deepstream smart record

[When user expect to not use a Display window], My component is not visible in the composer even after registering the extension with registry. There are two ways in which smart record events can be generated either through local events or through cloud messages. You may also refer to Kafka Quickstart guide to get familiar with Kafka. Recording also can be triggered by JSON messages received from the cloud. #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. Please help to open a new topic if still an issue to support. deepstream.io My DeepStream performance is lower than expected. deepstream.io MP4 and MKV containers are supported. 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. What if I dont set video cache size for smart record? And once it happens, container builder may return errors again and again. How to find out the maximum number of streams supported on given platform? The graph below shows a typical video analytic application starting from input video to outputting insights. deepstream smart record. It returns the session id which later can be used in NvDsSRStop() to stop the corresponding recording. 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) # default duration of recording in seconds. Smart Video Record DeepStream 5.1 Release documentation Can Gst-nvinferserver support inference on multiple GPUs? If you are familiar with gstreamer programming, it is very easy to add multiple streams. In the deepstream-test5-app, to demonstrate the use case smart record Start / Stop events are generated every interval second. The property bufapi-version is missing from nvv4l2decoder, what to do? How to handle operations not supported by Triton Inference Server? What if I dont set default duration for smart record? Why does the deepstream-nvof-test application show the error message Device Does NOT support Optical Flow Functionality ? 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. Does Gst-nvinferserver support Triton multiple instance groups? What should I do if I want to set a self event to control the record? Can Jetson platform support the same features as dGPU for Triton plugin? NVIDIA introduced Python bindings to help you build high-performance AI applications using Python. They are atomic bits of JSON data that can be manipulated and observed. Following are the default values of configuration parameters: Following fields can be used under [sourceX] groups to configure these parameters. Can users set different model repos when running multiple Triton models in single process? Why do I observe: A lot of buffers are being dropped. Why am I getting ImportError: No module named google.protobuf.internal when running convert_to_uff.py on Jetson AGX Xavier? Duration of recording. Why does my image look distorted if I wrap my cudaMalloced memory into NvBufSurface and provide to NvBufSurfTransform? What is the difference between batch-size of nvstreammux and nvinfer? Uncategorized. Add this bin after the parser element in the pipeline. On Jetson platform, I get same output when multiple Jpeg images are fed to nvv4l2decoder using multifilesrc plugin. 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. The performance benchmark is also run using this application. This application is covered in greater detail in the DeepStream Reference Application - deepstream-app chapter. These plugins use GPU or VIC (vision image compositor). Nothing to do. 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. For deployment at scale, you can build cloud-native, DeepStream applications using containers and orchestrate it all with Kubernetes platforms. Adding a callback is a possible way. The first frame in the cache may not be an Iframe, so, some frames from the cache are dropped to fulfil this condition. Only the data feed with events of importance is recorded instead of always saving the whole feed. 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. Can I record the video with bounding boxes and other information overlaid? How to handle operations not supported by Triton Inference Server? When to start smart recording and when to stop smart recording depend on your design. 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. There are deepstream-app sample codes to show how to implement smart recording with multiple streams. because when I try deepstream-app with smart-recording configured for 1 source, the behaviour is perfect. How can I construct the DeepStream GStreamer pipeline? Following are the default values of configuration parameters: Following fields can be used under [sourceX] groups to configure these parameters. There are more than 20 plugins that are hardware accelerated for various tasks. That means smart record Start/Stop events are generated every 10 seconds through local events. There are several built-in reference trackers in the SDK, ranging from high performance to high accuracy. 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. What types of input streams does DeepStream 6.0 support? If current time is t1, content from t1 - startTime to t1 + duration will be saved to file. Add this bin after the audio/video parser element in the pipeline. DeepStream provides building blocks in the form of GStreamer plugins that can be used to construct an efficient video analytic pipeline. Why do I observe: A lot of buffers are being dropped. GstBin which is the recordbin of NvDsSRContext must be added to the pipeline. The registry failed to perform an operation and reported an error message. At the bottom are the different hardware engines that are utilized throughout the application. Learn More. 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. Configure DeepStream application to produce events, 4. Yes, on both accounts. This recording happens in parallel to the inference pipeline running over the feed. How to fix cannot allocate memory in static TLS block error? The containers are available on NGC, NVIDIA GPU cloud registry. Once the frames are in the memory, they are sent for decoding using the NVDEC accelerator. What are the recommended values for. What is the recipe for creating my own Docker image? 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. Smart Record Deepstream Deepstream Version: 5.1 documentation . London, awarded World book of records Why is a Gst-nvegltransform plugin required on a Jetson platform upstream from Gst-nveglglessink? When expanded it provides a list of search options that will switch the search inputs to match the current selection. Based on the event, these cached frames are encapsulated under the chosen container to generate the recorded video. How do I configure the pipeline to get NTP timestamps? In existing deepstream-test5-app only RTSP sources are enabled for smart record. Powered by Discourse, best viewed with JavaScript enabled. Please make sure you understand how to migrate your DeepStream 5.1 custom models to DeepStream 6.0 before you start. Container Contents How to tune GPU memory for Tensorflow models? smart-rec-dir-path= Duration of recording. Observing video and/or audio stutter (low framerate), 2. The pre-processing can be image dewarping or color space conversion. Welcome to the DeepStream Documentation DeepStream 6.0 Release What is the official DeepStream Docker image and where do I get it? When running live camera streams even for few or single stream, also output looks jittery? DeepStream applications can be orchestrated on the edge using Kubernetes on GPU. How can I verify that CUDA was installed correctly? 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 The first frame in the cache may not be an Iframe, so, some frames from the cache are dropped to fulfil this condition. My DeepStream performance is lower than expected. Does DeepStream Support 10 Bit Video streams? It expects encoded frames which will be muxed and saved to the file. DeepStream abstracts these libraries in DeepStream plugins, making it easy for developers to build video analytic pipelines without having to learn all the individual libraries. recordbin of NvDsSRContext is smart record bin which must be added to the pipeline. In this documentation, we will go through Host Kafka server, producing events to Kafka Cluster from AGX Xavier during DeepStream runtime, and For sending metadata to the cloud, DeepStream uses Gst-nvmsgconv and Gst-nvmsgbroker plugin. Why does my image look distorted if I wrap my cudaMalloced memory into NvBufSurface and provide to NvBufSurfTransform? Copyright 2020-2021, NVIDIA. 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. How to enable TensorRT optimization for Tensorflow and ONNX models? By default, Smart_Record is the prefix in case this field is not set. How can I change the location of the registry logs? Whats the throughput of H.264 and H.265 decode on dGPU (Tesla)? What is maximum duration of data I can cache as history for smart record?

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