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. In smart record, encoded frames are cached to save on CPU memory. Thanks again. MP4 and MKV containers are supported. How to extend this to work with multiple sources? What types of input streams does DeepStream 6.2 support? What are different Memory transformations supported on Jetson and dGPU? What if I do not get expected 30 FPS from camera using v4l2src plugin in pipeline but instead get 15 FPS or less than 30 FPS? Smart Video Record DeepStream 6.1.1 Release documentation 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. Dieser Button zeigt den derzeit ausgewhlten Suchtyp an. Which Triton version is supported in DeepStream 6.0 release? Powered by Discourse, best viewed with JavaScript enabled. The reference application has capability to accept input from various sources like camera, RTSP input, encoded file input, and additionally supports multi stream/source capability. This parameter will ensure the recording is stopped after a predefined default duration. Freelancer I hope to wrap up a first version of ODE services and alpha v0.5 by the end of the week, Once released I'm going to start on the Deepstream 5 upgrade, and the Smart recording will be the first new ODE action to implement. What types of input streams does DeepStream 5.1 support? Prefix of file name for generated video. # Use this option if message has sensor name as id instead of index (0,1,2 etc.). Why do I see tracker_confidence value as -0.1.? Smart video record is used for event (local or cloud) based recording of original data feed. Why does my image look distorted if I wrap my cudaMalloced memory into NvBufSurface and provide to NvBufSurfTransform? To make it easier to get started, DeepStream ships with several reference applications in both in C/C++ and in Python. Records are the main building blocks of deepstream's data-sync capabilities. I started the record with a set duration. A callback function can be setup to get the information of recorded video once recording stops. 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. The DeepStream 360d app can serve as the perception layer that accepts multiple streams of 360-degree video to generate metadata and parking-related events. smart-rec-dir-path= How can I specify RTSP streaming of DeepStream output? Can Gst-nvinferserver support inference on multiple GPUs? Please see the Graph Composer Introduction for details. tensorflow python framework errors impl notfounderror no cpu devices are available in this process Why do I observe: A lot of buffers are being dropped. On Jetson platform, I get same output when multiple Jpeg images are fed to nvv4l2decoder using multifilesrc plugin. My component is getting registered as an abstract type. DeepStream builds on top of several NVIDIA libraries from the CUDA-X stack such as CUDA, TensorRT, NVIDIA Triton Inference server and multimedia libraries. How to enable TensorRT optimization for Tensorflow and ONNX models? What are different Memory types supported on Jetson and dGPU? DeepStream is optimized for NVIDIA GPUs; the application can be deployed on an embedded edge device running Jetson platform or can be deployed on larger edge or datacenter GPUs like T4. The inference can use the GPU or DLA (Deep Learning accelerator) for Jetson AGX Xavier and Xavier NX. Call NvDsSRDestroy() to free resources allocated by this function. 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. Smart video record is used for event (local or cloud) based recording of original data feed. Why do some caffemodels fail to build after upgrading to DeepStream 6.2? How can I specify RTSP streaming of DeepStream output? deepstream smart record. Where can I find the DeepStream sample applications? [When user expect to use Display window], 2. For developers looking to build their custom application, the deepstream-app can be a bit overwhelming to start development. London, awarded World book of records Optimizing nvstreammux config for low-latency vs Compute, 6. A callback function can be setup to get the information of recorded audio/video once recording stops. Read more about DeepStream here. World-class customer support and in-house procurement experts. Here, start time of recording is the number of seconds earlier to the current time to start the recording. MP4 and MKV containers are supported. They will take video from a file, decode, batch and then do object detection and then finally render the boxes on the screen. . For creating visualization artifacts such as bounding boxes, segmentation masks, labels there is a visualization plugin called Gst-nvdsosd. On Jetson platform, I get same output when multiple Jpeg images are fed to nvv4l2decoder using multifilesrc plugin. Why is a Gst-nvegltransform plugin required on a Jetson platform upstream from Gst-nveglglessink? How does secondary GIE crop and resize objects? What is the official DeepStream Docker image and where do I get it? 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? DeepStream 5.1 This application will work for all AI models with detailed instructions provided in individual READMEs. Add this bin after the audio/video parser element in the pipeline. How can I run the DeepStream sample application in debug mode? Also included are the source code for these applications. DeepStream supports application development in C/C++ and in Python through the Python bindings. Modifications made: (1) based on the results of the real-time video analysis, and: (2) by the application user through external input. Details are available in the Readme First section of this document. Does DeepStream Support 10 Bit Video streams? By executing this trigger-svr.py when AGX is producing the events, we now can not only consume the messages from AGX Xavier but also produce JSON messages to in Kafka server which will be subscribed by AGX Xavier to trigger SVR. mp4, mkv), DeepStream plugins failing to load without DISPLAY variable set when launching DS dockers, On Jetson, observing error : gstnvarguscamerasrc.cpp, execute:751 No cameras available. Its lightning-fast realtime data platform helps developers of any background or skillset build apps, IoT platforms, and backends that always stay in sync - without having to worry about infrastructure or . Each NetFlow record . 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. If you set smart-record=2, this will enable smart record through cloud messages as well as local events with default configurations. The graph below shows a typical video analytic application starting from input video to outputting insights. If you are trying to detect an object, this tensor data needs to be post-processed by a parsing and clustering algorithm to create bounding boxes around the detected object. 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. Gst-nvvideoconvert plugin can perform color format conversion on the frame. What is batch-size differences for a single model in different config files (. For example, the record starts when theres an object being detected in the visual field. See the deepstream_source_bin.c for more details on using this module. Copyright 2020-2021, NVIDIA. Refer to the deepstream-testsr sample application for more details on usage. Please make sure you understand how to migrate your DeepStream 5.1 custom models to DeepStream 6.0 before you start. How can I display graphical output remotely over VNC? Call NvDsSRDestroy() to free resources allocated by this function. How can I display graphical output remotely over VNC? When executing a graph, the execution ends immediately with the warning No system specified. smart-rec-start-time= Produce device-to-cloud event messages, 5. In this documentation, we will go through Host Kafka server, producing events to Kafka Cluster from AGX Xavier during DeepStream runtime, and #sensor-list-file=dstest5_msgconv_sample_config.txt, Install librdkafka (to enable Kafka protocol adaptor for message broker), Run deepstream-app (the reference application), Remove all previous DeepStream installations, Run the deepstream-app (the reference application), dGPU Setup for RedHat Enterprise Linux (RHEL), DeepStream Triton Inference Server Usage Guidelines, 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, DeepStream Reference Application - deepstream-audio app, ONNX Parser replace instructions (x86 only), 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, IModelParser Interface for Custom Model Parsing, Configure TLS options in Kafka config file for DeepStream, Choosing Between 2-way TLS and SASL/Plain, Application Migration to DeepStream 5.0 from DeepStream 4.X, Major Application Differences with DeepStream 4.X, Running DeepStream 4.x compiled Apps in DeepStream 5.0, Compiling DeepStream 4.X Apps in DeepStream 5.0, 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-nvinfer File Configuration Specifications, To read or parse inference raw tensor data of output layers, Gst-nvinferserver File Configuration Specifications, Low-Level Tracker Library Comparisons and Tradeoffs, nvds_msgapi_connect(): Create a Connection, nvds_msgapi_send() and nvds_msgapi_send_async(): Send an event, nvds_msgapi_subscribe(): Consume data by subscribing to topics, nvds_msgapi_do_work(): Incremental Execution of Adapter Logic, nvds_msgapi_disconnect(): Terminate a Connection, nvds_msgapi_getversion(): Get Version Number, nvds_msgapi_get_protocol_name(): Get name of the protocol, nvds_msgapi_connection_signature(): Get Connection signature, Connection Details for the Device Client Adapter, Connection Details for the Module Client Adapter, nv_msgbroker_connect(): Create a Connection, nv_msgbroker_send_async(): Send an event asynchronously, nv_msgbroker_subscribe(): Consume data by subscribing to topics, nv_msgbroker_disconnect(): Terminate a Connection, nv_msgbroker_version(): Get Version Number, You are migrating from DeepStream 4.0+ to DeepStream 5.0, NvDsBatchMeta not found for input buffer error while running DeepStream pipeline, The DeepStream reference application fails to launch, or any plugin fails to load, Application fails to run when the neural network is changed, The DeepStream application is running slowly (Jetson only), The DeepStream application is running slowly, NVIDIA Jetson Nano, deepstream-segmentation-test starts as expected, but crashes after a few minutes rebooting the system, Errors occur when deepstream-app is run with a number of streams greater than 100, Errors occur when deepstream-app fails to load plugin Gst-nvinferserver on dGPU only, Tensorflow models are running into OOM (Out-Of-Memory) problem, Memory usage keeps on increasing when the source is a long duration containerized files(e.g. This function creates the instance of smart record and returns the pointer to an allocated NvDsSRContext. That means smart record Start/Stop events are generated every 10 seconds through local events. # Configure this group to enable cloud message consumer. Why do some caffemodels fail to build after upgrading to DeepStream 5.1? It expects encoded frames which will be muxed and saved to the file. Please help to open a new topic if still an issue to support. The streams are captured using the CPU. This recording happens in parallel to the inference pipeline running over the feed. Can I stop it before that duration ends? What is the official DeepStream Docker image and where do I get it? # Use this option if message has sensor name as id instead of index (0,1,2 etc.). See the deepstream_source_bin.c for more details on using this module. Optimum memory management with zero-memory copy between plugins and the use of various accelerators ensure the highest performance. The first frame in the cache may not be an Iframe, so, some frames from the cache are dropped to fulfil this condition. Does DeepStream Support 10 Bit Video streams? A video cache is maintained so that recorded video has frames both before and after the event is generated. How to tune GPU memory for Tensorflow models? Configure [source0] and [sink1] groups of DeepStream app config configs/test5_dec_infer-resnet_tracker_sgie_tiled_display_int8.txt so that DeepStream is able to use RTSP source from step 1 and render events to your Kafka server: At this stage, our DeepStream application is ready to run and produce events containing bounding box coordinates to Kafka server: To consume the events, we write consumer.py. How can I interpret frames per second (FPS) display information on console? What happens if unsupported fields are added into each section of the YAML file? How can I verify that CUDA was installed correctly? How do I configure the pipeline to get NTP timestamps?