Showing 4 open source projects for "python q learning"

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    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! https://docs.opencv.org/master Books about the OpenCV are described here: https://opencv.org/books.html
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    Downloads: 19,884 This Week
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  • 2
    EnCodec

    EnCodec

    State-of-the-art deep learning based audio codec

    Encodec is a neural audio codec developed by Meta for high-fidelity, low-bitrate audio compression using end-to-end deep learning. Unlike traditional codecs (like MP3 or Opus), Encodec uses a learned quantizer and decoder to reconstruct complex waveforms with remarkable accuracy at bitrates as low as 1.5 kbps. It employs a convolutional encoder–decoder architecture trained with perceptual loss functions that optimize for human auditory quality rather than raw waveform distance. The model can...
    Downloads: 0 This Week
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  • 3

    FastoCloud PRO

    IPTV/NVR/CCTV/Video cloud https://fastocloud.com

    IPTV/Video cloud Features: Cross-platform (Linux, MacOSX, FreeBSD, Raspbian/Armbian) GPU/CPU Encode/Decode/Post Processing Stream statistics CCTV Adaptive hls streams Load balancing Temporary urls HLS push EPG scanning Subtitles to text conversions AD insertion Logo overlay Video effects Relays Timeshifts Catchups Playlists Restream/Transcode from online streaming services like Youtube, Twitch ...
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  • 4
    Bullet

    Bullet

    JVM Bullet Physics SDK

    Bullet is real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc. Jvm port of Bullet, by Erwin Coumans. Take a look at the tests to see what has been ported and tested to be working. A high-end desktop GPU, such as an AMD Radeon 7970 or NVIDIA GTX 680 or better. We succesfully tested the software under Windows, Linux and Mac OSX. The software currently doesn't work on OpenCL CPU devices. It might run on a laptop GPU but...
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