*****************************************************************************
* Copyright (c) 2018-2019 NVIDIA Corporation.  All rights reserved.
*
* NVIDIA Corporation and its licensors retain all intellectual property
* and proprietary rights in and to this software, related documentation
* and any modifications thereto.  Any use, reproduction, disclosure or
* distribution of this software and related documentation without an express
* license agreement from NVIDIA Corporation is strictly prohibited.
*****************************************************************************

***********************************************************************
                              README
                       DEEPSTREAM ON TEGRA SDK
                         QUICK START GUIDE
***********************************************************************
The NVIDIA® DeepStream on Jetson Software Development Kit (SDK) provides a
framework for constructing GPU-accelerated video analytics
applications running within the L4T package on the
Jetson platform.

=======================================================================
Package contents
=======================================================================
The DeepStream packages include:
1. binaries.tbz2 - Core binaries
2. sources - Sources for sample application and plugin
3. samples - Config files, models, streams and tools to run the sample app

=======================================================================
Prerequisites
=======================================================================
JetPack-4.2.2 is required to successfully run and use the
DeepStream on Jetson SDK. JetPack, including the latest L4T
release, is available for download at:
https://developer.nvidia.com/embedded/jetpack

After downloading the installer, follow the steps mentioned in SDK Manager
document to flash the L4T image to your target system.
The SDK Manager document is available for download at:
https://docs.nvidia.com/sdk-manager/index.html

=======================================================================
Additional components required on the target
=======================================================================
To successfully use the DeepStream SDK, the following additional
components must be installed and set up on the target system:
- CUDA (10.0)
- TensorRT (5.1+)
- OpenCV (3.3.1)
- VisionWorks (1.6)
Install these packages using JetPack SDK Manager.

=======================================================================
Installing prerequisite software on Jetson development board:
=======================================================================
Packages to be installed:
$ sudo apt-get install \
    libssl1.0.0 \
    libgstreamer1.0-0 \
    gstreamer1.0-tools \
    gstreamer1.0-plugins-good \
    gstreamer1.0-plugins-bad \
    gstreamer1.0-plugins-ugly \
    gstreamer1.0-libav \
    libgstrtspserver-1.0-0 \
    libjansson4

=======================================================================
Installing librdkafka to use kafka protocol adaptor with message broker
=======================================================================
Use one of the following steps.

  sudo apt-get install librdkafka1=0.11.3-1build1

_or_

  git clone https://github.com/edenhill/librdkafka.git
  cd librdkafka
  git reset --hard 7101c2310341ab3f4675fc565f64f0967e135a6a
  ./configure
  make
  sudo make install

  Set the LD_LIBRARY_PATH environment variable accordingly so that
  librdkafka binaries are in the system path.
  For example, you can use the following command assuming librdkafka is installed
  under /usr/local/lib.

  export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH

=======================================================================
Using Azure MQTT protocol adaptor with message broker
=======================================================================
Refer to the README files available under sources/libs/azure_protocol_adaptor
for detailed documentation on prerequisites and usages of azure MQTT protocol
adaptor with the message broker plugin for sending messages to cloud.

Refer to the source code and README of deepstream-test4 available under
sources/apps/sample_apps/deepstream-test4/ to send messages to the cloud.

=======================================================================
[Optional] Uninstall DeepStream 3.0
=======================================================================
Flash the target device with the latest release of JetPack.

=======================================================================
Installing DeepStream SDK on Jetson
=======================================================================
After using the JetPack SDK Manager, you are ready to install and run
the DeepStream SDK on Jetson.

To install the DeepStream SDK on Jetson:
1. On the Jetson target development board, determine the IP address by
   executing the command:
   ifconfig

2. Copy the DeepStream on Jetson SDK tarball from the host system to the NVIDIA
   home directory on the Jetson development board:
   scp deepstream_sdk_v4.0.1_jetson.tbz2 nvidia@$<ip_address>:~

   Where:
   - <ip_address> is the IP address as determined earlier.

3. On the Jetson development board, navigate to the DeepStream
   package and extract it to current directory as follows:
   sudo tar xpvf deepstream_sdk_v4.0.1_jetson.tbz2
   cd deepstream_sdk_v4.0.1_jetson

4. This package contains binaries.tbz2 and the directories sources and samples.

5. Untar binaries.tbz2:
   sudo tar -xvf binaries.tbz2 -C /

6. Run the install.sh script as follows:
   sudo ./install.sh

7. Execute the following command on the Jetson development board:
   sudo ldconfig

=======================================================================
Running the samples
=======================================================================
1. Go to samples directory and run:
   deepstream-app -c <path to config.txt>
2. Application config files included in `configs/deepstream-app/`:
   a. source30_1080p_dec_infer-resnet_tiled_display_int8.txt (30 Decode + Infer)
   b. source4_1080p_dec_infer-resnet_tracker_sgie_tiled_display_int8.txt
      (4 Decode + Infer + SGIE + Tracker)
3. Configuration files for "nvinfer" element in `configs/deepstream-app/`:
   a. config_infer_primary.txt (Primary Object Detector)
   b. config_infer_secondary_carcolor.txt (Secondary Car Color Classifier)
   c. config_infer_secondary_carmake.txt (Secondary Car Make Classifier)
   d. config_infer_secondary_vehicletypes.txt (Secondary Vehicle Type Classifier)

=======================================================================
Notes:
=======================================================================
1. If the application runs into errors and cannot create gst elements, try again
after removing gstreamer cache:
   rm ${HOME}/.cache/gstreamer-1.0/registry.aarch64.bin