deepstream smart record deepstream smart record

The DeepStream Python application uses the Gst-Python API action to construct the pipeline and use probe functions to access data at various points in the pipeline. The params structure must be filled with initialization parameters required to create the instance. In existing deepstream-test5-app only RTSP sources are enabled for smart record. The deepstream-test2 progresses from test1 and cascades secondary network to the primary network. . The core SDK consists of several hardware accelerator plugins that use accelerators such as VIC, GPU, DLA, NVDEC and NVENC. The increasing number of IoT devices in "smart" environments, such as homes, offices, and cities, produce seemingly endless data streams and drive many daily decisions. TensorRT accelerates the AI inference on NVIDIA GPU. For example, the record starts when theres an object being detected in the visual field. Smart-rec-container=<0/1> By default, Smart_Record is the prefix in case this field is not set. In this documentation, we will go through, producing events to Kafka Cluster from AGX Xavier during DeepStream runtime, and. To get started with Python, see the Python Sample Apps and Bindings Source Details in this guide and DeepStream Python in the DeepStream Python API Guide. Smart-rec-container=<0/1> smart-rec-file-prefix= The streams are captured using the CPU. DeepStream pipelines can be constructed using Gst-Python, the GStreamer frameworks Python bindings. How does secondary GIE crop and resize objects? Can Gst-nvinfereserver (DeepSream Triton plugin) run on Nano platform? Duration of recording. Smart video record is used for event (local or cloud) based recording of original data feed. mp4, mkv), Troubleshooting in NvDCF 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, DeepStream plugins failing to load without DISPLAY variable set when launching DS dockers, 1. In this documentation, we will go through Host Kafka server, producing events to Kafka Cluster from AGX Xavier during DeepStream runtime, and You may also refer to Kafka Quickstart guide to get familiar with Kafka. Add this bin after the audio/video parser element in the pipeline. Therefore, a total of startTime + duration seconds of data will be recorded. # Configure this group to enable cloud message consumer. Here startTime specifies the seconds before the current time and duration specifies the seconds after the start of recording. What if I dont set default duration for smart record? Which Triton version is supported in DeepStream 6.0 release? How can I specify RTSP streaming of DeepStream output? Whats the throughput of H.264 and H.265 decode on dGPU (Tesla)? 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? Does smart record module work with local video streams? The pre-processing can be image dewarping or color space conversion. For example, the record starts when theres an object being detected in the visual field. How does secondary GIE crop and resize objects? See the deepstream_source_bin.c for more details on using this module. Sink plugin shall not move asynchronously to PAUSED, 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, DS-Riva ASR Yaml File Configuration Specifications, DS-Riva TTS Yaml File Configuration Specifications, You are migrating from DeepStream 5.x to DeepStream 6.0, 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, 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. Does DeepStream Support 10 Bit Video streams? #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. Which Triton version is supported in DeepStream 5.1 release? Why do I observe: A lot of buffers are being dropped. The SDK ships with several simple applications, where developers can learn about basic concepts of DeepStream, constructing a simple pipeline and then progressing to build more complex applications. With DeepStream you can trial our platform for free for 14-days, no commitment required. What is the difference between DeepStream classification and Triton classification? Using records Records are requested using client.record.getRecord (name). Batching is done using the Gst-nvstreammux plugin. On Jetson platform, I get same output when multiple Jpeg images are fed to nvv4l2decoder using multifilesrc plugin. It returns the session id which later can be used in NvDsSRStop() to stop the corresponding recording. Can users set different model repos when running multiple Triton models in single process? Python is easy to use and widely adopted by data scientists and deep learning experts when creating AI models. smart-rec-file-prefix= Copyright 2023, NVIDIA. This function creates the instance of smart record and returns the pointer to an allocated NvDsSRContext. How do I obtain individual sources after batched inferencing/processing? This means, the recording cannot be started until we have an Iframe. When to start smart recording and when to stop smart recording depend on your design. Here, start time of recording is the number of seconds earlier to the current time to start the recording. What is the difference between batch-size of nvstreammux and nvinfer? When expanded it provides a list of search options that will switch the search inputs to match the current selection. Gst-nvmsgconv converts the metadata into schema payload and Gst-nvmsgbroker establishes the connection to the cloud and sends the telemetry data. How can I determine whether X11 is running? The inference can use the GPU or DLA (Deep Learning accelerator) for Jetson AGX Xavier and Xavier NX. Yes, on both accounts. How to clean and restart? What if I dont set default duration for smart record? How can I display graphical output remotely over VNC? At the bottom are the different hardware engines that are utilized throughout the application. What are the sample pipelines for nvstreamdemux? DeepStream - Smart Video Recording DeepStream - IoT Edge DeepStream - Demos DeepStream - Common Issues Transfer Learning Toolkit - Getting Started Transfer Learning Toolkit - Specification Files Transfer Learning Toolkit - StreetNet (TLT2) Transfer Learning Toolkit - CovidNet (TLT2) Transfer Learning Toolkit - Classification (TLT2) Records are the main building blocks of deepstream's data-sync capabilities. A callback function can be setup to get the information of recorded video once recording stops. Optimizing nvstreammux config for low-latency vs Compute, 6. After inference, the next step could involve tracking the object. This is the time interval in seconds for SR start / stop events generation. The plugin for decode is called Gst-nvvideo4linux2. Path of directory to save the recorded file. The source code for this application is available in /opt/nvidia/deepstream/deepstream-6.0/sources/apps/sample_apps/deepstream-app. Why do I encounter such error while running Deepstream pipeline memory type configured and i/p buffer mismatch ip_surf 0 muxer 3? In smart record, encoded frames are cached to save on CPU memory. Why is that? Observing video and/or audio stutter (low framerate), 2. Records are created and retrieved using client.record.getRecord ('name') To learn more about how they are used, have a look at the Record Tutorial. Powered by Discourse, best viewed with JavaScript enabled. It will not conflict to any other functions in your application. Does Gst-nvinferserver support Triton multiple instance groups? Call NvDsSRDestroy() to free resources allocated by this function. This function stops the previously started recording. DeepStream 5.1 Jetson devices) to follow the demonstration. 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. 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. deepstream smart record. What is batch-size differences for a single model in different config files (, Generating a non-DeepStream (GStreamer) extension, Generating a DeepStream (GStreamer) extension, 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, 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, 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. smart-rec-cache= What trackers are included in DeepStream and which one should I choose for my application? However, when configuring smart-record for multiple sources the duration of the videos are no longer consistent (different duration for each video). What are different Memory transformations supported on Jetson and dGPU? What types of input streams does DeepStream 5.1 support? You can design your own application functions. 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. Does Gst-nvinferserver support Triton multiple instance groups? When executing a graph, the execution ends immediately with the warning No system specified. Object tracking is performed using the Gst-nvtracker plugin. 1 Like a7med.hish October 4, 2021, 12:18pm #7 When running live camera streams even for few or single stream, also output looks jittery? It comes pre-built with an inference plugin to do object detection cascaded by inference plugins to do image classification. This function starts writing the cached video data to a file. How can I construct the DeepStream GStreamer pipeline? Gst-nvvideoconvert plugin can perform color format conversion on the frame. It will not conflict to any other functions in your application. What is the difference between batch-size of nvstreammux and nvinfer? These 4 starter applications are available in both native C/C++ as well as in Python. It's free to sign up and bid on jobs. What are the recommended values for. # Use this option if message has sensor name as id instead of index (0,1,2 etc.). DeepStream Reference Application - deepstream-app DeepStream 6.1.1 Release documentation. Please make sure you understand how to migrate your DeepStream 5.1 custom models to DeepStream 6.0 before you start. My DeepStream performance is lower than expected. How can I check GPU and memory utilization on a dGPU system? Dieser Button zeigt den derzeit ausgewhlten Suchtyp an. How can I change the location of the registry logs? Please help to open a new topic if still an issue to support. This is currently supported for Kafka. Sink plugin shall not move asynchronously to PAUSED, 5. There are two ways in which smart record events can be generated - either through local events or through cloud messages. Why do I see the below Error while processing H265 RTSP stream? 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/*. Do I need to add a callback function or something else? DeepStream is a streaming analytic toolkit to build AI-powered applications. Why do I observe a lot of buffers being dropped when running deepstream-nvdsanalytics-test application on Jetson Nano ? Why does the RTSP source used in gst-launch pipeline through uridecodebin show blank screen followed by the error -. 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 is an optimized graph architecture built using the open source GStreamer framework. A Record is an arbitrary JSON data structure that can be created, retrieved, updated, deleted and listened to. DeepStream ships with several out of the box security protocols such as SASL/Plain authentication using username/password and 2-way TLS authentication. Revision 6f7835e1. 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. 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. You may use other devices (e.g. Where can I find the DeepStream sample applications? Can I stop it before that duration ends? What are different Memory types supported on Jetson and dGPU? For creating visualization artifacts such as bounding boxes, segmentation masks, labels there is a visualization plugin called Gst-nvdsosd. Path of directory to save the recorded file. This is a good reference application to start learning the capabilities of DeepStream. DeepStream applications can be deployed in containers using NVIDIA container Runtime. Does smart record module work with local video streams? Below diagram shows the smart record architecture: This module provides the following APIs. To enable audio, a GStreamer element producing encoded audio bitstream must be linked to the asink pad of the smart record bin. I started the record with a set duration. In existing deepstream-test5-app only RTSP sources are enabled for smart record. 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.