Showing 1085 open source projects for "processing"

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  • 1
    Jina

    Jina

    Build cross-modal and multimodal applications on the cloud

    Jina is a framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Build applications that deliver fresh insights from multiple data types such as text, image, audio, video, 3D mesh, PDF with Jina AI’s DocArray. Polyglot gateway that supports gRPC, Websockets, HTTP,...
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  • 2
    fastai

    fastai

    Deep learning library

    ...It aims to do both things without substantial compromises in ease of use, flexibility, or performance. This is possible thanks to a carefully layered architecture, which expresses common underlying patterns of many deep learning and data processing techniques in terms of decoupled abstractions. These abstractions can be expressed concisely and clearly by leveraging the dynamism of the underlying Python language and the flexibility of the PyTorch library. fastai is organized around two main design goals: to be approachable and rapidly productive, while also being deeply hackable and configurable. ...
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  • 3
    OAGI Python SDK

    OAGI Python SDK

    Python SDK for the Computer Use model Lux, developed by OpenAGI

    OAGI Python SDK is a Python client library for the Lux computer-use model that turns Lux into a programmable automation layer for operating human-facing software via vision and actions. It exposes the OAGI API in an ergonomic way, letting you trigger Lux in three main modes: Tasker for precise scripted sequences, Actor for fast one-shot tasks, and Thinker for open-ended, multi-step objectives. The SDK is designed around “computer use” as a paradigm, where the AI actually navigates...
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  • 4
    Step-Audio 2

    Step-Audio 2

    Multi-modal large language model designed for audio understanding

    Step-Audio2 is an advanced, end-to-end multimodal large language model designed for high-fidelity audio understanding and natural speech conversation: unlike many pipelines that separate speech recognition, processing, and synthesis, Step-Audio2 processes raw audio, reasons about semantic and paralinguistic content (like emotion, speaker characteristics, non-verbal cues), and can generate contextually appropriate responses — including potentially generating or transforming audio output. It integrates a latent-space audio encoder, discrete acoustic tokens, and reinforcement-learning–based training (CoT + RL) to enhance its ability to capture and reproduce voice styles, intonations, and subtle vocal cues. ...
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    Mini Agent

    Mini Agent

    A minimal yet professional single agent demo project

    ...It includes a basic toolset for file-system operations and shell commands, plus integrations with MCP tools such as web search and knowledge graph access. Mini-Agent also comes with “Claude Skills”-style predefined skills for tasks like document processing, design work, and testing, packaged as reusable behaviors that can be invoked by the agent as needed.
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  • 6
    HunyuanOCR

    HunyuanOCR

    OCR expert VLM powered by Hunyuan's native multimodal architecture

    HunyuanOCR is an open-source, end-to-end OCR (optical character recognition) Vision-Language Model (VLM) developed by Tencent‑Hunyuan. It’s designed to unify the entire OCR pipeline, detection, recognition, layout parsing, information extraction, translation, and even subtitle or structured output generation, into a single model inference instead of a cascade of separate tools. Despite being fairly lightweight (about 1 billion parameters), it delivers state-of-the-art performance across a...
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  • 7
    MiniMax-01

    MiniMax-01

    Large-language-model & vision-language-model based on Linear Attention

    MiniMax-01 is the official repository for two flagship models: MiniMax-Text-01, a long-context language model, and MiniMax-VL-01, a vision-language model built on top of it. MiniMax-Text-01 uses a hybrid attention architecture that blends Lightning Attention, standard softmax attention, and Mixture-of-Experts (MoE) routing to achieve both high throughput and long-context reasoning. It has 456 billion total parameters with 45.9 billion activated per token and is trained with advanced parallel...
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  • 8
    Alan AI for iOS

    Alan AI for iOS

    In-App assistant SDK to build a multimodal conversational UX for iOS

    ...Alan's AI-backend powered by the industry’s best Automatic Speech Recognition (ASR), Natural Language Understanding (NLU) and Speech Synthesis. The Alan Cloud provisions and handles the infrastructure required to maintain your voice deployments and perform all the voice processing tasks. Voice enable your app, you only need to get the Alan Client SDK and drop it into your app. No need to plan for, deploy and maintain any infrastructure or speech components - the Alan Platform does the bulk of the work.
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  • 9
    Swirl

    Swirl

    Swirl queries any number of data sources with APIs

    Swirl queries any number of data sources with APIs and uses spaCy and NLTK to re-rank the unified results without extracting and indexing anything! Includes zero-code configs for Apache Solr, ChatGPT, Elastic Search, OpenSearch, PostgreSQL, Google BigQuery, RequestsGet, Google PSE, NLResearch.com, Miro & more! SWIRL adapts and distributes queries to anything with a search API - search engines, databases, noSQL engines, cloud/SaaS services etc - and uses AI (Large Language Models) to re-rank...
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  • 10
    FlowGram

    FlowGram

    Extensible workflow development framework

    ...Instead of shipping as a ready-made product, it provides the building blocks — a canvas for wiring together nodes, a form engine for configuring node parameters, a variable-scope and type-inference engine, and a set of “materials” (pre-built node types such as code execution, conditional logic, LLM calls, etc.) that can be composed into larger workflows. This makes FlowGram highly flexible: you can prototype data-processing pipelines, AI-agent flows, automation scripts, or even business process automation without writing all the plumbing yourself. The framework supports both free-layout canvases (for free-form graphs) and fixed-layout canvases (for more structured flowcharts, including loops, branches, compound nodes), giving you visual freedom depending on your use-case.
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  • 11
    Zero to Mastery Deep Learning TensorFlow

    Zero to Mastery Deep Learning TensorFlow

    All course materials for the Zero to Mastery Deep Learning with TF

    ...It is structured as a series of progressively complex Jupyter notebooks that emphasize writing and understanding code before diving into theory, reinforcing learning through repetition and application. The material covers core machine learning workflows including regression, classification, computer vision, natural language processing, and time series forecasting, allowing users to build a well-rounded understanding of modern AI tasks. It also integrates milestone projects that simulate real-world scenarios, helping users translate abstract concepts into deployable solutions.
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  • 12
    MegEngine

    MegEngine

    Easy-to-use deep learning framework with 3 key features

    MegEngine is a fast, scalable and easy-to-use deep learning framework with 3 key features. You can represent quantization/dynamic shape/image pre-processing and even derivation in one model. After training, just put everything into your model and inference it on any platform at ease. Speed and precision problems won't bother you anymore due to the same core inside. In training, GPU memory usage could go down to one-third at the cost of only one additional line, which enables the DTR algorithm. ...
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  • 13
    OpenCV

    OpenCV

    Open Source Computer Vision Library

    The Open Source Computer Vision Library has >2500 algorithms, extensive documentation and sample code for real-time computer vision. It works on Windows, Linux, Mac OS X, Android, iOS in your browser through JavaScript. Languages: C++, Python, Julia, Javascript Homepage: https://opencv.org Q&A forum: https://forum.opencv.org/ Documentation: https://docs.opencv.org Source code: https://github.com/opencv Please pay special attention to our tutorials!...
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    Downloads: 9,114 This Week
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  • 14
    torchtext

    torchtext

    Data loaders and abstractions for text and NLP

    We recommend Anaconda as a Python package management system. Please refer to pytorch.org for the details of PyTorch installation. LTS versions are distributed through a different channel than the other versioned releases. Alternatively, you might want to use the Moses tokenizer port in SacreMoses (split from NLTK). You have to install SacreMoses. To build torchtext from source, you need git, CMake and C++11 compiler such as g++. When building from source, make sure that you have the same C++...
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  • 15
    airda

    airda

    airda(Air Data Agent

    airda(Air Data Agent) is a multi-smart body for data analysis, capable of understanding data development and data analysis needs, understanding data, generating data-oriented queries, data visualization, machine learning and other tasks of SQL and Python codes.
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  • 16

    BoofCV

    BoofCV is an open source Java library for real-time computer vision.

    ...Written from scratch for ease of use and high performance, it provides both basic and advanced features needed for creating a computer vision system. Functionality include optimized low level image processing routines (e.g. convolution, interpolation, gradient) to high level functionality such as image stabilization. Released under an Apache 2.0 license for both academic and commercial use.
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    Downloads: 32 This Week
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  • 17
    crème de la crème of AI courses

    crème de la crème of AI courses

    This repository is a curated collection of links to various courses

    ...The repository organizes courses by topic, difficulty level, format, and release year, allowing learners to quickly identify relevant material depending on their experience and interests. Topics covered include deep learning, natural language processing, computer vision, large language models, linear algebra, reinforcement learning, and machine learning engineering. Because the repository links to well-known educational content such as university lecture series and professional training materials, it functions as a structured roadmap for individuals who want to develop expertise in artificial intelligence.
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  • 18
    SMILI

    SMILI

    Scientific Visualisation Made Easy

    ...The main sMILX application features for viewing n-D images, vector images, DICOMs, anonymizing, shape analysis and models/surfaces with easy drag and drop functions. It also features a number of standard processing algorithms for smoothing, thresholding, masking etc. images and models, both with graphical user interfaces and/or via the command-line. See our YouTube channel for tutorial videos via the homepage. The applications are all built out of a uniform user-interface framework that provides a very high level (Qt) interface to powerful image processing and scientific visualisation algorithms from the Insight Toolkit (ITK) and Visualisation Toolkit (VTK). ...
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    Downloads: 37 This Week
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  • 19
    goodsKill

    goodsKill

    Microservices-based flash sale system for high-concurrency testing

    ...It supports distributed transactions, database sharding, and multiple concurrency control strategies including distributed locks and message queues. It includes modular services like gateway, authentication, order management, and seckill processing, along with a Vue 3-based admin UI. It also incorporates AI-driven simulation capabilities for automated testing. Designed primarily as a learning reference, it showcases scalable system design, microservices communication, and real-world tradeoffs in handling high-traffic transactional systems.
    Downloads: 0 This Week
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  • 20
    AI_Tutorial

    AI_Tutorial

    A selection of learning materials, search, recommendation, advertising

    AI_Tutorial is a large curated repository that aggregates high-quality learning resources related to artificial intelligence, machine learning, deep learning, natural language processing, and data engineering. The project functions as a centralized knowledge base designed to help engineers and researchers discover tutorials, technical articles, algorithm explanations, and architecture discussions from across the AI ecosystem. Rather than focusing on a single framework or course, the repository collects materials from many sources such as open-source projects, technical blogs, research papers, and industry engineering posts. ...
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  • 21
    A Survey of Surveys

    A Survey of Surveys

    A collection of 1000+ survey papers on Natural Language Processing

    A Survey of Surveys is a large curated repository that collects and organizes survey papers related to natural language processing, machine learning, and artificial intelligence research. The project aims to provide a centralized index of survey literature that summarizes major developments across different subfields of AI. Rather than focusing on code implementations, the repository functions as an academic resource that helps researchers quickly discover comprehensive survey papers covering various topics. ...
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  • 22
    MATLAB Deep Learning Model Hub

    MATLAB Deep Learning Model Hub

    Discover pretrained models for deep learning in MATLAB

    Discover pre-trained models for deep learning in MATLAB. Pretrained image classification networks have already learned to extract powerful and informative features from natural images. Use them as a starting point to learn a new task using transfer learning. Inputs are RGB images, the output is the predicted label and score.
    Downloads: 3 This Week
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  • 23
    Machine Learning Notebooks

    Machine Learning Notebooks

    Machine Learning Notebooks

    ...Each notebook is intentionally lightweight, avoiding unnecessary complexity so that users can easily understand the core concepts and adapt the code to their own projects. The repository supports a wide range of applications, including natural language processing, computer vision, and general deep learning workflows. It is also designed to be easily extensible, allowing developers and researchers to build upon the provided examples without needing to restructure the codebase.
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  • 24
    Armadillo

    Armadillo

    fast C++ library for linear algebra & scientific computing

    * Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads: http://arma.sourceforge.net/download.html * Documentation: http://arma.sourceforge.net/docs.html * Bug reports: http://arma.sourceforge.net/faq.html * Git repo: https://gitlab.com/conradsnicta/armadillo-code
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    Downloads: 2,538 This Week
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  • 25

    libsombrero

    Astronomical object/structure detection from 1D and 2D data sets.

    Sombrero is a fast wavelet image processing and object detection C library for astronomical images. Sombrero is named after the "Mexican Hat" shape of the wavelet masks used in image convolution and is released under the GNU LGPL library.
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