Showing 3401 open source projects for "c source code"

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  • 1
    wav2letter++

    wav2letter++

    Facebook AI research's automatic speech recognition toolkit

    First, install Flashlight (using the 0.3 branch is required) with the ASR application. This repository includes recipes to reproduce the following research papers as well as pre-trained models. All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run...
    Downloads: 0 This Week
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  • 2
    GIMP ML

    GIMP ML

    AI for GNU Image Manipulation Program

    This repository introduces GIMP3-ML, a set of Python plugins for the widely popular GNU Image Manipulation Program (GIMP). It enables the use of recent advances in computer vision to the conventional image editing pipeline. Applications from deep learning such as monocular depth estimation, semantic segmentation, mask generative adversarial networks, image super-resolution, de-noising and coloring have been incorporated with GIMP through Python-based plugins. Additionally, operations on...
    Downloads: 9 This Week
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  • 3
    ANDTool

    ANDTool

    Analysis Nuclei DAB (AND) Tool

    ...The tool requires as input the original RGB images, and the FastRed, FastBlue, DAB channel, easily obtained using the Fiji function: "ImageJ" -> "Image" -> "Colour Deconvolution" -> "FastRed FastBlue DAB" Then, the tool first segment the nuclei using the FastBlue channel and the DAB channel, and then computes statistics by subdividing the sample in three regions according to the FastRed channel: a dark-red ROI, a light-pink ROI and a white ROI. ANDTool is written in MATLAB (The MathWorks, Inc., Massachusetts, USA) and the source code and standalone versions are here available for download. USER MANUAL: see the specific PDF available in the Files section. REQUIREMENTS: MATLAB R2017b and Image Processing Toolbox 10.1 or later versions. MAIN CONTACT: Filippo Piccinini (E-mail: filippo.piccinini85@gmail.com)
    Downloads: 0 This Week
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  • 4
    NLP.js

    NLP.js

    An NLP library for building bots

    NLP.js is an NLP library for building bots, with entity extraction, sentiment analysis, automatic language identifier, and much more. "NLP.js" is a general natural language utility for nodejs. Search the best substring of a string with less Levenshtein distance to a given pattern. Get stemmers and tokenizers for several languages. Sentiment Analysis for phrases (with negation support). Named Entity Recognition and management, multi-language support, and acceptance of similar strings, so the...
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  • 5
    Turi Create

    Turi Create

    Simplifies the development of custom machine learning models

    ...If you want to build Turi Create from source, see BUILD.md. Turi Create does not require a GPU, but certain models can be accelerated 9-13x by utilizing a GPU.
    Downloads: 0 This Week
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  • 6
    TensorFlow 2.0 Tutorials

    TensorFlow 2.0 Tutorials

    TensorFlow 2.x version's Tutorials and Examples

    ...Each section of the repository includes runnable code and structured experiments designed to illustrate how different architectures and algorithms function in real applications. The tutorials use well-known benchmark datasets such as MNIST, CIFAR, and Fashion-MNIST to demonstrate practical model training and evaluation workflows.
    Downloads: 2 This Week
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  • 7
    Isolation‐based anomaly detection

    Isolation‐based anomaly detection

    Isolation‐based anomaly detection using nearest‐neighbor ensembles

    This site provides the source code of Isolation‐based anomaly detection (iNNE). https://onlinelibrary.wiley.com/doi/abs/10.1111/coin.12156 Bandaragoda, T.R., Ting, K.M., Albrecht, D., Liu, F.T., Zhu, Y. and Wells, J.R., 2018. Isolation‐based anomaly detection using nearest‐neighbor ensembles. Computational Intelligence, 34(4), pp.968-998.
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  • 8

    cuneiformplus

    Fork of OCR software cuneiform

    Fork of OCR software cuneiform Original software see: https://launchpad.net/cuneiform-linux by Cognitive Technologies and Jussi Pakkanen Other Open Source OCR stuff see * Tesseract by Ray Smith (using the Leptonica image library) * GOCR * OCRAD
    Downloads: 3 This Week
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  • 9
    Astro Boy Chat Room

    Astro Boy Chat Room

    Atom chat room nestjs+vue full stack chat room

    In my spare time, I wanted to make a chat room to consolidate front-end skills, so I started the development journey of Astro chat room on June 24, 2020. The project is developed in full typescript, which is to lay the foundation for future functional iterations. Of course, I also like typescript very much. At present, the chat room has a complete chat function. More cool features will be developed in the future! Interested friends can fork to develop by themselves, you can change it at...
    Downloads: 0 This Week
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  • 10
    ML.NET Samples

    ML.NET Samples

    Samples for ML.NET, an open source and cross-platform machine learning

    ...The "best" model and the code for running it will be generated for you. The ML.NET CLI (command-line interface) is a tool you can run on any command prompt (Windows, Mac or Linux) for generating good quality ML.NET models based on training datasets you provide. In addition, it also generates sample C# code to run/score that model plus the C# code that was used to create/train it so you can research what algorithm and settings it is using.
    Downloads: 0 This Week
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  • 11
    LTI-Lib is an object oriented computer vision library written in C++ for Windows/MS-VC++ and Linux/gcc. It provides lots of functionality to solve mathematical problems, many image processing algorithms, some classification tools and much more...
    Downloads: 0 This Week
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  • 12
    Multilingual Speech Synthesis

    Multilingual Speech Synthesis

    An implementation of Tacotron 2 that supports multilingual experiments

    This repository provides synthesized samples, training and evaluation data, source code, and parameters for the paper One Model, Many Languages: Meta-learning for Multilingual Text-to-Speech. It contains an implementation of Tacotron 2 that supports multilingual experiments and that implements different approaches to encoder parameter sharing. It presents a model combining ideas from Learning to speak fluently in a foreign language: Multilingual speech synthesis and cross-language voice cloning, End-to-End Code-Switched TTS with Mix of Monolingual Recordings, and Contextual Parameter Generation for Universal Neural Machine Translation. ...
    Downloads: 1 This Week
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  • 13
    BotMan

    BotMan

    A framework agnostic PHP library to build chat bots

    Write your chatbot logic once and connect it to one of the available messaging services, including Amazon Alexa, Facebook Messenger, Slack, Telegram or even your own Website. BotMan is framework agnostic, which means you can use it in your existing codebase, whatever framework you might use. Starting a new chatbot project? BotMan Studio is a Laravel 5.5 boiler project to get you started in no time! BotMan is all about having an expressive, yet powerful syntax that allows you to focus on the...
    Downloads: 0 This Week
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  • 14
    Supervised Reptile

    Supervised Reptile

    Code for the paper "On First-Order Meta-Learning Algorithms"

    The supervised-reptile repository contains code associated with the paper “On First-Order Meta-Learning Algorithms”, which introduces Reptile, a meta-learning algorithm for learning model parameter initializations that adapt quickly to new tasks. The implementation here is aimed at supervised few-shot learning settings (e.g. Omniglot, Mini-ImageNet), not reinforcement learning, and includes scripts to run training and evaluation for few-shot classification. The fundamental idea is: sample a...
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  • 15
    Stable Baselines

    Stable Baselines

    A fork of OpenAI Baselines, implementations of reinforcement learning

    Stable Baselines is a set of improved implementations of reinforcement learning algorithms based on OpenAI Baselines. You can read a detailed presentation of Stable Baselines in the Medium article. These algorithms will make it easier for the research community and industry to replicate, refine, and identify new ideas, and will create good baselines to build projects on top of. We expect these tools will be used as a base around which new ideas can be added, and as a tool for comparing a new...
    Downloads: 0 This Week
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  • 16
    Linux-Intelligent-Ocr-Solution

    Linux-Intelligent-Ocr-Solution

    Easy-OCR solution and Tesseract trainer for GNU/Linux

    ...forum/lios Video Tutorial : https://www.youtube.com/playlist?list=PLn29o8rxtRe1zS1r2-yGm1DNMOZCgdU0i Tesseract Training Tutorial (beta) : https://www.youtube.com/watch?v=qLpCld4cdtk Source Code Github : https://github.com/Nalin-x-Linux/lios-3 Gitlab : https://gitlab.com/Nalin-x-Linux/lios-3 User guide is available in download page
    Downloads: 7 This Week
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  • 17
    MMdnn

    MMdnn

    Tools to help users inter-operate among deep learning frameworks

    MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML. MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model management, and "dnn" is the acronym of deep neural network. We implement a universal converter to convert DL models between frameworks,...
    Downloads: 0 This Week
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  • 18
    uTensor

    uTensor

    TinyML AI inference library

    uTensor is an embedded machine learning inference framework designed to run neural network models on resource-constrained devices such as microcontrollers and Internet-of-Things hardware. The project focuses on enabling TinyML deployments by translating trained machine learning models into efficient C++ code that can execute directly on embedded systems. Instead of training models on-device, the framework uses an offline workflow that converts trained TensorFlow graphs into optimized inference kernels suitable for constrained environments. This approach allows developers to build machine learning models using standard frameworks and then deploy them to devices with extremely limited memory and processing power. ...
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  • 19
    Computer Vision

    Computer Vision

    Best Practices, code samples, and documentation for Computer Vision

    In recent years, we've see an extra-ordinary growth in Computer Vision, with applications in face recognition, image understanding, search, drones, mapping, semi-autonomous and autonomous vehicles. A key part to many of these applications are visual recognition tasks such as image classification, object detection and image similarity. This repository provides examples and best practice guidelines for building computer vision systems. The goal of this repository is to build a comprehensive...
    Downloads: 2 This Week
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  • 20
    The Player Project: Player is a networked interface to robots and sensors. Stage and Gazebo are Player-friendly multiple-robot simulators. The software aims for POSIX compliance and runs on most UNIX-like OS's. Some parts also work on Windows.
    Downloads: 15 This Week
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  • 21
    Euler

    Euler

    A distributed graph deep learning framework.

    As a general data structure with strong expressive ability, graphs can be used to describe many problems in the real world, such as user networks in social scenarios, user and commodity networks in e-commerce scenarios, communication networks in telecom scenarios, and transaction networks in financial scenarios. and drug molecule networks in medical scenarios, etc. Data in the fields of text, speech, and images is easier to process into a grid-like type of Euclidean space, which is suitable...
    Downloads: 1 This Week
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  • 22
    StellarGraph

    StellarGraph

    Machine Learning on Graphs

    StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can...
    Downloads: 0 This Week
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  • 23
    DETR

    DETR

    End-to-end object detection with transformers

    PyTorch training code and pretrained models for DETR (DEtection TRansformer). We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based...
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  • 24
    Dive into DL PyTorch

    Dive into DL PyTorch

    This project changes the MXNet implementation

    Dive into DL PyTorch is a PyTorch adaptation of the Chinese edition of the educational book Dive into Deep Learning. It replaces the book's original MXNet implementations with executable PyTorch examples while preserving the broader instructional material. Chapter code is organized as Jupyter notebooks so learners can run and modify examples interactively. The accompanying documentation is stored in Markdown and published as a browsable Docsify website. The material is intended for beginners...
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  • 25
    Tensor2Tensor

    Tensor2Tensor

    Library of deep learning models and datasets

    Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and...
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