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What is NVIDIA DeepStream SDK?

NVIDIA's DeepStream SDK is a powerful toolkit designed for streaming analytics, utilizing GStreamer to enable AI-enhanced processing across a multitude of sensors that encompass video, audio, and image data. This SDK allows developers to build sophisticated stream-processing pipelines that effectively incorporate neural networks along with advanced features such as tracking, video encoding and decoding, and rendering, thus facilitating real-time analysis of varied data formats. DeepStream is integral to NVIDIA Metropolis, a holistic platform that transforms pixel and sensor data into actionable insights. It offers a flexible and responsive environment tailored to a range of industries, supporting numerous programming languages including C/C++, Python, and an intuitive UI via Graph Composer. By facilitating immediate understanding of intricate, multi-modal sensor information at the edge, it not only boosts operational efficiency but also provides managed AI services deployable in cloud-native containers orchestrated by Kubernetes. As a result, with the growing dependence on AI for informed decision-making, the functionalities of DeepStream become increasingly critical in maximizing the potential of sensor data. Moreover, the continuous evolution of the SDK ensures that it remains at the forefront of technological advancements, adapting to the changing needs of various sectors.

What is C-Radiant?

C-Radiant operates as a supplementary module that significantly upgrades Aechelon Technology's pC-Nova image generator by incorporating advanced physics-based spectral rendering, autogain capabilities, and a variety of noise and sensor special effects, all through cutting-edge shader technology, which removes the need for hardware post-processing. When paired with Aechelon Technology's C-Genesis database framework and toolkit, C-Radiant allows for a cohesive runtime and database system that can accommodate both existing and future sensors. The material descriptions within the database cover a comprehensive spectrum rather than just a single band, which supports the generation of synchronized multi-sensor outputs, including Night Vision Goggles (NVG), Forward Looking InfraRed (FLIR), and Radar systems. This novel method ensures impeccable correlation at the pixel level across all sensors and the Out-The-Window view, functioning smoothly at a refresh rate of 60Hz. Consequently, users can anticipate a significant improvement in visual fidelity and realism in their imaging endeavors, making it a valuable asset for various applications. This combination of features not only enhances performance but also broadens the potential for innovative developments in imaging technologies.

Media

Media

Integrations Supported

C
C++
Helm
Kubernetes
NVIDIA Jetson
NVIDIA Metropolis
NVIDIA TensorRT
NVIDIA Triton Inference Server
PyTorch
Python
TensorFlow

Integrations Supported

C
C++
Helm
Kubernetes
NVIDIA Jetson
NVIDIA Metropolis
NVIDIA TensorRT
NVIDIA Triton Inference Server
PyTorch
Python
TensorFlow

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

developer.nvidia.com/deepstream-sdk

Company Facts

Organization Name

Aechelon Technology

Date Founded

1998

Company Location

United States

Company Website

www.aechelon.com/test/cradiant.php

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

Categories and Features

Simulation

1D Simulation
3D Modeling
3D Simulation
Agent-Based Modeling
Continuous Modeling
Design Analysis
Direct Manipulation
Discrete Event Modeling
Dynamic Modeling
Graphical Modeling
Industry Specific Database
Monte Carlo Simulation
Motion Modeling
Presentation Tools
Stochastic Modeling
Turbulence Modeling

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