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https://github.com/jetsonhacksnano/installlibrealsense

Build and install Intel's librealsense for the NVIDIA Jetson Nano Developer Kit
https://github.com/jetsonhacksnano/installlibrealsense

jetson-nano librealsense realsense-camera realsense-sdk

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Build and install Intel's librealsense for the NVIDIA Jetson Nano Developer Kit

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README

        

# installLibrealsense
Build and install scripts for Intel's librealsense for the NVIDIA Jetson Nano Developer Kit

Original article on JetsonHacks: https://wp.me/p7ZgI9-34j

The Intel® RealSense™ SDK is here: https://github.com/IntelRealSense/librealsense
The SDK library name is librealsense. This is for version 2 of the library, which supports
the D400 series depth cameras, T265 tracking camera, and the SR300 depth camera.

It is now possible on the NVIDIA Jetsons to do a simple install from a RealSense debian repository
(i.e. apt-get install). Previous versions of this repository require building librealsense from source, and (possibly) rebuilding the Linux kernel.

The current recommendation from Intel is to use UVC for video input on the Jetson family. The
UVC API in librealsense has been rewritten to better support this use case.

installLibrealsense.sh


This script will install librealsense from the Intel Librealsense Debian Repository.

```
$ ./installLibrealsense.sh
```

Note: You do not have to patch modules and kernels.

buildLibrealsense.sh


This script will build librealsense from source and install it on the system. Note: It is recommended to install from Debian repository as described above. However, if you need to compile from source, you will find this script useful.

```
$ ./buildLibrealsense.sh [ -v | --version ] [ -j | -jobs ] [ -n | --no_cuda ]
```

Where:
* `` = Librealsense version. E.g. v2.49.0
* `` = # of jobs to run concurrently when building. Defaults to 1 if the Jetson has <= 4GB memory
* `` = Compile without CUDA support. Defaults to CUDA.

The librealsense Github repository has good documentation for supporting more advanced modes for the RealSense sensors. Please see: [installation_jetson.md](https://github.com/IntelRealSense/librealsense/blob/master/doc/installation_jetson.md) The documentation covers different communication interfaces and how to explore different features, some of which may require recompiling kernel modules.

Note: The build uses libuvc. You will not have to rebuild the kernel or modules in order to use this build.

Notes


If you use realsense-ros, make sure that you match the librealsense versions with the realsense-ros version requirement.

## Releases

### September, 2021
* Release v1.1
* Change release naming for this repository
* Updated keyserver URL
* Thank you Tomasz @tomek-I and Tommy @Tommyisr !
* Enhanced buildLibrealsense script
* Lookup latest version of librealsense from Github repository
* Allow override via CLI argument ( -v | -version )
* Allow user to specify number of build jobs ( -j | -jobs )
* If Jetson has > 4GB use number of cores - 1 ; otherwise 1
* Different parsing of comand line arguments using getopt
* Tested on Jetson Nano, L4T 32.6.1, JetPack 4.6
* installLibrealsense.sh installed v2.49.0
* Thank you Abdul @jazarie2 and Matt @droter for pull requests!

December, 2019

* Release vL4T32.3.1
* Jetson Nano
* L4T 32.3.1, JetPack 4.3, Kernel 4.9.
* Also works with L4T 32.2.1 - 32.2.3
* Current librealsense version v2.31.0
* Fixed Issue: D435i and T265 have issues working together. Upgrading D435i firmware fixes this issue.
* Requires realsense-ros version 2.2.11
* Now uses libuvc in buildLibrealsense, no need to recompile linux kernel/modules

November, 2019

* Release vL4T32.2.3
* Jetson Nano
* L4T 32.2.3, JetPack 4.2.2, Kernel 4.9.
* Also works with L4T 32.2.1
* Currently librealsense version v2.31.0
* Issue: L4T 32.2.3 has issues with using RealSense cameras D435i and T265 simultaneously. Under L4T 32.2.1 appears to work correctly.
* Requires realsense-ros version 2.2.11
* Now uses libuvc in buildLibrealsense, no need to recompile linux kernel/modules

October, 2019

* Release vL4T32.2.1
* Jetson Nano
* L4T 32.2.1, JetPack 4.2.2, Kernel 4.9
* librealsense version v2.25.0 (matches realsense-ros package)

July, 2019

* Release vL4T32.2
* Jetson Nano
* L4T 32.2, Kernel 4.9, JetPack 4.2.1
* Add Python 3 support
* UVC_MAX_STATUS changed in Kernel to 1024, remove Patch
* Remove URBS UVC patch
* librealsense version v2.24.0

June, 2019

* Release vL4T32.1
* Jetson Nano
* L4T 32.1.0, Kernel 4.9-140
* Bump librealsense version to v2.22.0 for compatibility with realsense-ros

June, 2019

* Release v0.9
* Jetson Nano
* L4T 32.1.0, Kernel 4.9-140
* Bump librealsense version to v2.22.0 for compatibility with realsense-ros

May, 2019

* Release v0.8
* Jetson Nano
* L4T 32.1.0, Kernel 4.9-140
* D435i issue resolved - Make kernel image before modules

May 6, 2019

* Initial Release v0.7
* Jetson Nano
* L4T 32.1.0, Kernel 4.9-140
* D435i issue addressed

April 30, 2019


installLibrealsense.sh

* Switch CLI argument to build_with_cuda ; Build with CUDA takes a lot more time because CMake needs to be rebuilt. Default is to build without CUDA support

* previous commit Add CLI argument build_no_cuda ; script defaults to build with CUDA.

* D435i is not recognized by RealSense applications, but shows up in Cheese webcam viewer.

April 29, 2019


installLibrealsense.sh

Add CUDACXX flag for compilation using CUDA

Add USE_CUDA flag to script (Defaults to YES)

If using only RealSense T265 camera, this is the only installation necessary

If using the T265, you probably don't need CUDA (still needs to be tested); Set USE_CUDA to false. Saves compilation time

During compilation, the script will run out of memory on the Nano
You will need either to:

* Enable swap memory

OR:

* Modify the script to 'make' with only 1 processor

patchUbuntu.sh

patchUbuntu will patch all of the needed modules for librealsense, build the modules, and then install the modules. The kernel Image is then built and installed in /boot/Image.

Note: If you are building from a USB or some other device than the SD card, you will need to copy the Image file to the /boot directory on the SD card.