Audience
Anyone requiring an open-source neural network framework for neural network processes and image recognition
About Darknet
Darknet is an open-source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation. You can find the source on GitHub or you can read more about what Darknet can do. Darknet is easy to install with only two optional dependencies, OpenCV if you want a wider variety of supported image types, and CUDA if you want GPU computation. Darknet on the CPU is fast but it's like 500 times faster on GPU! You'll have to have an Nvidia GPU and you'll have to install CUDA. By default, Darknet uses stb_image.h for image loading. If you want more support for weird formats (like CMYK jpegs, thanks Obama) you can use OpenCV instead! OpenCV also allows you to view images and detections without having to save them to disk. Classify images with popular models like ResNet and ResNeXt. Recurrent neural networks are all the rage for time-series data and NLP.
Other Popular Alternatives & Related Software
Torch
Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. The goal of Torch is to have maximum flexibility and speed in building your scientific algorithms while making the process extremely simple. Torch comes with a large ecosystem of community-driven packages in machine learning, computer vision, signal processing, parallel processing, image, video, audio and networking among others, and builds on top of the Lua community. At the heart of Torch are the popular neural network and optimization libraries which are simple to use, while having maximum flexibility in implementing complex neural network topologies. You can build arbitrary graphs of neural networks, and parallelize them over CPUs and GPUs in an efficient manner.
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Chainer
A powerful, flexible, and intuitive framework for neural networks. Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort. Chainer supports various network architectures including feed-forward nets, convnets, recurrent nets and recursive nets. It also supports per-batch architectures. Forward computation can include any control flow statements of Python without lacking the ability of backpropagation. It makes code intuitive and easy to debug. Comes with ChainerRLA, a library that implements various state-of-the-art deep reinforcement algorithms. Also, with ChainerCVA, a collection of tools to train and run neural networks for computer vision tasks. Chainer supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort.
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OpenCV
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. OpenCV was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in commercial products. Being a BSD-licensed product, OpenCV makes it easy for businesses to utilize and modify the code. The library has more than 2500 optimized algorithms, which includes a comprehensive set of both classic and state-of-the-art computer vision and machine learning algorithms. These algorithms can be used to detect and recognize faces, identify objects, classify human actions in videos, track camera movements, track moving objects, extract 3D models of objects, produce 3D point clouds from stereo cameras, and stitch images together to produce a high-resolution image of an entire scene, find similar images from an image database, remove red eyes from images taken using flash, follow eye movements, recognize scenery, etc.
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DarkOwl
We are the industry’s leading provider of darknet data, offering the largest commercially available database of darknet content in the world. DarkOwl offers a suite of data products designed to meet the needs of business looking to quantify risk and understand their threat attack surface by leveraging darknet intelligence. DarkOwl Vision UI and API products make our data easy to access in your browser, native environment or customer-facing platform. Darknet data is a proven driver of business success for use cases spanning beyond threat intelligence and investigations. DarkOwl API products allow cyber insurance underwriters and third party risk assessors to utilize discrete data points from the darknet and incorporate them into scalable business models that accelerate revenue growth.
Learn more about DarkOwl
Integrations
No integrations listed.
Company Information
Darknet
pjreddie.com/darknet/
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Product Details
Platforms Supported
Mac
Linux
Training
Documentation
Support
Online
Darknet Frequently Asked Questions
Q: What kinds of users and organization types does Darknet work with?
Darknet works with these users and organization types: Mid Size Business, Small Business, Enterprise, Freelance, Nonprofit, Government, and Startup.
Q: What languages does Darknet support in their product?
Darknet supports these languages: English.
Q: What kind of support options does Darknet offer?
Darknet offers support via online.
Q: What type of training does Darknet provide?
Darknet provides training in the form of documentation.
