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features
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support

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Description

NVIDIA's DeepStream SDK serves as a robust toolkit for streaming analytics, leveraging GStreamer to facilitate AI-driven processing across various sensors, including video, audio, and image data. It empowers developers to craft intricate stream-processing pipelines that seamlessly integrate neural networks alongside advanced functionalities like tracking, video encoding and decoding, as well as rendering, thereby enabling real-time analysis of diverse data formats. DeepStream plays a crucial role within NVIDIA Metropolis, a comprehensive platform aimed at converting pixel and sensor information into practical insights. This SDK presents a versatile and dynamic environment catered to multiple sectors, offering support for an array of programming languages such as C/C++, Python, and an easy-to-use UI through Graph Composer. By enabling real-time comprehension of complex, multi-modal sensor information at the edge, it enhances operational efficiency while also providing managed AI services that can be deployed in cloud-native containers managed by Kubernetes. As industries increasingly rely on AI for decision-making, DeepStream's capabilities become even more vital in unlocking the value embedded within sensor data.

Description

The Qualcomm Cloud AI SDK serves as a robust software suite aimed at enhancing the performance of trained deep learning models for efficient inference on Qualcomm Cloud AI 100 accelerators. It accommodates a diverse array of AI frameworks like TensorFlow, PyTorch, and ONNX, which empowers developers to compile, optimize, and execute models with ease. Offering tools for onboarding, fine-tuning, and deploying models, the SDK streamlines the entire process from preparation to production rollout. In addition, it includes valuable resources such as model recipes, tutorials, and sample code to support developers in speeding up their AI projects. This ensures a seamless integration with existing infrastructures, promoting scalable and efficient AI inference solutions within cloud settings. By utilizing the Cloud AI SDK, developers are positioned to significantly boost the performance and effectiveness of their AI-driven applications, ultimately leading to more innovative solutions in the field.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

PyTorch Yes 
TensorFlow Yes 
Airstack No 
Amazon Web Services (AWS) No 
C Yes 
C++ Yes 
Cirrascale No 
Docker No 
EndoAim No 
GIGABYTE Rack Server No 
HPE Apollo No 
Helm Yes 
Hugging Face No 
Kubernetes Yes 
NVIDIA Jetson Yes 
NVIDIA Metropolis Yes 
NVIDIA TensorRT Yes 
NVIDIA Triton Inference Server Yes 
ONNX No 
Python Yes 

Integrations

PyTorch Yes 
TensorFlow Yes 
Airstack Yes 
Amazon Web Services (AWS) Yes 
C No 
C++ No 
Cirrascale Yes 
Docker Yes 
EndoAim Yes 
GIGABYTE Rack Server Yes 
HPE Apollo Yes 
Helm No 
Hugging Face Yes 
Kubernetes No 
NVIDIA Jetson No 
NVIDIA Metropolis No 
NVIDIA TensorRT No 
NVIDIA Triton Inference Server No 
ONNX Yes 
Python No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/deepstream-sdk

Vendor Details

Company Name

Qualcomm

Website

www.qualcomm.com/developer/software/cloud-ai-sdk

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Product Features

Deep Learning

Convolutional Neural Networks No 
Document Classification No 
Image Segmentation No 
ML Algorithm Library No 
Model Training No 
Neural Network Modeling No 
Self-Learning No 
Visualization No 

Alternatives

Alternatives

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