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Description

Darknet is a neural network framework that is open-source, developed using C and CUDA. Known for its speed and simplicity in installation, it accommodates both CPU and GPU processing. The source code is available on GitHub, where you can also explore its capabilities further. The installation process is straightforward, requiring only two optional dependencies: OpenCV for enhanced image format support and CUDA for GPU acceleration. While Darknet performs efficiently on CPUs, it boasts a performance increase of approximately 500 times when running on a GPU! To leverage this speed, you'll need an Nvidia GPU alongside the CUDA installation. By default, Darknet utilizes stb_image.h for loading images, but for those seeking compatibility with more obscure formats like CMYK jpegs, OpenCV can be employed. Additionally, OpenCV provides the functionality to visualize images and detections in real-time without needing to save them. Darknet supports the classification of images using well-known models such as ResNet and ResNeXt, and it has become quite popular for employing recurrent neural networks in applications related to time-series data and natural language processing. Whether you're a seasoned developer or a newcomer, Darknet offers an accessible way to implement advanced neural network solutions.

Description

QikkDB is a high-performance, GPU-accelerated columnar database designed to excel in complex polygon computations and large-scale data analytics. If you're managing billions of data points and require immediate insights, qikkDB is the solution you need. It is compatible with both Windows and Linux operating systems, ensuring flexibility for developers. The project employs Google Tests for its testing framework, featuring hundreds of unit tests alongside numerous integration tests to maintain robust quality. For those developing on Windows, it is advisable to use Microsoft Visual Studio 2019, with essential dependencies that include at least CUDA version 10.2, CMake 3.15 or a more recent version, vcpkg, and Boost libraries. Meanwhile, Linux developers will also require a minimum of CUDA version 10.2, CMake 3.15 or newer, and Boost for optimal operation. This software is distributed under the Apache License, Version 2.0, allowing for a wide range of usage. To simplify the installation process, users can opt for either an installation script or a Dockerfile to get qikkDB up and running seamlessly. Additionally, this versatility makes it an appealing choice for various development environments.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS Marketplace No 

Integrations

AWS Marketplace Yes 

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

Deployment

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

Customer Support

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

Customer Support

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

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Darknet

Website

pjreddie.com/darknet/

Vendor Details

Company Name

qikkDB

Website

github.com/qikkDB

Product Features

Product Features

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