Search Results for "image processing framework" - Page 26
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Showing 1534 open source projects for "image processing framework"
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dispy
Distributed and Parallel Computing with/for Python.
dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. dispy supports public / private / hybrid cloud computing, fog / edge computing. -
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uni-media
Easily display media content (image, video, audio, 3d-models)
Easily embed any types of media in your web app with one line of code. A simple, powerful, and performant media display web component fitting every framework. Automatically analyze the type of media with multiple fallback-able performant-first strategies. Works with all modern browsers and frameworks (React.js, Vue.js, Svelte...). Best for displaying decentralized media and content (like NFTs). -
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Phoronix Test Suite
Open-Source, Automated Benchmarking
The Phoronix Test Suite is the most comprehensive testing and benchmarking platform available that provides an extensible framework for which new tests can be easily added. The Phoronix Test Suite is designed to effectively carry out both benchmarks in a clean, reproducible, and easy-to-use manner. -
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LuLu UI
Cross-end and cross-framework native UI component library
LuLu UI is a front-end UI component library proudly produced by China Literature. The image and temperament are shown in the picture below. It is softer, more intimate, simple and flexible, and very user-friendly. It is very suitable for PC websites facing external users, or projects that require lightweight and agile. At this point, modify the JS and CSS files of the project, refresh the corresponding component page, and you can see the effect of the change. The whole project of LuLu is to... -
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pspider
Simple Python framework for building multithreaded web crawlers
PSpider is a lightweight web crawling framework written in Python designed to simplify the development of custom web spiders. It focuses on providing an easy-to-understand architecture while still supporting concurrent crawling for improved performance. It uses a multithreaded model that separates the crawling workflow into several components responsible for fetching, parsing, and saving data. Tasks are managed through queues, allowing different parts of the crawler to process work... -
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imgproxy
fast and secure image processing with machine learning features
imgproxy is a blazing fast and secure image processing tool. Built with a focus on developer productivity, it saves time and money on developing hand-rolled image processing pipelines. imgproxy Pro is an advanced version of this blazing fast and secure image processing tool. It provides priority support, smart image adjustments, machine learning features, watermarking, and video support. -
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Django REST Framework User
This Django User Model is customised user model
This Django User Model is a customized user model keeping in mind the practical need. JWT Support (Using Simple JWT) Mobile Number, single field for full name, REST API to register, REST API to login, MultiModelBackend: User can login using either of mobile, email or username. REST API to login with OTP (Same API endpoint as for OTP Verification; Set is_login: true while sending JSON request). OTP Verification for mobile and email, API to register / login with OTP (no pre-registration... -
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RCDCap
RCDCap is a remote capture preprocessor
RCDCap is a packet processing framework. At its core, it incorporates basic mechanisms for local and remote capturing and decapsulation of packets (CISCO ERSPAN and HP ERM are supported). It can be extended to support many types of packet-based traffic analysis by creating plug-ins and loading them in the main application. It includes many optimizations to ensure high performance traffic processing. -
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NewBreeze
Fast and light-weight File Manager
Built on top of the Powerful Qt GUI Toolkit, this file manager is sleek, stylish and fast. -
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xt7-player aims to be a complete gui to mplayer with library and playlist support, built with usability in mind.
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MAE (Masked Autoencoders)
PyTorch implementation of MAE
MAE (Masked Autoencoders) is a self-supervised learning framework for visual representation learning using masked image modeling. It trains a Vision Transformer (ViT) by randomly masking a high percentage of image patches (typically 75%) and reconstructing the missing content from the remaining visible patches. This forces the model to learn semantic structure and global context without supervision. -
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Deep learning time series forecasting
Deep learning PyTorch library for time series forecasting
Example image Flow Forecast (FF) is an open-source deep learning for time series forecasting framework. It provides all the latest state-of-the-art models (transformers, attention models, GRUs) and cutting-edge concepts with easy-to-understand interpretability metrics, cloud provider integration, and model serving capabilities. Flow Forecast was the first time series framework to feature support for transformer-based models and remains the only true end-to-end deep learning for time series forecasting framework. ... -
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NaveGo
NaveGo: an open source MATLAB/GNU Octave toolbox for processing integr
NaveGo is an open source MATLAB/GNU Octave toolbox designed for processing integrated navigation systems, simulating inertial sensors and GNSS receivers, and profiling inertial sensors using methods like Allan variance—providing a community-driven simulation framework for navigation system design and analysis. I am reaching out to share an important update regarding the NaveGo project. Due to a shift in both my professional career and personal interests away from navigation systems, I have made the difficult decision to step down from my role as the lead developer of NaveGo. ... -
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Unet
Source code for unet-pytorch, which can train its own model
...It includes scripts for general training, medical dataset training, prediction, annotation handling, model summaries, and evaluation. The project supports multiple backbones, data processing utilities, extensive comments, and adjustable training parameters. Its README notes that U-Net is better suited to datasets with fewer features and shallow visual structures, such as medical image segmentation, rather than complex VOC-style scenes. It is useful for developers and students who want a clear U-Net implementation for segmentation experiments, custom masks, and biomedical-style image analysis. -
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OpenPrompt
An Open-Source Framework for Prompt-Learning
Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks, which modifies the input text with a textual template and directly uses PLMs to conduct pre-trained tasks. OpenPrompt is a library built upon PyTorch and provides a standard, flexible and extensible framework to deploy the prompt-learning pipeline. OpenPrompt supports loading PLMs directly from huggingface transformers. In the future, we will also support PLMs implemented by other... -
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Lad
Lad is the best Node.js framework
Lad is the best Node.js framework. Made by a former Express TC and Koa team member. Lad boasts dozens of features and is extremely configurable. These microservices are preconfigured for security, performance, and graceful reloading. Redis, sessions, flash toast, and modal SweetAlert2 messages (uses ioredis which has support for Cluster, Sentinel, and more). Koa-based web app and API servers. Pagination built-in (using ctx-paginate). RESTful API with BasicAuth and versioning. Automated job... -
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Botkit
Tool for building chat bots, apps and custom integrations
An open source developer tool for building chat bots, apps and custom integrations for major messaging platforms. Part of the Microsoft Bot Framework. We love bots, and want to make them easy and fun to build! Include Botkit into your Node application and boot up a controller that will define your bot's behaviors. In this case, we're setting up a bot to use with the Bot Framework Emulator. Tell the bot to listen for users saying "hello," and use `bot.reply` to send an immediate response.... -
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TensorFlowOnSpark
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters
By combining salient features from the TensorFlow deep learning framework with Apache Spark and Apache Hadoop, TensorFlowOnSpark enables distributed deep learning on a cluster of GPU and CPU servers. It enables both distributed TensorFlow training and inferencing on Spark clusters, with a goal to minimize the amount of code changes required to run existing TensorFlow programs on a shared grid. -
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Flashlight library
A C++ standalone library for machine learning
Flashlight is a fast, flexible machine learning library written entirely in C++ by Facebook AI Research and the creators of Torch, TensorFlow, Eigen, and Deep Speech. Native support in C++ and simple extensibility make Flashlight a powerful research framework that's hackable to its core and enables fast iteration on new experimental setups and algorithms with little unopinionated and without sacrificing performance. In a single repository, Flashlight provides apps for research across... -
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Revel
A high productivity, full-stack web framework for the Go language
...It gives you a helpful description. Run-time code panic? Revel has you covered. Revel provides routing, parameter parsing, validation, session/flash, templating, caching, job running, a testing framework, and even internationalization. Revel is built around composable middleware called filters, which implement nearly all request-processing functionality. Developers have the freedom to replace the default filters with custom implementations. Already have an application started ? No problems, migrate easily to Revel by passing the path that you want your mux to handle to Revels Mux, and all requests for that path will be passed to that your Http muxer. ... -
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PyTorch Handbook
The pytorch handbook is an open source book
PyTorch Handbook is an open-source educational project designed to help developers and researchers quickly learn deep learning using the PyTorch framework. The repository functions as an online handbook that explains how to build, train, and evaluate neural network models using PyTorch. It includes tutorials and examples that demonstrate common deep learning tasks such as image classification, neural network design, model training workflows, and evaluation techniques. The material is written with a practical focus so that readers can follow along and run the provided examples successfully. ... -
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Firelens Datajet
Route test data to Fluent Bit flexibly
Route test data to Fluent Bit flexibly. This system can be run locally with a local Fluent Bit process or compiled to a docker image and run with a sidecar aws-for-fluent-bit container. The purpose of Firelens-Datajet is to abstract test configuration from implementation code It does so by running tests based on a single JSON file and outputting the results. Future work on this system involves making a REST interface for tests to be invoked by sending a POST request with the test... -
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VSGAN
VapourSynth Single Image Super-Resolution Generative Adversarial
Single Image Super-Resolution Generative Adversarial Network (GAN) which uses the VapourSynth processing framework to handle input and output image data. Transform, Filter, or Enhance your input video, or the VSGAN result with VapourSynth, a Script-based NLE. You can chain models or re-run the model twice-over (or more). Have low VRAM? Don’t worry! -
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Metztli Reiser5
Metztli Reiser4 Software Framework Release Number(SFRN) 5.1.3 unstable
'There is no reiser5', said the main reiser4 maintainer/developer; yet, he announced his new project as 'reiser5' ;-) Unstable snapshot of new Metztli Reiser4, Software Framework Release Number (SFRN) 5.1.3, minimal Debian Installer (d-i) for AMD64. Netboot ISO Image may be 'burned' to USB stick with command (assuming USB device is at /dev/sdb) *else* modify or you risk data loss: dd if=metztli-reiser4-sfrn5.iso of=/dev/sdb bs=4M; sync and/or for AMD Epyc/Ryzen CPUs dd if=metztli-reiser4-sfrn5-z.iso of=/dev/sdb bs=4M; sync Enables d-i create, partition, format, recover, and native installation operations on Reiser4 SFRN 5 filesystems. ... -
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MeshCNN in PyTorch
Convolutional Neural Network for 3D meshes in PyTorch
MeshCNN is a deep learning framework designed specifically for processing 3D triangular mesh data using convolutional neural networks. Unlike traditional CNNs that operate on images or voxel grids, MeshCNN performs convolution operations directly on the edges of mesh structures. This design allows the model to capture geometric relationships between mesh elements while preserving the underlying topology of 3D shapes.
