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Showing 3 open source projects for "tensorflow"

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    OPENRNDR

    OPENRNDR

    Kotlin library for creative coding, real-time and interactive graphics

    ...You can use OPENRNDR to visualize the data coming from these models in order to create compelling (interactive) experiences. The ORML library includes both models and interface code to make the use of those models simple. ORML is built on top of orx-tensorflow which is an OPENRNDR extra that provides tools to wrap and convert between Tensorflow and OPENRNDR primitives. With these integrations, Machine Learning has become more accessible for interactive designers, coders, and developers.
    Downloads: 0 This Week
    Last Update:
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  • 2
    Google AI Edge Gallery

    Google AI Edge Gallery

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

    Gallery is a curated collection of on-device machine learning examples, demo apps, and model artifacts designed to help developers experiment with and deploy ML at the edge. The project bundles runnable samples that show how to run TensorFlow Lite/Edge TPU models (and similar lightweight runtimes) on mobile and embedded platforms, demonstrating common tasks like image classification, object detection, audio recognition, and pose estimation. 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). ...
    Downloads: 56 This Week
    Last Update:
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  • 3
    KotlinDL

    KotlinDL

    High-level Deep Learning Framework written in Kotlin

    KotlinDL is a high-level Deep Learning API written in Kotlin and inspired by Keras. Under the hood, it uses TensorFlow Java API and ONNX Runtime API for Java. KotlinDL offers simple APIs for training deep learning models from scratch, importing existing Keras and ONNX models for inference, and leveraging transfer learning for tailoring existing pre-trained models to your tasks. This project aims to make Deep Learning easier for JVM and Android developers and simplify deploying deep learning models in production environments.
    Downloads: 5 This Week
    Last Update:
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