Get Started With the NVIDIA DeepStream SDK
Overview |
NVIDIA DeepStream is a powerful SDK that lets you use GPU-accelerated technology to develop end-to-end streaming vision AI pipelines and agents powered by generative AI. The latest release, DeepStream 8, is packed with innovative features to accelerate the development of your next-generation applications. |
Release Highlights |
DeepStream 8.0 Highlights:
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Containers |
DeepStream is available in three different flavors of containers:
All Dockerfiles are also available on GitHub. For full details, check the new NGC Collection page. |
Download DeepStream SDK
DeepStream 7.1 applications are fully compatible with DeepStream 8.0. Please read the migration guide for more information.
Python Bindings
The Python bindings source code and pre-built wheels are now available on GitHub.
Introduction to DeepStream SDK
Quick Start Guide
Get step-by-step instructions for building vision AI pipelines using DeepStream and Jetson or discrete GPUs.
Get Started
Inference Builder
Learn how to use the DeepStream low-code inference builder to quickly turn model ideas into standalone applications or deployable microservices.
Watch the Video
Multi-Camera Tracking
Learn how to add multi-view 3D tracking to your DeepStream pipelines.
Learn More
Get Started
Find everything you need to start developing your vision AI applications with DeepStream, including documentation, tutorials, and reference applications.
Getting Started with Python
Get Started Python Application
GitHub Repository Compile and Install
Python Bindings Python Sample
Applications
Getting Started with Inference Builder
Learn how to build DeepStream apps with a declarative approach using DeepStream Inference Builder.
Get Started
Additional Resources
Technical Blogs
- BuildReal-Time Visual Inspection Pipelines With NVIDIA TAO 6 and DeepStream 8
- Mitigating Visual Perception Occlusions Using Single-View 3D Tracking in NVIDIA DeepStream
- State-of-the-Art Real-Time Multi-Object Trackers With NVIDIA DeepStream SDK 6.2
- Building an End-to-End Retail Analytics Application With NVIDIA DeepStream and NVIDIA TAO Toolkit
- Applying Inference Over Specific Frame Regions With NVIDIA DeepStream
- Creating a Real-Time License Plate Detection and Recognition App
- See All DeepStream Technical Blogs
Webinars and GTC
- GTC 2024: The Vision-AI Revolution Powered by DeepStream
- GTC 2024: Streamed Video Processing for Cloud-Scale Vision AI Services (Presented by Netflix) )
- GTC 2023: An Intro into NVIDIA DeepStream and AI-Streaming Software Tools
- GTC 2023: Advancing AI Applications With Custom GPU-Powered Plugins for NVIDIA DeepStream
- GTC 2023: Next-Generation AI for Improving Building Security and Safety
- How OneCup AI Created Betsy, The AI Ranch HandD: A Developer Story
- Create Intelligent Places Using NVIDIA Pretrained Vision Models and DeepStream SDK
- Integrating NVIDIA DeepStream With AWS IoT Greengrass V2 and Sagemaker: Introduction to Amazon Lookout for Vision on Edge (2022 - Amazon Web Services)
Forum & FAQ
Ethical AI |
NVIDIA platforms and application frameworks enable developers to build a wide array of AI applications. Consider potential algorithmic bias when choosing or creating the models being deployed. Also, work with the model’s developer to ensure that it meets the requirements for the relevant industry and use case; that the necessary instruction and documentation are provided to understand error rates, confidence intervals, and results; and that the model is being used under the conditions and in the manner intended. |