DLI csi_camera.ipynb (hello camera) fails with CSI camera

Robotics & Edge Computing Jetson Systems Jetson Orin Nano
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1

I have an RPi Camera V2 attached to Jetson Orin Nano (dev kit) via CSI connector (“cam0”)

The RPi camera works properly outside of docker.

The DLI-provided docker image is run using the following:
sudo docker run -it --rm --runtime nvidia --volume /tmp/argus_socket:/tmp/argus_socket --volume ~/nvdli-data:/nvdli-nano/data --device /dev/video0:/dev/video0 --device /dev/video1:/dev/video1 --network host nvcr.io/nvidia/dli/dli-nano-ai:v2.0.3-r36.3.0

When DLI’s csi_camera.ipynb notebook is run in Jupyter NB, cell #1 (!ls -ltrh /dev/video*) results in:
crw-rw---- 1 root video 81, 0 Jun 30 01:05 /dev/video0

However, executing cell #2 (camera = CSICamera(width=224,…) eventually causes the kernel to restart after displaying the following:

GST_ARGUS: Creating output stream
CONSUMER: Waiting until producer is connected…
GST_ARGUS: Available Sensor modes :
GST_ARGUS: 3280 x 2464 FR = 21.000000 fps Duration = 47619048 ; Analog Gain range min 1.000000, max 10.625000; Exposure Range min 13000, max 683709000;

GST_ARGUS: 3280 x 1848 FR = 28.000001 fps Duration = 35714284 ; Analog Gain range min 1.000000, max 10.625000; Exposure Range min 13000, max 683709000;

GST_ARGUS: 1920 x 1080 FR = 29.999999 fps Duration = 33333334 ; Analog Gain range min 1.000000, max 10.625000; Exposure Range min 13000, max 683709000;

GST_ARGUS: 1640 x 1232 FR = 29.999999 fps Duration = 33333334 ; Analog Gain range min 1.000000, max 10.625000; Exposure Range min 13000, max 683709000;

GST_ARGUS: 1280 x 720 FR = 59.999999 fps Duration = 16666667 ; Analog Gain range min 1.000000, max 10.625000; Exposure Range min 13000, max 683709000;

GST_ARGUS: Running with following settings:
Camera index = 0
Camera mode = 4
Output Stream W = 1280 H = 720
seconds to Run = 0
Frame Rate = 59.999999
GST_ARGUS: Setup Complete, Starting captures for 0 seconds
GST_ARGUS: Starting repeat capture requests.
CONSUMER: Producer has connected; continuing.

The companion notebook for USB cameras - usb_camera.ipynb - works properly when a USB camera is attached to the same system.

H/W & S/W config…
Jetson Orin Nano (dev kit): L4T version is 36.4.4
Jetson: # R36 (release), REVISION: 4.4, GCID: 41062509, BOARD: generic, EABI: aarch64

DLI docker image is r36.3.0
Docker:
sudo docker run -it --rm --runtime nvidia --volume /tmp/argus_socket:/tmp/argus_socket --volume ~/nvdli-data:/nvdli-nano/data --device /dev/video0:/dev/video0 --device /dev/video1:/dev/video1 --network host nvcr.io/nvidia/dli/dli-nano-ai:v2.0.3-r36.3.0

3

Hi,

The tutorial is for Jetson Nano instead of Orin Nano.
For the Orin series, we recommended checking our Jetson AI Lab:

https://www.jetson-ai-lab.com/tutorial_llava.html

Thanks.

1 Like
4

Ok. Thank you. I’ll take a look at the AI Lab.

(FYI, in the course into, the Orin Nano Dev Kit is included under “Hardware Requirements.”
Course Detail | NVIDIA)

5

Hi,

Thanks for this feedback.
Please find the Jetson AI Lab for the Orin series.

7

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