That means smart record Start/Stop events are generated every 10 seconds through local events. At the bottom are the different hardware engines that are utilized throughout the application. 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. Can I record the video with bounding boxes and other information overlaid? If you set smart-record=2, this will enable smart record through cloud messages as well as local events with default configurations. Thanks for ur reply! 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. There are several built-in broker protocols such as Kafka, MQTT, AMQP and Azure IoT. 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? smart-rec-duration=
Path of directory to save the recorded file. To enable audio, a GStreamer element producing encoded audio bitstream must be linked to the asink pad of the smart record bin. Please help to open a new topic if still an issue to support. Why do I observe a lot of buffers being dropped When running deepstream-nvdsanalytics-test application on Jetson Nano ? smart-rec-interval= I started the record with a set duration. Sink plugin shall not move asynchronously to PAUSED, 5. Smart-rec-container=<0/1> Do I need to add a callback function or something else? How can I change the location of the registry logs? This button displays the currently selected search type. Why do I observe a lot of buffers being dropped when running deepstream-nvdsanalytics-test application on Jetson Nano ? Modifications made: (1) based on the results of the real-time video analysis, and: (2) by the application user through external input. Below diagram shows the smart record architecture: From DeepStream 6.0, Smart Record also supports audio. For deployment at scale, you can build cloud-native, DeepStream applications using containers and orchestrate it all with Kubernetes platforms. What are different Memory types supported on Jetson and dGPU? Why is the Gst-nvstreammux plugin required in DeepStream 4.0+? How to tune GPU memory for Tensorflow models? 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. 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. 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. DeepStream applications can be deployed in containers using NVIDIA container Runtime. Can Jetson platform support the same features as dGPU for Triton plugin? You can design your own application functions. Does smart record module work with local video streams? Optimizing nvstreammux config for low-latency vs Compute, 6. Once frames are batched, it is sent for inference. Smart-rec-container=<0/1>
How to handle operations not supported by Triton Inference Server? For creating visualization artifacts such as bounding boxes, segmentation masks, labels there is a visualization plugin called Gst-nvdsosd. It uses same caching parameters and implementation as video. On Jetson platform, I observe lower FPS output when screen goes idle. This application is covered in greater detail in the DeepStream Reference Application - deepstream-app chapter. In smart record, encoded frames are cached to save on CPU memory. How to tune GPU memory for Tensorflow models? By default, the current directory is used. Which Triton version is supported in DeepStream 5.1 release? Search for jobs related to Freelancer projects vlsi embedded or hire on the world's largest freelancing marketplace with 22m+ jobs. Any data that is needed during callback function can be passed as userData. In this documentation, we will go through Host Kafka server, producing events to Kafka Cluster from AGX Xavier during DeepStream runtime, and Why is that? Why is that? Here, start time of recording is the number of seconds earlier to the current time to start the recording. Are multiple parallel records on same source supported? This is currently supported for Kafka. My component is getting registered as an abstract type. Does Gst-nvinferserver support Triton multiple instance groups? 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. DeepStream supports application development in C/C++ and in Python through the Python bindings. How to use nvmultiurisrcbin in a pipeline, 3.1 REST API payload definitions and sample curl commands for reference, 3.1.1 ADD a new stream to a DeepStream pipeline, 3.1.2 REMOVE a new stream to a DeepStream pipeline, 4.1 Gst Properties directly configuring nvmultiurisrcbin, 4.2 Gst Properties to configure each instance of nvurisrcbin created inside this bin, 4.3 Gst Properties to configure the instance of nvstreammux created inside this bin, 5.1 nvmultiurisrcbin config recommendations and notes on expected behavior, 3.1 Gst Properties to configure nvurisrcbin, You are migrating from DeepStream 6.0 to DeepStream 6.2, Application fails to run when the neural network is changed, The DeepStream application is running slowly (Jetson only), The DeepStream application is running slowly, Errors occur when deepstream-app fails to load plugin Gst-nvinferserver, Tensorflow models are running into OOM (Out-Of-Memory) problem, Troubleshooting in Tracker Setup and Parameter Tuning, Frequent tracking ID changes although no nearby objects, Frequent tracking ID switches to the nearby objects, Error while running ONNX / Explicit batch dimension networks, My component is not visible in the composer even after registering the extension with registry. What if I dont set default duration for smart record? The latest release of #NVIDIADeepStream SDK version 6.2 delivers powerful enhancements such as state-of-the-art multi-object trackers, support for lidar and How can I verify that CUDA was installed correctly? The deepstream-test2 progresses from test1 and cascades secondary network to the primary network. 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. Why cant I paste a component after copied one? Following are the default values of configuration parameters: Following fields can be used under [sourceX] groups to configure these parameters. Size of video cache in seconds. Refer to this post for more details. How can I display graphical output remotely over VNC? This parameter will increase the overall memory usages of the application. DeepStream is only a SDK which provide HW accelerated APIs for video inferencing, video decoding, video processing, etc. What types of input streams does DeepStream 6.0 support? NVIDIA introduced Python bindings to help you build high-performance AI applications using Python. smart-rec-start-time=
On AGX Xavier, we first find the deepstream-app-test5 directory and create the sample application: If you are not sure which CUDA_VER you have, check */usr/local/*. For the output, users can select between rendering on screen, saving the output file, or streaming the video out over RTSP.
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