Ubuntu L4T User Guide

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Getting Started

Host Environment

Ubuntu 18.04 (recommended) or 16.04

Force Recovery Mode

To enter force recovery mode, you can do:

1. Hold the Recovery key
2. Power on device
3. Wait for 5 seconds and you can release the Recovery key

Once it enters recovery mode successfully, the HDMI output should be disabled. Then, you have to connect a USB cable with TX2 device and PC. A new "nvidia apx" device will be detected on PC.

Flash Pre-built Image

First, make sure your TX2 device is already in Force Recover mode, and USB cable is connected.

Then, execute the TX2_flash.sh script which you can find it in the release folder.

$ sudo ./TX2_flash.sh

After script is done, the target device will boot into OS automatically.

Install SDK Components

SDK Manager

Download the SDK Manager for Jetson TX2 series from JetPack website.

You will need a nVidia developer account for access.

After download complete, install via dpkg.

$ sudo dpkg -i sdkmanager_0.9.14-4964_amd64.deb

Then, you're able to run SDK manager.

$ sdkmanager



In this section, we setup and run demo applications on TX2 target device.

Export deepstream sdk root first.

$ export DS_SDK_ROOT="/opt/nvidia/deepstream/deepstream-4.0"

Deepstream Samples

There are 3 kinds of object detector demos in deepstream SDK.

To replace the video file, you can modify the corresponding config files. For example,

$ vim deepstream_app_config_yoloV3.txt



$ cd $DS_SDK_ROOT/sources/objectDectector_FasterRCNN
$ wget --no-check-certificate  https://dl.dropboxusercontent.com/s/06ii098bu51d139/faster_rcnn_models.tgz?dl=0  -O faster-rcnn.tgz
$ tar zxvf  faster-rcnn.tgz  -C .  --strip-components=1  --exclude=ZF_*
$ cp /usr/src/tensorrt/data/faster-rcnn/faster_rcnn_test_iplugin.prototxt .

$ make -C nvdsinfer_custom_impl_fasterRCNN


$ deepstream-app -c deepstream_app_config_fasterRCNN.txt



$ cd $DS_SDK_ROOT/sources/objectDectector_SSD

$ cp /usr/src/tensorrt/data/ssd/ssd_coco_labels.txt .
$ pip install tensorflow-gpu

$ sudo apt-get install python-protobuf

$ wget http://download.tensorflow.org/models/object_detection/ssd_inception_v2_coco_2017_11_17.tar.gz
$ tar zxvf ssd_inception_v2_coco_2017_11_17.tar.gz
$ cd ssd_inception_v2_coco_2017_11_17
$ python3 /usr/lib/python3.6/dist-packages/uff/bin/convert_to_uff.py \
    frozen_inference_graph.pb  -O NMS  -p /usr/src/tensorrt/samples/sampleUffSSD/config.py  -o sample_ssd_relu6.uff
$ cp sample_ssd_relu6.uff ../

$ cd ..
$ make -C nvdsinfer_custom_impl_ssd


$ deepstream-app -c deepstream_app_config_ssd.txt



$ cd $DS_SDK_ROOT/sources/objectDectector_Yolo
$ ./prebuild.sh
$ export CUDA_VER=10.0
$ make -C nvdsinfer_custom_impl_Yolo


$ deepstream-app -c deepstream_app_config_yoloV3.txt
$ deepstream-app -c deepstream_app_config_yoloV3_tiny.txt

Deepstream Reference Apps