C/C++ Sample Apps Source Details

The DeepStream SDK package includes archives containing plugins, libraries, applications, and source code. The sources directory is located at /opt/nvidia/deepstream/deepstream-5.0/sources for both Debian installation (on Jetson or dGPU) and for installation by SDK Manager. For tar packages the source files are in the extracted deepstream package. DeepStream Python bindings and sample applications are available as a separate package. More information and documentation can be found at https://github.com/NVIDIA-AI-IOT/deepstream_python_apps.

Sample source details

Reference test application

Path inside sources directory


Sample test application 1


Sample of how to use DeepStream elements for a single H.264 stream: filesrc → decode → nvstreammux → nvinfer (primary detector) → nvdsosd → renderer.

Sample test application 2


Sample of how to use DeepStream elements for a single H.264 stream: filesrc → decode → nvstreammux → nvinfer (primary detector) → nvtracker → nvinfer (secondary classifier) → nvdsosd → renderer.

Sample test application 3


Builds on deepstream-test1 (simple test application 1) to demonstrate how to:

  • Use multiple sources in the pipeline

  • Use a uridecodebin to accept any type of input (e.g. RTSP/File), any GStreamer supported container format, and any codec

  • Configure Gst-nvstreammux to generate a batch of frames and infer on it for better resource utilization

  • Extract the stream metadata, which contains useful information about the frames in the batched buffer

Sample test application 4


Builds on deepstream-test1 for a single H.264 stream: filesrc, decode, nvstreammux, nvinfer, nvdsosd, renderer to demonstrate how to:

  • Use the Gst-nvmsgconv and Gst-nvmsgbroker plugins in the pipeline

  • Create NVDS_META_EVENT_MSG type metadata and attach it to the buffer

  • Use NVDS_META_EVENT_MSG for different types of objects, e.g. vehicle and person

  • Implement “copy” and “free” functions for use if metadata is extended through the extMsg field

Sample test application 5


Builds on top of deepstream-app. Demonstrates:

  • Use of Gst-nvmsgconv and Gst-nvmsgbroker plugins in the pipeline for multistream

  • How to configure Gst-nvmsgbroker plugin from the config file as a sink plugin (for KAFKA, Azure, etc.)

  • How to handle the RTCP sender reports from RTSP servers or cameras and translate the Gst Buffer PTS to a UTC timestamp.

For more details refer the RTCP Sender Report callback function test5_rtcp_sender_report_callback() registration and usage in deepstream_test5_app_main.c. GStreamer callback registration with rtpmanager element’s “handle-sync” signal is documented in apps-common/src/deepstream_source_bin.c.

AMQP protocol test application


Application to test AMQP protocol.

Azure MQTT test application


Test application to show Azure IoT device2edge messaging and device2cloud messaging using MQTT.

DeepStream reference application


Source code for the DeepStream reference application.

UFF SSD detector


Configuration files and custom library implementation for the SSD detector model.

Faster RCNN detector


Configuration files and custom library implementation for the FasterRCNN model.

Yolo detector


Configuration files and custom library implementation for the Yolo models, currently Yolo v2, v2 tiny, v3, and v3 tiny.

Dewarper example


Demonstrates dewarper functionality for single or multiple 360-degree camera streams. Reads camera calibration parameters from a CSV file and renders aisle and spot surfaces on the display.

Optical flow example


Demonstrates optical flow functionality for single or multiple streams. This example uses two GStreamer plugins (Gst-nvof and Gst-nvofvisual). The Gst-nvof element generates the MV (motion vector) data and attaches it as user metadata. The Gst-nvofvisual element visualizes the MV data using a predefined color wheel matrix.

Custom meta data example


Demonstrates how to add custom or user-specific metadata to any component of DeepStream. The test code attaches a 16-byte array filled with user data to the chosen component. The data is retrieved in another component.

MJPEG and JPEG decoder and inferencing example


Builds on deepstream-test3 to demonstrate image decoding instead of video. This example uses a custom decode bin so the MJPEG codec can be used as input.

Image/Video segmentation example


Demonstrates segmentation of multi-stream video or images using a semantic or industrial neural network and rendering output to a display.

Handling metadata before Gst-nvstreammux


Demonstrates how to set metadata before the Gst-nvstreammux plugin in the DeepStream pipeline, and how to access it after Gst-nvstreammux.

Gst-nvinfer tensor meta flow example


Demonstrates how to flow and access nvinfer tensor output as metadata.

Performance demo


Performs single channel cascaded inferencing and object tracking sequentially on all streams in a directory.

Analytics example


Demonstrates batched analytics like ROI filtering, Line crossing, direction detection and overcrowding

OpenCV example


Demonstrates the use of OpenCV in dsexample plugin

Image as Metadata example

Apps/sample_apps / deepstream-image-meta-test

Demonstrates how to attach encoded image as meta data and save the images in jpeg format.

Appsrc and Appsink example


Demonstrates AppSrc and AppSink usage for consuming and giving data from non DeepStream code respectively.

Transfer learning example

apps/sample_apps/ deepstream-transfer-learning-app

Demonstrates a mechanism to save the images for objects which have lesser confidence and the same can be used for training further

Mask-RCNN example

apps/sample_apps/ deepstream-mrcnn-test

Demonstrates Instance segmentation using Mask-RCNN model

Plugin and Library Source Details

The following table describes the contents of the sources directory except for the reference test applications, which are listed separately below:

Plugin and Library source details

Plugin or library

Path inside sources directory


DsExample GStreamer plugin


Template plugin for integrating custom algorithms into DeepStream SDK graph.

GStreamer Gst-nvmsgconv plugin


Source code for the GStreamer Gst-nvmsgconv plugin to convert metadata to schema format.

GStreamer Gst-nvmsgbroker plugin


Source code for the GStreamer Gst-nvmsgbroker plugin to send data to the server.

GStreamer Gst-nvinfer plugin


Source code for the GStreamer Gst-nvinfer plugin for inference.

GStreamer Gst-nvdsosd plugin


Source code for the GStreamer Gst-nvdsosd plugin to draw bboxes, text and other objects.

NvDsInfer library


Source code for the NvDsInfer library, used by the Gst-nvinfer GStreamer plugin.

NvMsgConv library


Source code for the NvMsgConv library, required by the Gst-nvmsgconv GStreamer plugin.

Kafka protocol adapter


Protocol adapter for Kafka.



Custom model output parsing example for detectors and classifiers.


See the note below 1

Source code for v4l2 codecs.



Gst-v4l2 sources are not present in DeepStream package. To download, follow these steps:

  1. Go to: https://developer.nvidia.com/embedded/downloads.

  2. In the Search filter field, enter L4T sources

  3. Select the appropriate item for L4T Release 32.4.3.

  4. Download the file and un-tar it, to get the .tbz2 file.

  5. Expand the .tbz2 file. Gst-v4l2 source files are in gst-nvvideo4linux2_src.tbz2