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Description

The VLFeat open source library offers a range of well-known algorithms focused on computer vision, particularly for tasks such as image comprehension and the extraction and matching of local features. Among its various algorithms are Fisher Vector, VLAD, SIFT, MSER, k-means, hierarchical k-means, the agglomerative information bottleneck, SLIC superpixels, quick shift superpixels, and large scale SVM training, among many others. Developed in C to ensure high performance and broad compatibility, it also has MATLAB interfaces that enhance user accessibility, complemented by thorough documentation. This library is compatible with operating systems including Windows, Mac OS X, and Linux, making it widely usable across different platforms. Additionally, MatConvNet serves as a MATLAB toolbox designed specifically for implementing Convolutional Neural Networks (CNNs) tailored for various computer vision applications. Known for its simplicity and efficiency, MatConvNet is capable of running and training cutting-edge CNNs, with numerous pre-trained models available for tasks such as image classification, segmentation, face detection, and text recognition. The combination of these tools provides a robust framework for researchers and developers in the field of computer vision.

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.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

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

Integrations

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

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

VLFeat

Country

United States

Website

www.vlfeat.org/matconvnet/

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/deepstream-sdk

Product Features

Deep Learning

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

Product Features

Deep Learning

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

Alternatives

Alternatives

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