Showing 9 open source projects for "modes"

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  • 1
    BoxMOT

    BoxMOT

    Pluggable SOTA multi-object tracking modules for segmentation

    ...It also includes evaluation tools and benchmarking pipelines that allow researchers to test tracking performance on standard datasets such as MOT17 and MOT20. The system offers different performance modes that balance computational efficiency with tracking accuracy depending on the application requirements.
    Downloads: 0 This Week
    Last Update:
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  • 2
    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: 2 This Week
    Last Update:
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  • 3
    FiftyOne

    FiftyOne

    The open-source tool for building high-quality datasets

    ...FiftyOne supercharges your machine learning workflows by enabling you to visualize datasets and interpret models faster and more effectively. Improving data quality and understanding your model’s failure modes are the most impactful ways to boost the performance of your model. FiftyOne provides the building blocks for optimizing your dataset analysis pipeline. Use it to get hands-on with your data, including visualizing complex labels, evaluating your models, exploring scenarios of interest, identifying failure modes, finding annotation mistakes, and much more! ...
    Downloads: 0 This Week
    Last Update:
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  • 4
    Velocity server

    Velocity server

    The modern, next-generation Minecraft server proxy

    ...Acting as an intermediary between players and backend servers, Velocity manages player connections and routes them to different game servers within a network. This architecture allows large Minecraft communities to run multiple servers for different game modes while presenting them as a unified system to players. The software is designed with a focus on performance, scalability, and modern architecture, allowing it to handle thousands of simultaneous players efficiently. Velocity also includes a plugin API that allows developers to extend the proxy with custom functionality and integrate it with existing server tools. ...
    Downloads: 7 This Week
    Last Update:
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  • 5
    OneFlow

    OneFlow

    OneFlow is a deep learning framework designed to be user-friendly

    ...Provides a variety of services from primary AI talent training to enterprise-level machine learning lifecycle integrated management (MLOps), including AI training and AI development, and supports three deployment modes of public cloud, private cloud and hybrid cloud.
    Downloads: 0 This Week
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  • 6
    AI-Aimbot

    AI-Aimbot

    CS2, Valorant, Fortnite, APEX, every game

    AI-Aimbot is a computer vision project that demonstrates how artificial intelligence can be used to automatically identify and target opponents in video games. The system uses an object detection model based on the YOLOv5 architecture to detect human-shaped characters in gameplay screenshots or video frames. Once a target is identified, the program automatically adjusts the player’s aim toward the detected target, effectively automating the aiming process in first-person shooter games. The...
    Downloads: 949 This Week
    Last Update:
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  • 7
    Pwnagotchi

    Pwnagotchi

    Deep Reinforcement learning instrumenting bettercap for WiFi pwning

    Pwnagotchi is an A2C-based “AI” powered by bettercap and running on a Raspberry Pi Zero W that learns from its surrounding WiFi environment in order to maximize the crackable WPA key material it captures (either through passive sniffing or by performing deauthentication and association attacks). This material is collected on disk as PCAP files containing any form of handshake supported by hashcat, including full and half WPA handshakes as well as PMKIDs. Instead of merely playing Super Mario...
    Downloads: 2 This Week
    Last Update:
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  • 8
    BerryNet

    BerryNet

    Deep learning gateway on Raspberry Pi and other edge devices

    This project turns edge devices such as Raspberry Pi into an intelligent gateway with deep learning running on it. No internet connection is required, everything is done locally on the edge device itself. Further, multiple edge devices can create a distributed AIoT network. At DT42, we believe that bringing deep learning to edge devices is the trend towards the future. It not only saves costs of data transmission and storage but also makes devices able to respond according to the events...
    Downloads: 0 This Week
    Last Update:
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  • 9
    Neural Networks Collection

    Neural Networks Collection

    Neural Networks Collection

    ...So far the project implements: LVQ in several variants, SOM in several variants, Hopfield network and Perceptron. Other neural network types are planned, but not implemented yet. The project can run in two modes: command line tool and Python 7.2 extension. Currently, Python version appears more functional, as it allows easy interaction with algorithms developed by other people.
    Downloads: 0 This Week
    Last Update:
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