Showing 7 open source projects for "can"

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  • 1
    Google AI Edge Gallery

    Google AI Edge Gallery

    A gallery that showcases on-device ML/GenAI use cases

    ...Each sample is intended to be both a learning aid and a practical starting point: code is organized to show model loading, pre/post-processing, performance measurement, and common optimization knobs (quantization, NNAPI/Delegate usage, and hardware accelerators). The repo also collects small, well-documented models and conversion scripts so developers can reproduce a pipeline from a full-size model down to a device-friendly artifact.
    Downloads: 146 This Week
    Last Update:
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  • 2
    MNN

    MNN

    MNN is a blazing fast, lightweight deep learning framework

    MNN is a highly efficient and lightweight deep learning framework. It supports inference and training of deep learning models, and has industry leading performance for inference and training on-device. At present, MNN has been integrated in more than 20 apps of Alibaba Inc, such as Taobao, Tmall, Youku, Dingtalk, Xianyu and etc., covering more than 70 usage scenarios such as live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity...
    Downloads: 58 This Week
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  • 3
    Vosk Speech Recognition Toolkit

    Vosk Speech Recognition Toolkit

    Offline speech recognition API for Android, iOS, Raspberry Pi

    ...Speech recognition bindings are implemented for various programming languages like Python, Java, Node.JS, C#, C++, Rust, Go and others. Vosk supplies speech recognition for chatbots, smart home appliances, and virtual assistants. It can also create subtitles for movies, and transcription for lectures and interviews. Vosk scales from small devices like Raspberry Pi or Android smartphones to big clusters.
    Downloads: 112 This Week
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  • 4
    MMdnn

    MMdnn

    Tools to help users inter-operate among deep learning frameworks

    ...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, which means you can train a model with one framework and deploy it with another. During the model conversion, we generate some code snippets to simplify later retraining or inference. We provide a model collection to help you find some popular models. We provide a model visualizer to display the network architecture more intuitively. We provide some guidelines to help you deploy DL models to another hardware platform.
    Downloads: 0 This Week
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  • Custom VMs From 1 to 96 vCPUs With 99.95% Uptime Icon
    Custom VMs From 1 to 96 vCPUs With 99.95% Uptime

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  • 5
    Face Detector

    Face Detector

    Detect faces in real time

    This Face Detector app can able to detect multiple faces from images in Real-time or from any images that placed in device's storage. In Real-time detection mode user have to give permission to this app to access device camera and voice recorder. In Gallery mode user have to select images from external storage, then it can able to detect the actual faces. This is very short and simple AI based project that can runs on Firebase ML kit API and Google play vision API. ...
    Downloads: 0 This Week
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  • 6
    nunn

    nunn

    This is an implementation of a machine learning library in C++17

    nunn is a collection of ML algorithms and related examples written in modern C++17.
    Downloads: 1 This Week
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  • 7
    neural network designer

    neural network designer

    a dbms for neural nets. Chatbots, DTrees, random forests, n-grams,...

    ...With the designer, you are able to create different types of decision trees, random forests, n-grams, pattern-matchers, conversational agents and all sorts of AI related algorithms. You can combine statistical approaches as well as pattern matchers or others. Do natural language processing, image or data analysis & interpretation,...
    Downloads: 2 This Week
    Last Update:
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