Showing 4 open source projects for "fps"

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  • 1
    ViZDoom

    ViZDoom

    Doom-based AI research platform for reinforcement learning

    ...This means compatibility with a huge range of tools and resources that can be used to create custom scenarios, availability of detailed documentation of the engine and tools and support of Doom community. Async and sync single-player and multi-player modes. Fast (up to 7000 fps in sync mode, single-threaded). Lightweight (few MBs). Customizable resolution and rendering parameters. Access to the depth buffer (3D vision). Automatic labeling of game objects visible in the frame. Access to the list of actors/objects and map geometry.ViZDoom API is reinforcement learning friendly (suitable also for learning from demonstration, apprenticeship learning or apprenticeship via inverse reinforcement learning.
    Downloads: 1 This Week
    Last Update:
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  • 2
    DeepFaceLive

    DeepFaceLive

    Real-time face swap for PC streaming or video calls

    ...The quality is not the best, and requires fine face matching and tuning parameters for every face pair, but enough for funny videos and memes or real-time streaming at 25 fps using 35 TFLOPS GPU.
    Downloads: 710 This Week
    Last Update:
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  • 3
    Pytorch Points 3D

    Pytorch Points 3D

    Pytorch framework for doing deep learning on point clouds

    Torch Points 3D is a framework for developing and testing common deep learning models to solve tasks related to unstructured 3D spatial data i.e. Point Clouds. The framework currently integrates some of the best-published architectures and it integrates the most common public datasets for ease of reproducibility. It heavily relies on Pytorch Geometric and Facebook Hydra library thanks for the great work! We aim to build a tool that can be used for benchmarking SOTA models, while also...
    Downloads: 0 This Week
    Last Update:
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  • 4
    UnrealCV

    UnrealCV

    Connecting Computer Vision to Unreal Engine

    UnrealCV is a project to help computer vision researchers build virtual worlds using Unreal Engine (UE). It extends UE with a plugin. UnrealCV can be used in two ways. The first one is using a compiled game binary with UnrealCV embedded. This is as simple as running a game, no knowledge of Unreal Engine is required. The second is installing the UnrealCV plugin into Unreal Engine and using the editor to build a new virtual world.
    Downloads: 1 This Week
    Last Update:
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