Tensor data is the raw tensor output that comes out after inference. It provides a built-in mechanism for obtaining frames from a variety of video sources for use in AI inference processing. Running without an X server (applicable for applications supporting RTSP streaming output), DeepStream Triton Inference Server Usage Guidelines, Creating custom DeepStream docker for dGPU using DeepStreamSDK package, Creating custom DeepStream docker for Jetson using DeepStreamSDK package, Recommended Minimal L4T Setup necessary to run the new docker images on Jetson, Python Bindings and Application Development, Expected Output for the DeepStream Reference Application (deepstream-app), DeepStream Reference Application - deepstream-test5 app, IoT Protocols supported and cloud configuration, Sensor Provisioning Support over REST API (Runtime sensor add/remove capability), DeepStream Reference Application - deepstream-audio app, DeepStream Audio Reference Application Architecture and Sample Graphs, DeepStream Reference Application - deepstream-nmos app, Using Easy-NMOS for NMOS Registry and Controller, DeepStream Reference Application on GitHub, Implementing a Custom GStreamer Plugin with OpenCV Integration Example, Description of the Sample Plugin: gst-dsexample, Enabling and configuring the sample plugin, Using the sample plugin in a custom application/pipeline, Implementing Custom Logic Within the Sample Plugin, Custom YOLO Model in the DeepStream YOLO App, NvMultiObjectTracker Parameter Tuning Guide, Components Common Configuration Specifications, libnvds_3d_dataloader_realsense Configuration Specifications, libnvds_3d_depth2point_datafilter Configuration Specifications, libnvds_3d_gl_datarender Configuration Specifications, libnvds_3d_depth_datasource Depth file source Specific Configuration Specifications, Configuration File Settings for Performance Measurement, IModelParser Interface for Custom Model Parsing, Configure TLS options in Kafka config file for DeepStream, Choosing Between 2-way TLS and SASL/Plain, Setup for RTMP/RTSP Input streams for testing, Pipelines with existing nvstreammux component, Reference AVSync + ASR (Automatic Speech Recognition) Pipelines with existing nvstreammux, Reference AVSync + ASR Pipelines (with new nvstreammux), Gst-pipeline with audiomuxer (single source, without ASR + new nvstreammux), Sensor provisioning with deepstream-test5-app, Callback implementation for REST API endpoints, DeepStream 3D Action Recognition App Configuration Specifications, Custom sequence preprocess lib user settings, Build Custom sequence preprocess lib and application From Source, Depth Color Capture to 2D Rendering Pipeline Overview, Depth Color Capture to 3D Point Cloud Processing and Rendering, Run RealSense Camera for Depth Capture and 2D Rendering Examples, Run 3D Depth Capture, Point Cloud filter, and 3D Points Rendering Examples, DeepStream 3D Depth Camera App Configuration Specifications, DS3D Custom Components Configuration Specifications, Lidar Point Cloud to 3D Point Cloud Processing and Rendering, Run Lidar Point Cloud Data File reader, Point Cloud Inferencing filter, and Point Cloud 3D rendering and data dump Examples, DeepStream Lidar Inference App Configuration Specifications, Networked Media Open Specifications (NMOS) in DeepStream, DeepStream Can Orientation App Configuration Specifications, Application Migration to DeepStream 6.2 from DeepStream 6.1, Running DeepStream 6.1 compiled Apps in DeepStream 6.2, Compiling DeepStream 6.1 Apps in DeepStream 6.2, User/Custom Metadata Addition inside NvDsBatchMeta, Adding Custom Meta in Gst Plugins Upstream from Gst-nvstreammux, Adding metadata to the plugin before Gst-nvstreammux, Gst-nvdspreprocess File Configuration Specifications, Gst-nvinfer File Configuration Specifications, Clustering algorithms supported by nvinfer, To read or parse inference raw tensor data of output layers, Gst-nvinferserver Configuration File Specifications, Tensor Metadata Output for Downstream Plugins, NvDsTracker API for Low-Level Tracker Library, Unified Tracker Architecture for Composable Multi-Object Tracker, Low-Level Tracker Comparisons and Tradeoffs, Setup and Visualization of Tracker Sample Pipelines, How to Implement a Custom Low-Level Tracker Library, NvStreamMux Tuning Solutions for specific use cases, 3.1. Free Trial Download See Riva in Action Read the NVIDIA Riva solution brief Announcing DeepStream 6.0 - NVIDIA Developer Forums DeepStream Version 6.0.1 NVIDIA GPU Driver Version 512.15 When I run the sample deepstream config app, everything loads up well but the nvv4l2decoder plugin is not able to load /dev/nvidia0. For more information on DeepStream documentation containing Development guide, Plug-ins manual, API reference manual, migration guide, . How to measure pipeline latency if pipeline contains open source components. Also, work with the models developer to ensure that it meets the requirements for the relevant industry and use case; that the necessary instruction and documentation are provided to understand error rates, confidence intervals, and results; and that the model is being used under the conditions and in the manner intended. The inference can be done using TensorRT, NVIDIAs inference accelerator runtime or can be done in the native framework such as TensorFlow or PyTorch using Triton inference server. How can I change the location of the registry logs? How to set camera calibration parameters in Dewarper plugin config file? See the C/C++ Sample Apps Source Details and Python Sample Apps and Bindings Source Details sections to learn more about the available apps. Why I cannot run WebSocket Streaming with Composer? DeepStream offers exceptional throughput for a wide variety of object detection, image processing, and instance segmentation AI models. Contents of the package. I have caffe and prototxt files for all the three models of mtcnn. class pyds.NvOSD_CircleParams . On Jetson platform, I get same output when multiple Jpeg images are fed to nvv4l2decoder using multifilesrc plugin. Each Lab Comes With World-Class Service and Support Here's What You Can Expect From NVIDIA LaunchPad Labs A Hands-On Experience Why does my image look distorted if I wrap my cudaMalloced memory into NvBufSurface and provide to NvBufSurfTransform? Why do I encounter such error while running Deepstream pipeline memory type configured and i/p buffer mismatch ip_surf 0 muxer 3? NVDS_LABEL_INFO_META : metadata type to be set for given label of classifier. DeepStream pipelines can be constructed using Gst-Python, the GStreamer frameworks Python bindings. Also with DeepStream 6.1.1, applications can communicate with independent/remote instances of Triton Inference Server using gPRC.