Showing 4 open source projects for "visual%20scraper"

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  • Automate contact and company data extraction Icon
    Automate contact and company data extraction

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  • 1
    Self-Operating Computer

    Self-Operating Computer

    A framework to enable multimodal models to operate a computer

    ...Notably, it was the first known project to implement a multimodal model capable of viewing and controlling a computer screen. The framework supports features like Optical Character Recognition (OCR) and Set-of-Mark (SoM) prompting to enhance visual grounding capabilities. It is designed to be compatible with macOS, Windows, and Linux (with X server installed), and is released under the MIT license.
    Downloads: 4 This Week
    Last Update:
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  • 2
    Android Use

    Android Use

    Automate native Android apps with AI using accessibility APIs

    android-action-kernel is an open source Python library designed to let AI agents control and automate native Android applications running on real devices or emulators. It fills a gap in automation tooling by focusing on mobile-first workflows where traditional browser or desktop-based automation doesn’t work; such as logistics, gig work, field operations, and other industries reliant on phones or tablets. The project works by using Android’s accessibility API to extract structured UI state...
    Downloads: 3 This Week
    Last Update:
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  • 3
    airda

    airda

    airda(Air Data Agent

    airda(Air Data Agent) is a multi-smart body for data analysis, capable of understanding data development and data analysis needs, understanding data, generating data-oriented queries, data visualization, machine learning and other tasks of SQL and Python codes.
    Downloads: 0 This Week
    Last Update:
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  • 4
    Universe Starter Agent

    Universe Starter Agent

    A starter agent that can solve a number of universe environments

    The universe-starter-agent repository is an archived OpenAI codebase designed as a starter reinforcement-learning agent that can interact with and solve tasks in OpenAI’s Universe environment platform. Its purpose is to serve as a baseline or reference implementation so researchers or developers can see how to build agents that operate in real-time, visual environments (e.g., games, browser apps) via pixel observations and keyboard/mouse actions. Under the hood, this starter agent implements a version of the A3C (Asynchronous Advantage Actor-Critic) algorithm, adapted for the specific challenges of Universe environments (e.g., network latency, VNC streaming, asynchronous observations). ...
    Downloads: 0 This Week
    Last Update:
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