NVIDIA Metropolis

NVIDIA Metropolis features GPU-accelerated SDKs and developer tools that help developers optimally build, deploy, and scale AI-enabled video analytics and IoT applications–from the edge to the cloud.


NVIDIA Metropolis includes a hosts of SDK and developer tools

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Explore the benefits

Faster builds

Use and customize high-performance, pretrained models, or your own models, to streamline deploying AI applications across a range of industries. Jump-start application development by building off modular microservices and reference applications.

Lower cost

Powerful SDKs including NVIDIA TensorRT?, DeepStream, and TAO Toolkit reduce overall solution cost by maximizing inference throughput and optimizing hardware usage on NVIDIA platforms and infrastructure.

Flexible deployments

Manage and scale AI deployments securely with Fleet Command? and deploy with flexibility using cloud-native Metropolis Microservices and containerized apps with options for on-premise, cloud, or hybrid deployments.

Powerful tools for
AI-enabled video analytics

The Metropolis suite of SDKs provides a variety of starting points to accelerate and optimize any aspect of AI application development and deployment.



NVIDIA Omniverse? Replicator

Generate physically accurate 3D synthetic data at scale, or build your own synthetic data tools and frameworks. Bootstrap perception AI model training and achieve accurate Sim2Real performance without having to manually curate and label real-world data.


Learn more
 NVIDIA Omniverse replicator generates 3D synthetic data

Pretrained models

Eliminate the time-consuming process of building models from scratch. Choose from over 100+ permutations of highly accurate models and generic neural network architectures or start with our task-based models to recognize human actions and poses, detect people in crowded spaces, classify vehicles and license plates, and much more.


Learn more Try pretrained models with Jupyter Notebook

TAO Toolkit

The Train, Adapt and Optimize (TAO) Toolkit is a low-code AI model development solution that lets you use the power of transfer learning to fine-tune NVIDIA pretrained models with your own data and optimize for inference–without AI expertise or a large training dataset.


Learn more Try TAO on LaunchPad
Leverage NVIDIA TAO Toolkit to train, adapt, and optimize AI model development
Logos of popular AI model frameworks

Many AI model frameworks

Create your AI models and applications on these popular NVIDIA-supported AI frameworks. Integrate any existing AI model into the Metropolis workflow and easily customize existing models in TensorFlow, PyTorch, and more by easily converting to TAO.


Learn more

TensorRT

This SDK for high-performance deep learning inference includes an inference optimizer and runtime that delivers low latency and high throughput, both on edge devices and within the cloud. TensorRT is supported on all popular frameworks, including TensorFlow and PyTorch. Powering NVIDIA solutions such as JetPack? and DeepStream, TensorRT is a gateway to accelerated inferencing.


Learn more
TensorRT SDK for high-performance deep learning inference
NVIDIA DeepStream SDK - a complete streaming analytics toolkit

DeepStream SDK

NVIDIA DeepStream SDK is a complete streaming analytics toolkit based on GStreamer for AI-based multi-sensor processing, video, audio, and image understanding. It’s ideal for vision AI developers, software partners, startups, and OEMs building IVA apps and services.


Learn more Try DeepStream on LaunchPad

Triton Inference Server

The NVIDIA Triton? open-source, multi-framework inference serves software to deploy, run, and scale AI models in production on both GPUs and CPUs. It supports all major frameworks, including TensorFlow and Pytorch, and maximizes inference throughput on any platform.


Learn more
Triton Inference Server maximizes inference throughput on any platform
Video Storage Toolkit (VST) manages and stores footage for large volumes of video cameras

Video Storage Toolkit (VST)

Easily manage and store footage for large volumes of video cameras with hardware-accelerated video decoding, streaming, and storage. Get started quickly with the included web-based user interface and take advantage of VST flexibility through intuitive REST APIs. It’s available for NVIDIA Jetson Xavier? and Orin? devices.


Learn more

Metropolis Microservices

This suite of cloud-native microservices and reference applications fast-tracks development and deployment of vision AI applications. Unlock business insights for a wide range of spaces, ranging from roadways to airports to retail stores, in significantly shortened development cycles.


Learn more
Use Metropolis Microservices to develop and deploy vision AI apps
 NVIDIA CUDA-X libraries help with pre-processing and model performance

CUDA-X libraries

Take advantage of low-level libraries and primitives for computer vision and more that can help with pre-processing and model performance. NVIDIA? CUDA-X?, built on top of NVIDIA CUDA?, is a collection of libraries, tools, and technologies that deliver dramatically higher performance in compute-intensive algorithms spanning complex math, deep learning, and image processing.


Fleet Command

Streamline the provisioning and deployment of systems and AI applications at the edge with NVIDIA Fleet Command. A managed platform for container orchestration, it simplifies the management of distributed computing environments with the scale and resiliency of the cloud, turning every site into a secure, intelligent location.


Learn more Experience Fleet Command on LaunchPad
NVIDIA Fleet Command. deploys vision AI apps at the edge
Video Storage Toolkit (VST) manages and stores footage for large volumes of video cameras

Cloud containers

Combine NVIDIA SDKs to create containerized applications easily with Docker, Kubernetes, and GPU Operators to deploy cloud-native solutions on Jetson, x86, and dGPU.


Learn more

Generate – Synthetic data generation

NVIDIA Omniverse? Replicator

Generate physically accurate 3D synthetic data at scale, or build your own synthetic data tools and frameworks. Bootstrap perception AI model training and achieve accurate Sim2Real performance without having to manually curate and label real-world data.


Learn more
 NVIDIA Omniverse replicator generates 3D synthetic data

Train – Application-specific model customization

Pretrained models

Eliminate the time-consuming process of building models from scratch. Choose from over 100+ permutations of highly accurate models and generic neural network architectures or start with our task-based models to recognize human actions and poses, detect people in crowded spaces, classify vehicles and license plates, and much more.


Learn more Try pretrained models with Jupyter Notebook

TAO Toolkit

The Train, Adapt and Optimize (TAO) Toolkit is a low-code AI model development solution that lets you use the power of transfer learning to fine-tune NVIDIA pretrained models with your own data and optimize for inference–without AI expertise or a large training dataset.


Learn more Try TAO on LaunchPad
Leverage NVIDIA TAO Toolkit to train, adapt, and optimize AI model development
Logos of popular AI model frameworks

Many AI model frameworks

Create your AI models and applications on these popular NVIDIA-supported AI frameworks. Integrate any existing AI model into the Metropolis workflow and easily customize existing models in TensorFlow, PyTorch, and more by easily converting to TAO.


Learn more

Build – Powerful AI applications

TensorRT

This SDK for high-performance deep learning inference includes an inference optimizer and runtime that delivers low latency and high throughput, both on edge devices and within the cloud. TensorRT is supported on all popular frameworks, including TensorFlow and PyTorch. Powering NVIDIA solutions such as JetPack? and DeepStream, TensorRT is a gateway to accelerated inferencing.


Learn more
TensorRT SDK for high-performance deep learning inference
NVIDIA DeepStream SDK - a complete streaming analytics toolkit

DeepStream SDK

NVIDIA DeepStream SDK is a complete streaming analytics toolkit based on GStreamer for AI-based multi-sensor processing, video, audio, and image understanding. It’s ideal for vision AI developers, software partners, startups, and OEMs building IVA apps and services.


Learn more Try DeepStream on LaunchPad

Triton Inference Server

The NVIDIA Triton? open-source, multi-framework inference serves software to deploy, run, and scale AI models in production on both GPUs and CPUs. It supports all major frameworks, including TensorFlow and Pytorch, and maximizes inference throughput on any platform.


Learn more
Triton Inference Server maximizes inference throughput on any platform
Video Storage Toolkit (VST) manages and stores footage for large volumes of video cameras

Video Storage Toolkit (VST)

Easily manage and store footage for large volumes of video cameras with hardware-accelerated video decoding, streaming, and storage. Get started quickly with the included web-based user interface and take advantage of VST flexibility through intuitive REST APIs. It’s available for NVIDIA Jetson Xavier? and Orin? devices.


Learn more

Metropolis Microservices

This suite of cloud-native microservices and reference applications fast-tracks development and deployment of vision AI applications. Unlock business insights for a wide range of spaces, ranging from roadways to airports to retail stores, in significantly shortened development cycles.


Learn more
Use Metropolis Microservices to develop and deploy vision AI apps
 NVIDIA CUDA-X libraries help with pre-processing and model performance

CUDA-X libraries

Take advantage of low-level libraries and primitives for computer vision and more that can help with pre-processing and model performance. NVIDIA? CUDA-X?, built on top of NVIDIA CUDA?, is a collection of libraries, tools, and technologies that deliver dramatically higher performance in compute-intensive algorithms spanning complex math, deep learning, and image processing.


Deploy – Application management and scaling

Fleet Command

Streamline the provisioning and deployment of systems and AI applications at the edge with NVIDIA Fleet Command. A managed platform for container orchestration, it simplifies the management of distributed computing environments with the scale and resiliency of the cloud, turning every site into a secure, intelligent location.


Learn more Experience Fleet Command on LaunchPad
NVIDIA Fleet Command. deploys vision AI apps at the edge
Video Storage Toolkit (VST) manages and stores footage for large volumes of video cameras

Cloud containers

Combine NVIDIA SDKs to create containerized applications easily with Docker, Kubernetes, and GPU Operators to deploy cloud-native solutions on Jetson, x86, and dGPU.


Learn more

Get started with sample applications

Use TAO and Deepstream for action recognition app

Action recognition

Learn how to develop and deploy a no-code action recognition application using TAO and DeepStream.

 Integrate TAO with DeepStream for face mask detection

Face mask detection

Integrate TAO with DeepStream for a 10X reduction in development time when creating a real-time face-detection edge application.

Use TAO toolkit to optimize pose estimation

Pose estimation

Learn how to create a gesture recognition application with robot interactions. Also, train and optimize a 2D pose estimation model with NVIDIA TAO Toolkit.

Use TAO with Deepstream for number plate detection

Number plate detection

Learn how to combine TAO with DeepStream for a license plate detection and understanding app.

Explore NVIDIA GTC talks on-demand