Search Results for "deep" - Page 2
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Showing 55 open source projects for "deep"
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Neiki's Gallery
Vanilla JavaScript image gallery & lightbox
...Designed for both developers and end users, it supports responsive layouts, advanced lightbox features, touch and keyboard navigation, lazy loading, and seamless media handling including images and video. The library is modular and extensible, offering plugins, event hooks, and deep customization through JavaScript or HTML data attributes. It is optimized for performance, accessibility, and large-scale galleries while maintaining smooth animations and a modern visual style. -
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pH7 Social Dating CMS (pH7Builder)❤️
🚀 Professional Social Dating Web App Builder (formerly pH7CMS)
pH7Builder is a Professional, Free & Open Source PHP Social Dating Builder Software (primarily designed for developers ...). This Social Dating Web App is fully coded in object-oriented PHP (OOP) with the MVC pattern (Model-View-Controller). It is low resource-intensive, extremely powerful and highly secure. pH7Builder is included with over 42 native modules and is based on its homemade pH7 Framework which includes more than 52 packages To summarize, pH7Builder Social Dating Script... -
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MMDeploy
OpenMMLab Model Deployment Framework
MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. -
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django-sspanel
Diango shadowsocks
Shadowsocks panel developed with diango. Smart subscription system , support ss/clash/clash premium version. Deep integration with transit tunnels , convenient and fast construction of transit tunnels d7e4380-6532-* Backend supports common protocols. Registration adopts the invitation system to bid farewell to bad users. Unified and perfect background management interface. Perfect commodity purchase logic. Alipay face-to-face payment module. -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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pipeless
A computer vision framework to create and deploy apps in minutes
Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new... -
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Horovod
Distributed training framework for TensorFlow, Keras, PyTorch, etc.
Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. -
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KotlinDL
High-level Deep Learning Framework written in Kotlin
...This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning models in production environments. -
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Knet
Koç University deep learning framework
Knet.jl is a deep learning package implemented in Julia, so you should be able to run it on any machine that can run Julia. It has been extensively tested on Linux machines with NVIDIA GPUs and CUDA libraries, and it has been reported to work on OSX and Windows. If you would like to try it on your own computer, please follow the instructions on Installation. -
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hapi
The simple, secure framework developers trust
...Originally developed to handle Walmart’s Black Friday scale, hapi continues to be the proven choice for enterprise-grade backend needs. When you npm install @hapi/hapi, every single line of code you get has been verified. You never have to worry about some deep dependency being poorly maintained (or handed over to someone sketchy). hapi is the only leading node framework without any external code dependencies. None. hapi has been pushing the envelope on quality from day one. It was the first node framework to require and achieve 100% code coverage across every dependency – when everyone thought it was crazy. ... -
Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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deep-clean
When Gradle or the IDE let you down, just --nuke all them caches
A Kotlin script that nukes all build caches from Gradle/Android projects. Useful when Gradle or the IDE let you down. The script has been tested on macOS, but it is completely untested on Linux and Windows. KScript may not work at all on Windows! For this script to work, you need to have kotlin, script, and maven on your PATH. If you don't have all three commands on your PATH, then read on to the next section to install them. To make the script run, we'll first need to install all the... -
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graphql-api-koa
GraphQL execution and error handling middleware written from scratch
GraphQL execution and error handling middleware written from scratch for Koa. -
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Spring Boot Demo
A project for in-depth study and practical application of Spring Boot
This repository is a hands-on, “deep learning by doing” collection of Spring Boot demos that you can run and study module by module. It currently includes 66 planned integrations (with 55 completed) spanning monitoring, logging, templating, data access, caching, messaging, scheduling, search, security, and more. The master branch targets Spring Boot 2.1.0.RELEASE with a parent POM that centralizes common dependency versions; the older v-1.5.x branch is frozen and its contents are being migrated to master. ... -
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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ReconSpider
Most Advanced Open Source Intelligence (OSINT) Framework
ReconSpider is most Advanced Open Source Intelligence (OSINT) Framework for scanning IP Addresses, Emails, Websites, and Organizations and find out information from different sources. ReconSpider can be used by Infosec Researchers, Penetration Testers, Bug Hunters, and Cyber Crime Investigators to find deep information about their target. ReconSpider aggregate all the raw data, visualize it on a dashboard, and facilitate alerting and monitoring on the data. Recon Spider also combines the capabilities of Wave, Photon and Recon Dog to do a comprehensive enumeration of attack surfaces. Reconnaissance is a mission to obtain information by various detection methods, about the activities and resources of an enemy or potential enemy, or geographic characteristics of a particular area. ... -
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Gluon CV Toolkit
Gluon CV Toolkit
...The model zoo is the one-stop shopping center for many models you are expecting. GluonCV embraces a flexible development pattern while is super easy to optimize and deploy without retaining a heavyweight deep learning framework. -
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PyTorch SimCLR
PyTorch implementation of SimCLR: A Simple Framework
For quite some time now, we know about the benefits of transfer learning in Computer Vision (CV) applications. Nowadays, pre-trained Deep Convolution Neural Networks (DCNNs) are the first go-to pre-solutions to learn a new task. These large models are trained on huge supervised corpora, like the ImageNet. And most important, their features are known to adapt well to new problems. This is particularly interesting when annotated training data is scarce. In situations like this, we take the models’ pre-trained weights, append a new classifier layer on top of it, and retrain the network. ... -
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PyText
A natural language modeling framework based on PyTorch
PyText is a deep-learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapid experimentation and of serving models at scale. It achieves this by providing simple and extensible interfaces and abstractions for model components, and by using PyTorch’s capabilities of exporting models for inference via the optimized Caffe2 execution engine. -
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X-DeepLearning
An industrial deep learning framework for high-dimension sparse data
X-DeepLearning (XDL for short) is a complete set of deep optimization solutions for high-dimensional sparse data scenarios (such as advertising/recommendation/search, etc.). XDL version 1.2 has been released recently. Performance optimization for large batch/low concurrency scenarios, 50-100% performance improvement in such scenarios. Storage and communication optimization, parameters are automatically allocated globally without manual intervention, and requests are merged to completely eliminate computing/storage/communication hotspots of ps. ... -
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TheoremJS
A Math library for computation in JavaScript
...Even though we loose performances with BigNumber, our algorithms are well-engineered and ensure decent performances on every device. You can use TheoremJS for every project, ranging from doing your math homework to launching a rocket into deep space. (Ok, maybe if you're planning to launch a rocket into space, you might want to use other tools in addition to TheoremJS). -
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TenorSpace.js
Neural network 3D visualization framework
TensorSpace is a neural network 3D visualization framework built using TensorFlow.js, Three.js and Tween.js. TensorSpace provides Keras-like APIs to build deep learning layers, load pre-trained models, and generate a 3D visualization in the browser. From TensorSpace, it is intuitive to learn what the model structure is, how the model is trained and how the model predicts the results based on the intermediate information. After preprocessing the model, TensorSpace supports the visualization of pre-trained models from TensorFlow, Keras and TensorFlow.js. ... -
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Mocha.jl
Deep Learning framework for Julia
Mocha.jl is a deep learning framework for Julia, inspired by the C++ Caffe framework. It offers efficient implementations of gradient descent solvers and common neural network layers, supports optional unsupervised pre-training, and allows switching to a GPU backend for accelerated performance. The development of Mocha.jl happens in relative early days of Julia. -
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Intel neon
Intel® Nervana™ reference deep learning framework
neon is Intel's reference deep learning framework committed to best performance on all hardware. Designed for ease of use and extensibility. See the new features in our latest release. We want to highlight that neon v2.0.0+ has been optimized for much better performance on CPUs by enabling Intel Math Kernel Library (MKL). The DNN (Deep Neural Networks) component of MKL that is used by neon is provided free of charge and downloaded automatically as part of the neon installation. ... -
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Caffe2
Caffe2 is a lightweight, modular, and scalable deep learning framework
Caffe2 is a lightweight, modular, and scalable deep learning framework. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind. Caffe2 is a deep learning framework that provides an easy and straightforward way for you to experiment with deep learning and leverage community contributions of new models and algorithms. You can bring your creations to scale using the power of GPUs in the cloud or to the masses on mobile with Caffe2’s cross-platform libraries. ... -
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Orkney
Orkney Testframework
...Test steps are used like bricks to create test cases while test groups collect test cases and other test groups to create a test suite. Test cases are written in a simple text language thus allowing composition of cases from test steps without deep programming knowledge. Reports are created in text and in XML format, the latter are converted to a human readable form when using a standard web browser. -
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Caffe
A fast open framework for deep learning
Caffe is an open source deep learning framework that’s focused on expression, speed and modularity. It’s got an expressive architecture that encourages application and innovation, and extensible code that’s great for active development. Caffe also offers great speed, capable of processing over 60M images per day with a single NVIDIA K40 GPU. It’s arguably one of the fastest convnet implementations around.
