deepstream smart record deepstream smart record

This application will work for all AI models with detailed instructions provided in individual READMEs. 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 the recipe for creating my own Docker image? Path of directory to save the recorded file. Uncategorized. smart-rec-interval= The streams are captured using the CPU. Once frames are batched, it is sent for inference. Batching is done using the Gst-nvstreammux plugin. This function creates the instance of smart record and returns the pointer to an allocated NvDsSRContext. smart-rec-duration= How to find the performance bottleneck in DeepStream? For unique names every source must be provided with a unique prefix. Custom broker adapters can be created. Please see the Graph Composer Introduction for details. The params structure must be filled with initialization parameters required to create the instance. Running with an X server by creating virtual display, 2 . What is the difference between DeepStream classification and Triton classification? A Record is an arbitrary JSON data structure that can be created, retrieved, updated, deleted and listened to. These 4 starter applications are available in both native C/C++ as well as in Python. Why do I observe: A lot of buffers are being dropped. It takes the streaming data as input - from USB/CSI camera, video from file or streams over RTSP, and uses AI and computer vision to generate insights from pixels for better understanding of the environment. AGX Xavier consuming events from Kafka Cluster to trigger SVR. smart-rec-file-prefix= For example, the record starts when theres an object being detected in the visual field. Yes, on both accounts. The following minimum json message from the server is expected to trigger the Start/Stop of smart record. A video cache is maintained so that recorded video has frames both before and after the event is generated. What is the approximate memory utilization for 1080p streams on dGPU? For unique names every source must be provided with a unique prefix. London, awarded World book of records What are different Memory transformations supported on Jetson and dGPU? You can design your own application functions. How to enable TensorRT optimization for Tensorflow and ONNX models? However, when configuring smart-record for multiple sources the duration of the videos are no longer consistent (different duration for each video). How can I verify that CUDA was installed correctly? Based on the event, these cached frames are encapsulated under the chosen container to generate the recorded video. Hardware Platform (Jetson / CPU) World Book of Record Winner December 2020, Claim: Maximum number of textbooks published with ISBN number with a minimum period during COVID -19 lockdown period in India (between April 11, 2020, and July 01, 2020). Why does the RTSP source used in gst-launch pipeline through uridecodebin show blank screen followed by the error -. 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. Only the data feed with events of importance is recorded instead of always saving the whole feed. 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. Copyright 2020-2021, NVIDIA. For example, the record starts when theres an object being detected in the visual field. DeepStream SDK can be the foundation layer for a number of video analytic solutions like understanding traffic and pedestrians in smart city, health and safety monitoring in hospitals, self-checkout and analytics in retail, detecting component defects at a manufacturing facility and others. recordbin of NvDsSRContext is smart record bin which must be added to the pipeline. 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 is a streaming analytic toolkit to build AI-powered applications. 1 Like a7med.hish October 4, 2021, 12:18pm #7 smart-rec-dir-path= 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 At the bottom are the different hardware engines that are utilized throughout the application. Read more about DeepStream here. What is maximum duration of data I can cache as history for smart record? 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. Are multiple parallel records on same source supported? Why does the deepstream-nvof-test application show the error message Device Does NOT support Optical Flow Functionality ? For sending metadata to the cloud, DeepStream uses Gst-nvmsgconv and Gst-nvmsgbroker plugin. Before SVR is being triggered, configure [source0 ] and [message-consumer0] groups in DeepStream config (test5_dec_infer-resnet_tracker_sgie_tiled_display_int8.txt): Once the app config file is ready, run DeepStream: Finally, you are able to see recorded videos in your [smart-rec-dir-path] under [source0] group of the app config file. [When user expect to use Display window], 2. The core SDK consists of several hardware accelerator plugins that use accelerators such as VIC, GPU, DLA, NVDEC and NVENC. They will take video from a file, decode, batch and then do object detection and then finally render the boxes on the screen. Why does my image look distorted if I wrap my cudaMalloced memory into NvBufSurface and provide to NvBufSurfTransform? Does Gst-nvinferserver support Triton multiple instance groups? It expects encoded frames which will be muxed and saved to the file. Can users set different model repos when running multiple Triton models in single process? Call NvDsSRDestroy() to free resources allocated by this function. Container Contents Each NetFlow record . How can I run the DeepStream sample application in debug mode? Does smart record module work with local video streams? The core function of DSL is to provide a simple and intuitive API for building, playing, and dynamically modifying NVIDIA DeepStream Pipelines. How to minimize FPS jitter with DS application while using RTSP Camera Streams? Why is that? Why is that? 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. 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? deepstream-testsr is to show the usage of smart recording interfaces. There is an option to configure a tracker. Why cant I paste a component after copied one? Why am I getting ImportError: No module named google.protobuf.internal when running convert_to_uff.py on Jetson AGX Xavier? Revision 6f7835e1. Where can I find the DeepStream sample applications? How can I construct the DeepStream GStreamer pipeline? There are more than 20 plugins that are hardware accelerated for various tasks. The message format is as follows: Receiving and processing such messages from the cloud is demonstrated in the deepstream-test5 sample application. When running live camera streams even for few or single stream, also output looks jittery? Can Gst-nvinferserver support inference on multiple GPUs? That means smart record Start/Stop events are generated every 10 seconds through local events. How can I display graphical output remotely over VNC? userData received in that callback is the one which is passed during NvDsSRStart(). DeepStream is only a SDK which provide HW accelerated APIs for video inferencing, video decoding, video processing, etc. What is the official DeepStream Docker image and where do I get it? Here startTime specifies the seconds before the current time and duration specifies the seconds after the start of recording. How can I determine whether X11 is running? What are different Memory types supported on Jetson and dGPU? In existing deepstream-test5-app only RTSP sources are enabled for smart record. Gst-nvvideoconvert plugin can perform color format conversion on the frame. See NVIDIA-AI-IOT Github page for some sample DeepStream reference apps. 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. # Use this option if message has sensor name as id instead of index (0,1,2 etc.). What is maximum duration of data I can cache as history for smart record? #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. How can I check GPU and memory utilization on a dGPU system? The property bufapi-version is missing from nvv4l2decoder, what to do? Why do I observe: A lot of buffers are being dropped. It will not conflict to any other functions in your application. In case duration is set to zero, recording will be stopped after defaultDuration seconds set in NvDsSRCreate(). Can Gst-nvinferserver support models cross processes or containers? The source code for this application is available in /opt/nvidia/deepstream/deepstream-6.0/sources/apps/sample_apps/deepstream-app.