In this documentation, we will go through Host Kafka server, producing events to Kafka Cluster from AGX Xavier during DeepStream runtime, and The containers are available on NGC, NVIDIA GPU cloud registry. Copyright 2023, NVIDIA. Therefore, a total of startTime + duration seconds of data will be recorded. AGX Xavier consuming events from Kafka Cluster to trigger SVR. How does secondary GIE crop and resize objects? There is an option to configure a tracker. For example, the record starts when theres an object being detected in the visual field. All the individual blocks are various plugins that are used. Configure DeepStream application to produce events, 4. DeepStream is a streaming analytic toolkit to build AI-powered applications. In this app, developers will learn how to build a GStreamer pipeline using various DeepStream plugins. 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. Why do I observe a lot of buffers being dropped when running deepstream-nvdsanalytics-test application on Jetson Nano ? Why am I getting ImportError: No module named google.protobuf.internal when running convert_to_uff.py on Jetson AGX Xavier? To read more about these apps and other sample apps in DeepStream, see the C/C++ Sample Apps Source Details and Python Sample Apps and Bindings Source Details. How can I run the DeepStream sample application in debug mode? What should I do if I want to set a self event to control the record? At the heart of deepstreamHub lies a powerful data-sync engine: schemaless JSON documents called "records" can be manipulated and observed by backend-processes or clients. How can I construct the DeepStream GStreamer pipeline? Once frames are batched, it is sent for inference. How do I obtain individual sources after batched inferencing/processing? Here startTime specifies the seconds before the current time and duration specifies the seconds after the start of recording. Why is that? By executing this consumer.py when AGX Xavier is producing the events, we now can read the events produced from AGX Xavier: Note that messages we received earlier is device-to-cloud messages produced from AGX Xavier. When deepstream-app is run in loop on Jetson AGX Xavier using while true; do deepstream-app -c ; done;, after a few iterations I see low FPS for certain iterations. Why do I observe: A lot of buffers are being dropped. What are the sample pipelines for nvstreamdemux? To make it easier to get started, DeepStream ships with several reference applications in both in C/C++ and in Python. Recording also can be triggered by JSON messages received from the cloud. By default, the current directory is used. Why does the deepstream-nvof-test application show the error message Device Does NOT support Optical Flow Functionality ? DeepStream provides building blocks in the form of GStreamer plugins that can be used to construct an efficient video analytic pipeline. And once it happens, container builder may return errors again and again. 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 Sample Apps and Bindings Source Details, Python Bindings and Application Development, DeepStream Reference Application - deepstream-app, 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. Thanks again. For example, if t0 is the current time and N is the start time in seconds that means recording will start from t0 N. For it to work, the video cache size must be greater than the N. smart-rec-default-duration=
How can I check GPU and memory utilization on a dGPU system? By default, Smart_Record is the prefix in case this field is not set. How can I determine whether X11 is running? Running with an X server by creating virtual display, 2 . Smart Video Record DeepStream 6.1.1 Release documentation, DeepStream Reference Application - deepstream-app DeepStream 6.1.1 Release documentation. Why is that? Do I need to add a callback function or something else? How to find out the maximum number of streams supported on given platform? MP4 and MKV containers are supported. To activate this functionality, populate and enable the following block in the application configuration file: While the application is running, use a Kafka broker to publish the above JSON messages on topics in the subscribe-topic-list to start and stop recording. What is batch-size differences for a single model in different config files (, Create Container Image from Graph Composer, Generate an extension for GXF wrapper of GstElement, Extension and component factory registration boilerplate, Implementation of INvDsInPlaceDataHandler, Implementation of an Configuration Provider component, DeepStream Domain Component - INvDsComponent, Probe Callback Implementation - INvDsInPlaceDataHandler, Element Property Controller INvDsPropertyController, Configurations INvDsConfigComponent template and specializations, INvDsVideoTemplatePluginConfigComponent / INvDsAudioTemplatePluginConfigComponent, Set the root folder for searching YAML files during loading, Starts the execution of the graph asynchronously, Waits for the graph to complete execution, Runs all System components and waits for their completion, Get unique identifier of the entity of given component, Get description and list of components in loaded Extension, Get description and list of parameters of Component, nvidia::gxf::DownstreamReceptiveSchedulingTerm, nvidia::gxf::MessageAvailableSchedulingTerm, nvidia::gxf::MultiMessageAvailableSchedulingTerm, nvidia::gxf::ExpiringMessageAvailableSchedulingTerm, nvidia::triton::TritonInferencerInterface, nvidia::triton::TritonRequestReceptiveSchedulingTerm, nvidia::deepstream::NvDs3dDataDepthInfoLogger, nvidia::deepstream::NvDs3dDataColorInfoLogger, nvidia::deepstream::NvDs3dDataPointCloudInfoLogger, nvidia::deepstream::NvDsActionRecognition2D, nvidia::deepstream::NvDsActionRecognition3D, nvidia::deepstream::NvDsMultiSrcConnection, nvidia::deepstream::NvDsGxfObjectDataTranslator, nvidia::deepstream::NvDsGxfAudioClassificationDataTranslator, nvidia::deepstream::NvDsGxfOpticalFlowDataTranslator, nvidia::deepstream::NvDsGxfSegmentationDataTranslator, nvidia::deepstream::NvDsGxfInferTensorDataTranslator, nvidia::BodyPose2D::NvDsGxfBodypose2dDataTranslator, nvidia::deepstream::NvDsMsgRelayTransmitter, nvidia::deepstream::NvDsMsgBrokerC2DReceiver, nvidia::deepstream::NvDsMsgBrokerD2CTransmitter, nvidia::FacialLandmarks::FacialLandmarksPgieModel, nvidia::FacialLandmarks::FacialLandmarksSgieModel, nvidia::FacialLandmarks::FacialLandmarksSgieModelV2, nvidia::FacialLandmarks::NvDsGxfFacialLandmarksTranslator, nvidia::HeartRate::NvDsHeartRateTemplateLib, nvidia::HeartRate::NvDsGxfHeartRateDataTranslator, nvidia::deepstream::NvDsModelUpdatedSignal, nvidia::deepstream::NvDsInferVideoPropertyController, nvidia::deepstream::NvDsLatencyMeasurement, nvidia::deepstream::NvDsAudioClassificationPrint, nvidia::deepstream::NvDsPerClassObjectCounting, nvidia::deepstream::NvDsModelEngineWatchOTFTrigger, nvidia::deepstream::NvDsRoiClassificationResultParse, nvidia::deepstream::INvDsInPlaceDataHandler, nvidia::deepstream::INvDsPropertyController, nvidia::deepstream::INvDsAudioTemplatePluginConfigComponent, nvidia::deepstream::INvDsVideoTemplatePluginConfigComponent, nvidia::deepstream::INvDsInferModelConfigComponent, nvidia::deepstream::INvDsGxfDataTranslator, nvidia::deepstream::NvDsOpticalFlowVisual, nvidia::deepstream::NvDsVideoRendererPropertyController, nvidia::deepstream::NvDsSampleProbeMessageMetaCreation, nvidia::deepstream::NvDsSampleSourceManipulator, nvidia::deepstream::NvDsSampleVideoTemplateLib, nvidia::deepstream::NvDsSampleAudioTemplateLib, nvidia::deepstream::NvDsSampleC2DSmartRecordTrigger, nvidia::deepstream::NvDsSampleD2C_SRMsgGenerator, nvidia::deepstream::NvDsResnet10_4ClassDetectorModel, nvidia::deepstream::NvDsSecondaryCarColorClassifierModel, nvidia::deepstream::NvDsSecondaryCarMakeClassifierModel, nvidia::deepstream::NvDsSecondaryVehicleTypeClassifierModel, nvidia::deepstream::NvDsSonyCAudioClassifierModel, nvidia::deepstream::NvDsCarDetector360dModel, nvidia::deepstream::NvDsSourceManipulationAction, nvidia::deepstream::NvDsMultiSourceSmartRecordAction, nvidia::deepstream::NvDsMultiSrcWarpedInput, nvidia::deepstream::NvDsMultiSrcInputWithRecord, nvidia::deepstream::NvDsOSDPropertyController, nvidia::deepstream::NvDsTilerEventHandler, Setting up a Connection from an Input to an Output, A Basic Example of Container Builder Configuration, Container builder main control section specification, Container dockerfile stage section specification. Why is a Gst-nvegltransform plugin required on a Jetson platform upstream from Gst-nveglglessink? Can I record the video with bounding boxes and other information overlaid? Why is that? How can I display graphical output remotely over VNC? What is batch-size differences for a single model in different config files (. What if I dont set video cache size for smart record? Why am I getting ImportError: No module named google.protobuf.internal when running convert_to_uff.py on Jetson AGX Xavier? For unique names every source must be provided with a unique prefix. Can I stop it before that duration ends? Duration of recording. What happens if unsupported fields are added into each section of the YAML file? How can I verify that CUDA was installed correctly? There are two ways in which smart record events can be generated either through local events or through cloud messages. In SafeFac a set of cameras installed on the assembly line are used to captu. I started the record with a set duration. , awarded WBR. This function starts writing the cached audio/video data to a file. How does secondary GIE crop and resize objects? My component is getting registered as an abstract type. In the main control section, why is the field container_builder required? tensorflow python framework errors impl notfounderror no cpu devices are available in this process Why do I see the below Error while processing H265 RTSP stream? Below diagram shows the smart record architecture: This module provides the following APIs. Optimizing nvstreammux config for low-latency vs Compute, 6. I started the record with a set duration. My DeepStream performance is lower than expected. Why does my image look distorted if I wrap my cudaMalloced memory into NvBufSurface and provide to NvBufSurfTransform? London, awarded World book of records How to use the OSS version of the TensorRT plugins in DeepStream? What is the approximate memory utilization for 1080p streams on dGPU? It comes pre-built with an inference plugin to do object detection cascaded by inference plugins to do image classification. The message format is as follows: Receiving and processing such messages from the cloud is demonstrated in the deepstream-test5 sample application. How to fix cannot allocate memory in static TLS block error? Ive already run the program with multi streams input while theres another question Id like to ask. What is the recipe for creating my own Docker image? To enable smart record in deepstream-test5-app set the following under [sourceX] group: To enable smart record through only cloud messages, set smart-record=1 and configure [message-consumerX] group accordingly. For unique names every source must be provided with a unique prefix. How to clean and restart? They will take video from a file, decode, batch and then do object detection and then finally render the boxes on the screen. Add this bin after the audio/video parser element in the pipeline. How can I determine whether X11 is running? This function stops the previously started recording. Thanks for ur reply! Only the data feed with events of importance is recorded instead of always saving the whole feed. This means, the recording cannot be started until we have an Iframe. How can I check GPU and memory utilization on a dGPU system? For creating visualization artifacts such as bounding boxes, segmentation masks, labels there is a visualization plugin called Gst-nvdsosd. Where can I find the DeepStream sample applications? Gst-nvdewarper plugin can dewarp the image from a fisheye or 360 degree camera. If you set smart-record=2, this will enable smart record through cloud messages as well as local events with default configurations. Why do some caffemodels fail to build after upgrading to DeepStream 5.1? Abstract This work presents SafeFac, an intelligent camera-based system for managing the safety of factory environments. # Use this option if message has sensor name as id instead of index (0,1,2 etc.). To get started, developers can use the provided reference applications. If current time is t1, content from t1 - startTime to t1 + duration will be saved to file. There are several built-in broker protocols such as Kafka, MQTT, AMQP and Azure IoT. How can I run the DeepStream sample application in debug mode? How can I specify RTSP streaming of DeepStream output? KAFKA_TRANSACTION_STATE_LOG_REPLICATION_FACTOR, KAFKA_CONFLUENT_LICENSE_TOPIC_REPLICATION_FACTOR, KAFKA_CONFLUENT_BALANCER_TOPIC_REPLICATION_FACTOR, CONFLUENT_METRICS_REPORTER_BOOTSTRAP_SERVERS, CONFLUENT_METRICS_REPORTER_TOPIC_REPLICAS, 3. Why do I see the below Error while processing H265 RTSP stream? Copyright 2020-2021, NVIDIA. Gst-nvvideoconvert plugin can perform color format conversion on the frame. smart-rec-file-prefix=
Finally to output the results, DeepStream presents various options: render the output with the bounding boxes on the screen, save the output to the local disk, stream out over RTSP or just send the metadata to the cloud. Python Sample Apps and Bindings Source Details, DeepStream Reference Application - deepstream-app, Install librdkafka (to enable Kafka protocol adaptor for message broker), Run deepstream-app (the reference application), Remove all previous DeepStream installations, Install CUDA Toolkit 11.4.1 (CUDA 11.4 Update 1), Run the deepstream-app (the reference application), dGPU Setup for RedHat Enterprise Linux (RHEL), Install CUDA Toolkit 11.4 (CUDA 11.4 Update 1), DeepStream Triton Inference Server Usage Guidelines, Creating custom DeepStream docker for dGPU using DeepStreamSDK package, Creating custom DeepStream docker for Jetson using DeepStreamSDK package, 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, DeepStream Reference Application - deepstream-audio app, DeepStream Audio Reference Application Architecture and Sample Graphs, 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, 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), DeepStream 3D Action Recognition App Configuration Specifications, Custom sequence preprocess lib user settings, Build Custom sequence preprocess lib and application From Source, Application Migration to DeepStream 6.0 from DeepStream 5.X, Major Application Differences with DeepStream 5.X, Running DeepStream 5.X compiled Apps in DeepStream 6.0, Compiling DeepStream 5.1 Apps in DeepStream 6.0, Low-level Object Tracker Library Migration from DeepStream 5.1 Apps to DeepStream 6.0, 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 File Configuration Specifications, Tensor Metadata Output for DownStream Plugins, NvDsTracker API for Low-Level Tracker Library, Unified Tracker Architecture for Composable Multi-Object Tracker, Visualization of Sample Outputs and Correlation Responses, Low-Level Tracker Comparisons and Tradeoffs, How to Implement a Custom Low-Level Tracker Library, NvStreamMux Tuning Solutions for specific usecases, 3.1Video and Audio muxing; file sources of different fps, 3.2 Video and Audio muxing; RTMP/RTSP sources, 4.1 GstAggregator plugin -> filesink does not write data into the file, 4.2 nvstreammux WARNING Lot of buffers are being dropped, 1. When running live camera streams even for few or single stream, also output looks jittery? Where can I find the DeepStream sample applications? The inference can use the GPU or DLA (Deep Learning accelerator) for Jetson AGX Xavier and Xavier NX. After pulling the container, you might open the notebook deepstream-rtsp-out.ipynb and create a RTSP source. Here startTime specifies the seconds before the current time and duration specifies the seconds after the start of recording. You can design your own application functions. Why is the Gst-nvstreammux plugin required in DeepStream 4.0+? To activate this functionality, populate and enable the following block in the application configuration file: While the application is running, use a Kafka broker to publish the above JSON messages on topics in the subscribe-topic-list to start and stop recording. This function starts writing the cached video data to a file. Smart video recording (SVR) is an event-based recording that a portion of video is recorded in parallel to DeepStream pipeline based on objects of interests or specific rules for recording. The first frame in the cache may not be an Iframe, so, some frames from the cache are dropped to fulfil this condition. After decoding, there is an optional image pre-processing step where the input image can be pre-processed before inference. Why is the Gst-nvstreammux plugin required in DeepStream 4.0+? Why is that? Can users set different model repos when running multiple Triton models in single process? What should I do if I want to set a self event to control the record? Lets go back to AGX Xavier for next step. DeepStream applications can be created without coding using the Graph Composer. How can I determine the reason? Why do some caffemodels fail to build after upgrading to DeepStream 6.2? Can Gst-nvinferserver support inference on multiple GPUs? The params structure must be filled with initialization parameters required to create the instance. On Jetson platform, I observe lower FPS output when screen goes idle. World-class customer support and in-house procurement experts. Which Triton version is supported in DeepStream 5.1 release? What trackers are included in DeepStream and which one should I choose for my application? The DeepStream runtime system is pipelined to enable deep learning inference, image, and sensor processing, and sending insights to the cloud in a streaming application. DeepStream is only a SDK which provide HW accelerated APIs for video inferencing, video decoding, video processing, etc. I can run /opt/nvidia/deepstream/deepstream-5.1/sources/apps/sample_apps/deepstream-testsr to implement Smart Video Record, but now I would like to ask if Smart Video Record supports multi streams? In case duration is set to zero, recording will be stopped after defaultDuration seconds set in NvDsSRCreate(). Are multiple parallel records on same source supported? Prefix of file name for generated video. How can I specify RTSP streaming of DeepStream output? Any data that is needed during callback function can be passed as userData. I'll be adding new github Issues for both items, but will leave this issue open until then. What is the recipe for creating my own Docker image? The registry failed to perform an operation and reported an error message. To trigger SVR, AGX Xavier expects to receive formatted JSON messages from Kafka server: To implement custom logic to produce the messages, we write trigger-svr.py. Once the frames are in the memory, they are sent for decoding using the NVDEC accelerator. This parameter will ensure the recording is stopped after a predefined default duration. Surely it can. Which Triton version is supported in DeepStream 6.0 release? Why do I see the below Error while processing H265 RTSP stream? Configure Kafka server (kafka_2.13-2.8.0/config/server.properties): To host Kafka server, we open first terminal: Open a third terminal, and create a topic (You may think of a topic as a YouTube Channel which others people can subscribe to): You might check topic list of a Kafka server: Now, Kafka server is ready for AGX Xavier to produce events. On Jetson platform, I get same output when multiple Jpeg images are fed to nvv4l2decoder using multifilesrc plugin. How to find out the maximum number of streams supported on given platform? DeepStream Reference Application - deepstream-app DeepStream 6.1.1 Release documentation. . Search for jobs related to Freelancer projects vlsi embedded or hire on the world's largest freelancing marketplace with 22m+ jobs. How to find the performance bottleneck in DeepStream? Produce device-to-cloud event messages, 5. Details are available in the Readme First section of this document. Issue Type( questions). How do I obtain individual sources after batched inferencing/processing? The size of the video cache can be configured per use case. From the pallet rack to workstation, #Rexroth's MP1000R mobile robot offers a smart, easy-to-implement material transport solution to help you boost
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