IMX477 driver instalation problem

Autonomous Machines Jetson & Embedded Systems Jetson Nano
1

Hello, I have problem with
HW:

  1. SeedStudio reComputer J1020 - details
  2. Goodram ssd drive - SSDPR-PX500-256-80-G2
  3. Raspberry PI HQ camera IMX477 - details
  4. Lens - details

SW:

user@nvidia:~$ cat /etc/nv_tegra_release

R32 (release), REVISION: 7.3, GCID: 31982016, BOARD: t210ref, EABI: aarch64, DATE: Tue Nov 22 17:30:08 UTC 2022

user@nvidia:~$ sudo apt-cache show nvidia-jetpack
Package: nvidia-jetpack
Version: 4.6.3-b17
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-l4t-jetson-multimedia-api (>> 32.7-0), nvidia-l4t-jetson-multimedia-api (<< 32.8-0), nvidia-cuda (= 4.6.3-b17), nvidia-tensorrt (= 4.6.3-b17), nvidia-nsight-sys (= 4.6.3-b17), nvidia-cudnn8 (= 4.6.3-b17), nvidia-opencv (= 4.6.3-b17), nvidia-container (= 4.6.3-b17), nvidia-vpi (= 4.6.3-b17)
Homepage: http://developer.nvidia.com/jetson
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_4.6.3-b17_arm64.deb
Size: 29368
SHA256: 694254a8667ebbf13852548bdd13a5b8ae61481ac059845b706398eefdcb9e01
SHA1: 67140fc8463ec61fd69352b225244b639c799edd
MD5sum: afa1382b6caded6b736d494fc481bab4
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8

Package: nvidia-jetpack
Version: 4.6.2-b5
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-cuda (= 4.6.2-b5), nvidia-opencv (= 4.6.2-b5), nvidia-cudnn8 (= 4.6.2-b5), nvidia-tensorrt (= 4.6.2-b5), nvidia-visionworks (= 4.6.2-b5), nvidia-container (= 4.6.2-b5), nvidia-vpi (= 4.6.2-b5), nvidia-l4t-jetson-multimedia-api (>> 32.7-0), nvidia-l4t-jetson-multimedia-api (<< 32.8-0)
Homepage: http://developer.nvidia.com/jetson
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_4.6.2-b5_arm64.deb
Size: 29378
SHA256: 925f4abff97e6024d86cff3b9e132e7c7554d05fb83590487381b7e925d5b2bb
SHA1: e3ef727e87df5c331aece34508c110d57d744fe9
MD5sum: 7cb2e387af41bc8143ac7b6525af7794
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8

Package: nvidia-jetpack
Version: 4.6.1-b110
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-cuda (= 4.6.1-b110), nvidia-opencv (= 4.6.1-b110), nvidia-cudnn8 (= 4.6.1-b110), nvidia-tensorrt (= 4.6.1-b110), nvidia-visionworks (= 4.6.1-b110), nvidia-container (= 4.6.1-b110), nvidia-vpi (= 4.6.1-b110), nvidia-l4t-jetson-multimedia-api (>> 32.7-0), nvidia-l4t-jetson-multimedia-api (<< 32.8-0)
Homepage: http://developer.nvidia.com/jetson
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_4.6.1-b110_arm64.deb
Size: 29366
SHA256: acfd9e75af780eab165361d61de4b4fe4974890864fe191060b402ac4c2f54d5
SHA1: a016568ac53705acc145a9f7e60505707bea259f
MD5sum: 79be976b184a8c885bd9169ea5b7fb7b
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8

user@nvidia:~$ dmesg | grep -E “imx477|imx219|arducam”
[ 0.211575] DTS File Name: /var/jenkins_home/workspace/n_nano_kernel_l4t-32.7.2-arducam/kernel/kernel-4.9/arch/arm64/boot/dts/…/…/…/…/…/…/hardware/nvidia/platform/t210/batuu/kernel-dts/tegra210-p3448-0003-p3542-0000.dts
[ 0.408290] DTS File Name: /var/jenkins_home/workspace/n_nano_kernel_l4t-32.7.2-arducam/kernel/kernel-4.9/arch/arm64/boot/dts/…/…/…/…/…/…/hardware/nvidia/platform/t210/batuu/kernel-dts/tegra210-p3448-0003-p3542-0000.dts
[ 1.279426] imx477 6-001a: tegracam sensor driver:imx477_v2.0.6
[ 1.579797] imx477 6-001a: imx477_board_setup: error during i2c read probe (-121)
[ 1.587394] imx477 6-001a: board setup failed
[ 1.591866] imx477: probe of 6-001a failed with error -121

But still can’t see any “video?” in /dev/

user@nvidia:~$ ls /dev/vid*
ls: cannot access ‘/dev/vid*’: No such file or directory

Also there is a problem while setting up driver after instalation:

user@nvidia:~$ sudo ./install_full.sh -m imx477
–2023-03-14 17:49:07-- https://github.com/ArduCAM/MIPI_Camera/releases/download/v0.0.3/imx477_links.txt
Resolving github.com (github.com)… 140.82.121.3
Connecting to github.com (github.com)|140.82.121.3|:443… connected.
HTTP request sent, awaiting response… 302 Found
Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/186627215/10d26c97-da90-4f78-ab30-0f7d9a5aecf7?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230314%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230314T174908Z&X-Amz-Expires=300&X-Amz-Signature=b43433356a9ef881b11ae8c097094e0467501719f1fb941022a395c157f958e6&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=186627215&response-content-disposition=attachment%3B%20filename%3Dimx477_links.txt&response-content-type=application%2Foctet-stream [following]
–2023-03-14 17:49:08-- https://objects.githubusercontent.com/github-production-release-asset-2e65be/186627215/10d26c97-da90-4f78-ab30-0f7d9a5aecf7?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230314%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230314T174908Z&X-Amz-Expires=300&X-Amz-Signature=b43433356a9ef881b11ae8c097094e0467501719f1fb941022a395c157f958e6&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=186627215&response-content-disposition=attachment%3B%20filename%3Dimx477_links.txt&response-content-type=application%2Foctet-stream
Resolving objects.githubusercontent.com (objects.githubusercontent.com)… 185.199.109.133, 185.199.110.133, 185.199.108.133, …
Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.109.133|:443… connected.
HTTP request sent, awaiting response… 200 OK
Length: 8677 (8.5K) [application/octet-stream]
Saving to: ‘imx477_links.txt’

imx477_links.txt 100%[=====================================================================================================================>] 8.47K --.-KB/s in 0.008s

2023-03-14 17:49:08 (1005 KB/s) - ‘imx477_links.txt’ saved [8677/8677]

–2023-03-14 17:49:08-- https://github.com/ArduCAM/MIPI_Camera/releases/download/v0.0.1/arducam-nvidia-l4t-kernel-t210-4.9.299-tegra-32.7.3-20230111085049_arm64_imx477.deb
Resolving github.com (github.com)… 140.82.121.3
Connecting to github.com (github.com)|140.82.121.3|:443… connected.
HTTP request sent, awaiting response… 302 Found
Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/186627215/491a288f-38f5-47bd-b944-cb2486cad6bc?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230314%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230314T174908Z&X-Amz-Expires=300&X-Amz-Signature=f11f8c7974ac5d427e10d0c9f68a6fcda1d3685cf3061cbd74cc848f59b1fc97&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=186627215&response-content-disposition=attachment%3B%20filename%3Darducam-nvidia-l4t-kernel-t210-4.9.299-tegra-32.7.3-20230111085049_arm64_imx477.deb&response-content-type=application%2Foctet-stream [following]
–2023-03-14 17:49:08-- https://objects.githubusercontent.com/github-production-release-asset-2e65be/186627215/491a288f-38f5-47bd-b944-cb2486cad6bc?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20230314%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230314T174908Z&X-Amz-Expires=300&X-Amz-Signature=f11f8c7974ac5d427e10d0c9f68a6fcda1d3685cf3061cbd74cc848f59b1fc97&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=186627215&response-content-disposition=attachment%3B%20filename%3Darducam-nvidia-l4t-kernel-t210-4.9.299-tegra-32.7.3-20230111085049_arm64_imx477.deb&response-content-type=application%2Foctet-stream
Resolving objects.githubusercontent.com (objects.githubusercontent.com)… 185.199.111.133, 185.199.108.133, 185.199.110.133, …
Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.111.133|:443… connected.
HTTP request sent, awaiting response… 200 OK
Length: 8222530 (7.8M) [application/octet-stream]
Saving to: ‘arducam-nvidia-l4t-kernel-t210-4.9.299-tegra-32.7.3-20230111085049_arm64_imx477.deb’

arducam-nvidia-l4t-kernel-t210-4.9.299-tegra-32.7.3- 100%[=====================================================================================================================>] 7.84M 823KB/s in 9.3s

2023-03-14 17:49:18 (859 KB/s) - ‘arducam-nvidia-l4t-kernel-t210-4.9.299-tegra-32.7.3-20230111085049_arm64_imx477.deb’ saved [8222530/8222530]

(Reading database … 169311 files and directories currently installed.)
Preparing to unpack arducam-nvidia-l4t-kernel-t210-4.9.299-tegra-32.7.3-20230111085049_arm64_imx477.deb …
Unpacking arducam-nvidia-l4t-kernel (4.9.299-tegra-32.7.3-20230111085049) over (4.9.299-tegra-32.7.3-20230111085049) …
Setting up arducam-nvidia-l4t-kernel (4.9.299-tegra-32.7.3-20230111085049) …
Traceback (most recent call last):
File “/opt/arducam/jetson-io/config-by-hardware.py”, line 125, in
main()
File “/opt/arducam/jetson-io/config-by-hardware.py”, line 94, in main
jetson = board.Board()
File “/opt/arducam/jetson-io/Jetson/board.py”, line 223, in init
self.appdir = _board_partition_mount(‘APP’)
File “/opt/arducam/jetson-io/Jetson/board.py”, line 161, in _board_partition_mount
raise RuntimeError(“Mountpoint %s already exists!” % path)
RuntimeError: Mountpoint /mnt/APP already exists!
Jetson Nano CSI Connector not found.
Traceback (most recent call last):
File “/opt/arducam/jetson-io/config-by-hardware.py”, line 125, in
main()
File “/opt/arducam/jetson-io/config-by-hardware.py”, line 94, in main
jetson = board.Board()
File “/opt/arducam/jetson-io/Jetson/board.py”, line 223, in init
self.appdir = _board_partition_mount(‘APP’)
File “/opt/arducam/jetson-io/Jetson/board.py”, line 161, in _board_partition_mount
raise RuntimeError(“Mountpoint %s already exists!” % path)
RuntimeError: Mountpoint /mnt/APP already exists!
2

An unknown error occurred while installing dtoverlays.
dpkg: error processing package arducam-nvidia-l4t-kernel (–install):
installed arducam-nvidia-l4t-kernel package post-installation script subprocess returned error exit status 255
Errors were encountered while processing:
arducam-nvidia-l4t-kernel

Unknown error, please send the error message to support@arducam.com

I also cannot run jetson-io.py after execution of command
sudo /opt/arducam/jetson-io/jetson-io.py
interface only blinks for nanosecond and program ends without any output.

This particular camera was successfully installed on Jetson Nano 2GB with 128GB SD card, so I can assume it’s not a camera issue.

3

hello szozda.jakub

you cannot use Jetson-IO to configure CSI because it’s only support with developer kit.

it looks camera device cannot register correctly according to below errors.

since you’re using a customize board.
please double check it’s compatible with developer kits.
and… please check those device tree settings all correct to your customize board to enable IMX477.

4

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