Build and deploy AI-powered Intelligent Video Analytics apps and services. DeepStream offers a multi-platform scalable framework with TLS security to deploy on the edge and connect to any cloud.


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There are billions of cameras and sensors worldwide, capturing an abundance of data that can be used to generate business insights, unlock process efficiencies and improve revenue streams. Whether it’s at a traffic intersection to reduce vehicle congestion, health and safety monitoring at hospitals, surveying retail aisles for better customer satisfaction, sports analytics or at a manufacturing facility to detect component defects- every application demands reliable, real-time Intelligent Video Analytics (IVA).



Powerful & Flexible SDK

A unified SDK suitable for a multitude of use-cases across a broad set of industries.

Real-time Insights

Understand rich and multimodal sensor data at the edge.

Managed AI services

Deploy AI services in cloud native containers and orchestrate using Kubernetes.

Reduced TCO

Train with Transfer Learning Toolkit and use DeepStream to increase stream density.



NVIDIA’s DeepStream SDK delivers a complete streaming analytics toolkit for AI-based multi-sensor processing, video and image understanding.

DeepStream is for vision AI developers, software partners, startups and OEMs building IVA apps and services.


DeepStream is also an integral part of NVIDIA Metropolis, the platform for building end-to-end services and solutions that transform pixel and sensor data to actionable insights.

Achieving Higher Accuracy & Real-Time Performance


Deploy purpose-built models from TLT with DeepStream SDK to unlock greater end-to-end throughput.


Jetson Nano
Jetson Xavier NX
Jetson AGX Xavier
T4
Model Architecture
Inference Resolution
Precision
Model Accuracy
GPU (FPS)
GPU (FPS)
DLA1 (FPS)
DLA2 (FPS)
GPU (FPS)
DLA1 (FPS)
DLA2 (FPS)
GPU (FPS)
PeopleNet-ResNet34
960x544
FP16
84%
10
60
30
30
120
60
60
460
TrafficCamNet-ResNet18
960x544
INT8
83.5%
19*
180
90
90
420
120
120
1300
DashCamNet-ResNet18
960x544
INT8
80%
18*
180
90
90
390
120
120
1280
FaceDetect-IR-ResNet18
384x240
INT8
96%
95*
1080
570
570
1950
780
780
2160
Tabulated data is in FPS with 1080p input
* FP16 inference on Jetson Nano
Running on the DLAs for AGX Xavier and NX frees up GPU for other tasks

Why Use DeepStream SDK?


Seamless Development

  • Develop in C/C++ or Python
  • Built for scalability - one application for NVIDIA T4 and Jetson platforms
  • Highest throughput for object detection, image classification and semantic segmentation models
  • Deploy models in native DL frameworks such as Pytorch and TensorFlow for inference
  • IoT integration interface with Kafka, MQTT and AMQP
  • Turnkey integration with AWS IoT and Microsoft Azure IoT
  • Multi-GPU, multi-stream and batching support for high throughput inference




Managed IVA Apps & Services

  • Build cloud native applications with NVIDIA NGC containers
  • Deploy at scale and manage containerized apps with Kubernetes and Helm Charts
  • Connect edge to cloud securely with encrypted metadata and TLS authentication
  • Save on disk storage space, improve searchability and record anomalies with a smart recording event manager
  • Seamless Over-the-Air (OTA) update for the entire app or individual AI models from any cloud registry








End-to-End AI Solutions




Plug-ins & Sample Apps

  • 20+ sample apps in Python and C/C++ for quick reference and rapid prototyping
  • Object detection using using state of the art SSD, YOLO and FasterRCNN
  • Integrate OpenCV functions and libraries with DeepStream

DeepStream SDK Plug-ins


  • H.264 and H.265 video decoding
  • Stream aggregation and batching
  • TensorRT-based inferencing for detection, classification and segmentation
  • Object tracking reference implementation
  • On-screen display API for highlighting objects and text overlay
  • Frame rendering from multi-source into a 2D grid array
  • Accelerated X11/EGL-based rendering
  • Filtering based on Region of Interest (ROI)
  • JPEG decoding
  • Scaling, format conversion, and rotation
  • Dewarping for 360-degree camera input
  • Metadata generation and encoding
  • Messaging to cloud

Testimonials


Improving operational efficiency and reducing loss are key issues facing many retailers. Today’s large supermarkets have numerous in-store cameras, which can be used to mitigate these problems, but real-time video processing of so many streams can be a challenge. By leveraging NVIDIA T4 GPUs, DeepStream and TensorRT, Malong’s state-of-the-art Intelligent Video Analytics (IVA) solution achieves 3X higher throughput with industry-leading accuracy to help their retail customers significantly improve their business performance.


Malong Technologies Malong

Extracting actionable insights from a sea of data created by the world’s billions of cameras and sensors is a huge task, and maintaining a connection from these devices to the cloud for processing may be overly expensive or infeasible due to security, regulatory, or bandwidth restrictions. Microsoft Azure IoT Edge deploys applications and services built using DeepStream to edge devices, allowing organizations to process data locally to trigger alerts and take actions automatically and to upload to the cloud when needed. Combining Azure IoT Edge, NVIDIA DeepStream and Azure IoT Central brings device management, monitoring and custom business logic to millions of edge devices for real-time insights and easy deployment.

Microsoft Microsoft

As a leader in fulfillment and logistics management, SF Technology needed to track goods and vehicles across tens of thousands of locations. Every site requires detailed analytics around fleet management, loading times, and other operational activities. Using DeepStream and NVIDIA GPUs, they were able to increase the efficiency of AI Argus; an intelligent video analytics product that brings smarter video insights and can process 32 video streams simultaneously. The company is also looking at using next-generation GPUs, which is expected to increase the number of video streams processed.

SF Technology SFExpress

We are bringing AI and machine learning to the trade sector with a fleet of real-time analytics based products that help businesses secure the cash point area and carefully supervise store entry/exit to prevent loss of goods. By switching to a DeepStream-based solution running on Jetson Nano, we achieved 5X stream density increasing the platform efficiency, reducing hardware and installation costs.



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Frequently Asked Questions

DeepStream is a closed source SDK. Note that source for all reference applications and several plugins are available.

The DeepStream SDK can be used to build end-to-end AI-powered applications to analyze video and sensor data. Some popular use cases are: retail analytics, parking management, managing logistics, robotics, optical inspection and managing operations.

Yes, it is possible with the integration of Triton Inference server. Triton integration is an alpha feature and has few limitations for DeepStream SDK 5.0 developer preview. Triton supports TensorFlow, TensorFlow-TensorRT, PyTorch and ONNX on x86 and Tensorflow and TensorFlow-TensorRT on Jetson. More information can be found in the release notes.

To learn more about deploying TLT models with DeepStream, click here.

Latest Product News




Feature Explainer Blog

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Developer Tutorial

Learn how to deploy custom pre-trained models using DeepStream and Transfer Learning Toolkit.


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Free Online DLI Course

Learn how to use Jetson Nano and DeepStream to extract meaningful insights using IVA.


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Developer Projects

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Build High Performance IVA Apps & Services using DeepStream SDK


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