv/nv_opencv/modules/imgproc/src/resize.cpp:3720: error: (-215:Assertion failed) !ssize.empty() in function 'resize'

```

The same sequence works perfectly on a Raspberry PI 4

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 18, 2021, 8:55am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/7 "2021-01-18T08:55:58Z")

</div>

Also tried now three of this kind, with varying /dev/videoX:

`gst-launch-1.0 v4l2src device=/dev/video0 ! video/x-raw,format=YUY2,width=320,height=240,framerate=30/1 ! nvvidconv ! 'video/x-raw(memory:NVMM),format=NV12' ! nvvidconv ! nveglglessink`

The third opening leads to “Failed to allocate memory”:

```
neil@jetson:~$ gst-launch-1.0 v4l2src device=/dev/video2 ! video/x-raw,format=YUY2,width=640,height=480,framerate=30/1 ! nvvidconv ! 'video/x-raw(memory:NVMM),format=NV12' ! nvvidconv ! nveglglessink
Setting pipeline to PAUSED ...

Using winsys: x11 
Pipeline is live and does not need PREROLL ...
Got context from element 'eglglessink0': gst.egl.EGLDisplay=context, display=(GstEGLDisplay)NULL;
Setting pipeline to PLAYING ...
New clock: GstSystemClock
ERROR: from element /GstPipeline:pipeline0/GstV4l2Src:v4l2src0: Failed to allocate required memory.
Additional debug info:
gstv4l2src.c(658): gst_v4l2src_decide_allocation (): /GstPipeline:pipeline0/GstV4l2Src:v4l2src0:
Buffer pool activation failed
Execution ended after 0:00:01.014041254
Setting pipeline to PAUSED ...
Setting pipeline to READY ...
Setting pipeline to NULL ...
Freeing pipeline ...

```

---

<div class="post-metadata">

**Author:** ![DaneLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/danelll/32/14043_2.png) [@DaneLLL](https://forums.developer.nvidia.com/u/DaneLLL)\
**Post date:** [January 28, 2021, 4:35am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/10 "2021-01-28T04:35:59Z")

</div>

Hi,  
Please check _dmesg_ to see if the cameras are enumerated as SuperSpeed. If it is high-speed, is it USB2 bandwidth 480Mbps.

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 28, 2021, 7:52am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/11 "2021-01-28T07:52:38Z")

</div>

Well, I know, that these cameras are plain USB2 cameras. But I have two sets of three from the same brand ELP:

With one set I can achieve 3 cam capture 640 x 480 30 fps, but need to use MJPEG compression. The inference rate is about 20 fps per camera, which is good, but latency seems to be (from the preview) about 1 s for each camera. The same cameras are able to be operated in 320 x 240 30 fps YUY2, same inference result.

But the other set cannot even be operated in 640 x 480 MJPEG, obviously because the framerate is 60 fps.

My questions:

a) Is an inference rate for the resnet FP16 of 20 fps for each cam the maximum I can achieve with 3 USB cams? Would that be better with the USB3 cams you suggest?

b) I don’t see a big difference in inference rate and quality, if I operate the cams in 320x240. Is it suggested to capture that low in order to relief the USB bus or should I better try to capture bigger images?

---

<div class="post-metadata">

**Author:** ![DaneLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/danelll/32/14043_2.png) [@DaneLLL](https://forums.developer.nvidia.com/u/DaneLLL)\
**Post date:** [January 29, 2021, 7:52am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/12 "2021-01-29T07:52:13Z")

</div>

Hi,  
Performance of deep learning inference depends on the models. We have a sample config file for Jetson Nano:

```auto
/opt/nvidia/deepstream/deepstream-5.0/samples/configs/deepstream-app/source8_1080p_dec_infer-resnet_tracker_tiled_display_fp16_nano.txt

```

The model is resnet10.

For sources in MJPEG, you may refer to this patch:

> [@How to change source pixel format from YUYV to MJPG](https://forums.developer.nvidia.com/t/how-to-change-source-pixel-format-from-yuyv-to-mjpg/79409/7):
>
> Hi DaneLLL, Finally, it works. I really appreciate your help. bin-\>cap\_filter = gst\_element\_factory\_make (NVDS\_ELEM\_CAPS\_FILTER, "src\_cap\_filter"); if (!bin-\>cap\_filter) { NVGSTDS\_ERR\_MSG\_V ("Could not create 'src\_cap\_filter'"); goto done; } caps = gst\_caps\_new\_simple ("image/jpeg", "width", G\_TYPE\_INT, config-\>source\_width, "height", G\_TYPE\_INT, config-\>source\_height, "framerate", GST\_TYPE\_FRACTION, config-\>source\_fps\_n, config-\>source\_fps\_d, NULL); …

It uses _jpegdec_ in the patch. Another working solution is to use _nvv4l2decoder mjpeg=1_.

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 29, 2021, 8:01am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/13 "2021-01-29T08:01:14Z")

</div>

Thanks @DaneLLL. TBH, I can’t see nvjpecgec in this reference.

This is my working pipeline:

```
gst-launch-1.0 v4l2src device=/dev/video0 
! "image/jpeg,width=1280,height=720,framerate=30/1" 
! jpegdec 
! videoconvert 
! nvvideoconvert 
! "video/x-raw(memory:NVMM),fromat=NV12" 
! m.sink_0 nvstreammux name=m batch-size=1 width=640 height=480 
! nvinfer config-file-path=/opt/nvidia/deepstream/deepstream-5.0/samples/configs/deepstream-app/config_infer_primary.txt 
! fakesink

```

Could you please give me a hint, how this would look like with “nvjegdec” or “nv4ldecoder mjepg=1”?

---

<div class="post-metadata">

**Author:** ![DaneLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/danelll/32/14043_2.png) [@DaneLLL](https://forums.developer.nvidia.com/u/DaneLLL)\
**Post date:** [January 29, 2021, 8:09am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/14 "2021-01-29T08:09:34Z")

</div>

Hi,  
Sorry I made a typo. It should be _jpegdec_.

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 29, 2021, 8:34am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/15 "2021-01-29T08:34:20Z")

</div>

> [@DaneLLL](#):
>
> Another working solution is to use _nvv4l2decoder mjpeg=1_ .

OK thanks for clarifying. Any sample for the above statement available?

---

<div class="post-metadata">

**Author:** ![DaneLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/danelll/32/14043_2.png) [@DaneLLL](https://forums.developer.nvidia.com/u/DaneLLL)\
**Post date:** [January 29, 2021, 9:51am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/16 "2021-01-29T09:51:03Z")

</div>

Hi,  
The deepstream-image-decode-test sample demonstrates

```auto
multifilesrc ! jpegparse ! nvv4l2decoder mjpeg=1 ! ...

```

You may refer to it and try

```auto
v4l2src ! jpegparse ! nvv4l2decoder mjpeg=1 ! ..

```

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 29, 2021, 9:52am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/17 "2021-01-29T09:52:54Z")

</div>

Cool. Thanks. Will try and report

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 29, 2021, 11:27am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/18 "2021-01-29T11:27:47Z")

</div>

Hmm. No, doesn’t work…

This pipe works:

`gst-launch-1.0 v4l2src device=/dev/video0 ! "image/jpeg,width=640,height=480" ! jpegdec ! videoconvert ! nvvideoconvert ! "video/x-raw(memory:NVMM),fromat=NV12" ! m.sink_0 nvstreammux name=m batch-size=1 width=640 height=480 ! nvinfer config-file-path=/opt/nvidia/deepstream/deepstream-5.0/samples/configs/deepstream-app/config_infer_primary.txt ! nvdsosd ! nvegltransform bufapi-version=true ! nveglglessink qos=false async=false sync=false`

while this does not:

`gst-launch-1.0 v4l2src device=/dev/video0 ! "image/jpeg,width=640,height=480" ! jpegparse ! nvv4l2decoder mjpeg=1 ! nvvideoconvert ! "video/x-raw(memory:NVMM),fromat=NV12" ! m.sink_0 nvstreammux name=m batch-size=1 width=640 height=480 ! nvinfer config-file-path=/opt/nvidia/deepstream/deepstream-5.0/samples/configs/deepstream-app/config_infer_primary.txt ! nvdsosd ! nvegltransform bufapi-version=true ! nveglglessink qos=false async=false sync=false`

Error is:

` bash: ! nvv4l2decoder mjpeg=1: event not found`

EDIT: Works after typo fixed

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 29, 2021, 11:32am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/19 "2021-01-29T11:32:51Z")

</div>

Opps, sorry typo: nvvvideoconvert instead of videoconvert…

Works, but has color conversion issues. This looks exactly as if the wrong YUV decoding model is applied (see the color block). Any suggestion?

 ![IMG_8487](https://global.discourse-cdn.com/nvidia/original/3X/c/4/c47a887f69a28b7dbb31936659b6ed20a26b9b3a.jpeg)

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 29, 2021, 11:39am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/20 "2021-01-29T11:39:07Z")

</div>

OMG, there is still another typo: fromat instead of format. The first pipe didn’t care, it seems. Fixing it on the second makes the second non functional… Removed the NV12 format specifier, but the colour conversion issue remains…

---

<div class="post-metadata">

**Author:** ![DaneLLL](https://sea2.discourse-cdn.com/nvidia/user_avatar/forums.developer.nvidia.com/danelll/32/14043_2.png) [@DaneLLL](https://forums.developer.nvidia.com/u/DaneLLL)\
**Post date:** [January 29, 2021, 11:46am UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/21 "2021-01-29T11:46:43Z")

</div>

Hi,  
Please apply the prebuilt library and try again.  
_[Jetson/L4T/r32.4.x patches - eLinux.org](https://elinux.org/Jetson/L4T/r32.4.x_patches)_  
_[GSTREAMER]Prebuilt lib for decoding YUV422 MJPEG through nvv4l2decoder_

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 29, 2021, 3:22pm UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/22 "2021-01-29T15:22:36Z")

</div>

Perfect. Works

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 29, 2021, 4:05pm UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/23 "2021-01-29T16:05:08Z")

</div>

OK. I’m a bit surprised now. The inference rate has been slowed down from 20 fps per camera to 16-17 fps per camera. I don’t see a remarkable difference between the `jpegparse ! nvv4l2decoder mjpeg=1` and the `jpegdec ! videoconvert ` approach w.r.t. fps and latency. But I’m missing 4 to 5 fps now :(

I didn’t make a backup. Could one please send me the original `./usr/lib/aarch64-linux-tegra/libnvtvmr.so`? I think it was of August 2020.

---

<div class="post-metadata">

**Author:** ![foreverneilyoung](https://developer.download.nvidia.com/images/forums/profile-default-devtalk-84.png) [@foreverneilyoung](https://forums.developer.nvidia.com/u/foreverneilyoung)\
**Post date:** [January 30, 2021, 9:49pm UTC](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052/24 "2021-01-30T21:49:05Z")

</div>

As already reported, the patch for the colour space conversion dropped the achievable frame rate on all three cams by 5 fps per camera. Since I could not revert the file change I flashed a new image and started from scratch.

In the end I lost everything (not the sources, but a running system).

1. Since I flashed my first SDK (End of December) the JetPack subversion changed from 4.4. to 4.5. However, the "How to " Guide does not reflect this and is still referring to JP 4.4.

2. My 3 cam python script, which worked fine with JP 4.4, is still working, but just with one cam. If I add another or try to work with three cams simultaneously, the whole script crashes with “segmentation fault”

3. I gave up with JP 4.5 and downloaded a JP 4.4 image. I was trying to follow the deep stream “How to” and it failed with the first attempt to install the library dependencies (top 1 in the list). So I tried to update/upgrade the system from console, which ended up in an error telling me, that the “nvidia-l4t-bootloader package post-installer” failed.

4. Right now I have re-flashed the card with JP 4.4 again.

I’m inclined to say “Thanks, Obama” and my confidence in DeepStream is shaken for now.

[Next page](https://forums.developer.nvidia.com/t/three-cameras-on-jetson-nano/166052.md?page=2)