deepstream smart record

What are the recommended values for. smart-rec-interval= MP4 and MKV containers are supported. How can I run the DeepStream sample application in debug mode? Why does the RTSP source used in gst-launch pipeline through uridecodebin show blank screen followed by the error -. How can I interpret frames per second (FPS) display information on console? Can users set different model repos when running multiple Triton models in single process? 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. Ive configured smart-record=2 as the document said, using local event to start or end video-recording. Issue Type( questions). deepstream-testsr is to show the usage of smart recording interfaces. kafka_2.13-2.8.0/config/server.properties, configs/test5_dec_infer-resnet_tracker_sgie_tiled_display_int8.txt, #Type - 1=FakeSink 2=EglSink 3=File 4=UDPSink 5=nvoverlaysink 6=MsgConvBroker, #(0): PAYLOAD_DEEPSTREAM - Deepstream schema payload, #(1): PAYLOAD_DEEPSTREAM_MINIMAL - Deepstream schema payload minimal, #(257): PAYLOAD_CUSTOM - Custom schema payload, #msg-broker-config=../../deepstream-test4/cfg_kafka.txt, # do a dummy poll to retrieve some message, 'HWY_20_AND_LOCUST__EBA__4_11_2018_4_59_59_508_AM_UTC-07_00', 'Vehicle Detection and License Plate Recognition', "HWY_20_AND_LOCUST__EBA__4_11_2018_4_59_59_508_AM_UTC-07_00", test5_dec_infer-resnet_tracker_sgie_tiled_display_int8.txt, #Type - 1=CameraV4L2 2=URI 3=MultiURI 4=RTSP, # smart record specific fields, valid only for source type=4, # 0 = disable, 1 = through cloud events, 2 = through cloud + local events. What is the official DeepStream Docker image and where do I get it? Refer to the deepstream-testsr sample application for more details on usage. Regarding git source code compiling in compile_stage, Is it possible to compile source from HTTP archives? DeepStream builds on top of several NVIDIA libraries from the CUDA-X stack such as CUDA, TensorRT, NVIDIA Triton Inference server and multimedia libraries. An example of each: deepstream smart record. Typeerror hoverintent uncaught typeerror object object method jobs I want to Hire I want to Work. 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. The deepstream-test3 shows how to add multiple video sources and then finally test4 will show how to IoT services using the message broker plugin. Why am I getting following waring when running deepstream app for first time? , awarded WBR. How to extend this to work with multiple sources? There is an option to configure a tracker. There are two ways in which smart record events can be generated - either through local events or through cloud messages. 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. With DeepStream you can trial our platform for free for 14-days, no commitment required. Does smart record module work with local video streams? In existing deepstream-test5-app only RTSP sources are enabled for smart record. Optimum memory management with zero-memory copy between plugins and the use of various accelerators ensure the highest performance. What trackers are included in DeepStream and which one should I choose for my application? See the C/C++ Sample Apps Source Details and Python Sample Apps and Bindings Source Details sections to learn more about the available apps. What is the difference between batch-size of nvstreammux and nvinfer? Does Gst-nvinferserver support Triton multiple instance groups? Are multiple parallel records on same source supported? You may use other devices (e.g. '/usr/lib/aarch64-linux-gnu/gstreamer-1.0/libgstlibav.so': # Configure this group to enable cloud message consumer. #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. To get started, developers can use the provided reference applications. How do I obtain individual sources after batched inferencing/processing? 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. . 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. 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. After decoding, there is an optional image pre-processing step where the input image can be pre-processed before inference. What is the difference between batch-size of nvstreammux and nvinfer? How can I construct the DeepStream GStreamer pipeline? During container builder installing graphs, sometimes there are unexpected errors happening while downloading manifests or extensions from registry. I started the record with a set duration. How can I display graphical output remotely over VNC? The performance benchmark is also run using this application. Prefix of file name for generated video. Smart Video Record DeepStream 6.1.1 Release documentation These 4 starter applications are available in both native C/C++ as well as in Python. Call NvDsSRDestroy() to free resources allocated by this function. 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. If you set smart-record=2, this will enable smart record through cloud messages as well as local events with default configurations. Gst-nvvideoconvert plugin can perform color format conversion on the frame. Native TensorRT inference is performed using Gst-nvinfer plugin and inference using Triton is done using Gst-nvinferserver plugin. For example, the record starts when theres an object being detected in the visual field. And once it happens, container builder may return errors again and again. DeepStream supports application development in C/C++ and in Python through the Python bindings. smart-rec-start-time= How can I verify that CUDA was installed correctly? Records are the main building blocks of deepstream's data-sync capabilities. The containers are available on NGC, NVIDIA GPU cloud registry. Why does the deepstream-nvof-test application show the error message Device Does NOT support Optical Flow Functionality if run with NVIDIA Tesla P4 or NVIDIA Jetson Nano, Jetson TX2, or Jetson TX1? Path of directory to save the recorded file. What is the approximate memory utilization for 1080p streams on dGPU? In existing deepstream-test5-app only RTSP sources are enabled for smart record. The DeepStream reference application is a GStreamer based solution and consists of set of GStreamer plugins encapsulating low-level APIs to form a complete graph. What are different Memory transformations supported on Jetson and dGPU? What is the official DeepStream Docker image and where do I get it? The pre-processing can be image dewarping or color space conversion. DeepStream 5.1 Produce cloud-to-device event messages, 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), Custom Model - Triton Inference Server Configurations, Custom Model - Custom Parser - Yolov2-coco, Custom Model - Custom Parser - Tiny Yolov2, Custom Model - Custom Parser - EfficientDet, Custom Model - Sample Custom Parser - Resnet - Frcnn - Yolov3 - SSD, Custom Model - Sample Custom Parser - SSD, Custom Model - Sample Custom Parser - FasterRCNN, Custom Model - Sample Custom Parser - Yolov4. 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. recordbin of NvDsSRContext is smart record bin which must be added to the pipeline. What is maximum duration of data I can cache as history for smart record? Lets go back to AGX Xavier for next step. What if I dont set default duration for smart record? How can I interpret frames per second (FPS) display information on console? Can Gst-nvinferserver support models across processes or containers? 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. Whats the throughput of H.264 and H.265 decode on dGPU (Tesla)? Edge AI device (AGX Xavier) is used for this demonstration. This is the time interval in seconds for SR start / stop events generation. Hardware Platform (Jetson / CPU) How can I specify RTSP streaming of DeepStream output? smart-rec-dir-path= In existing deepstream-test5-app only RTSP sources are enabled for smart record. In smart record, encoded frames are cached to save on CPU memory. Can Jetson platform support the same features as dGPU for Triton plugin? The message format is as follows: Receiving and processing such messages from the cloud is demonstrated in the deepstream-test5 sample application. This means, the recording cannot be started until we have an Iframe. Smart-rec-container=<0/1> What types of input streams does DeepStream 6.2 support? Can I stop it before that duration ends? How does secondary GIE crop and resize objects? How to find out the maximum number of streams supported on given platform? They will take video from a file, decode, batch and then do object detection and then finally render the boxes on the screen. My DeepStream performance is lower than expected. This module provides the following APIs. Changes are persisted and synced across all connected devices in milliseconds. Can Gst-nvinferserver support inference on multiple GPUs? Smart video record is used for event (local or cloud) based recording of original data feed. Using records Records are requested using client.record.getRecord (name). The source code for this application is available in /opt/nvidia/deepstream/deepstream-6.0/sources/apps/sample_apps/deepstream-app. How to fix cannot allocate memory in static TLS block error? deepstream smart record. This function starts writing the cached audio/video data to a file. What are the sample pipelines for nvstreamdemux?

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