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AgCV:用于自动化计算机视觉应用程序的代理框架
Arav Saxena1, Archana Y Chaudhari1, Anilkumar Gupta2
1Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India.
MethodsX
|July 4, 2025
概括
代理计算机视觉 (AgCV) 框架使用自主代理和自然语言命令自动化复杂的计算机视觉任务. 这种方法提高了各种CV应用程序的可访问性和灵活性.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 机器学习 机器学习
背景情况:
- 传统的计算机视觉 (CV) 管道通常需要大量的技术专业知识.
- 由于复杂的工作流程和各种要求,自动化复杂的CV任务可能具有挑战性.
研究的目的:
- 引入代理计算机视觉 (AgCV) 框架,用于自动化复杂的简历任务.
- 使最终用户能够通过自然语言命令来配置CV操作,减少对专业知识的需求.
主要方法:
- 利用LangGraph进行代理沟通和工作流程编排.
- 整合自然语言处理 (NLP) 和深度学习模型来执行任务.
- 利用检索增强生成 (RAG) 来增强代理能力和用户交互.
主要成果:
- AgCV框架成功地自动化了一系列CV任务,包括对象识别,分类和图像细分.
- 用户驱动的CV管道配置是通过直观的自然语言命令实现的.
- 该框架展示了跨不同领域和用户需求的适应性和可扩展性.
结论:
- 该AgCV框架显著降低了利用先进CV功能进入市场的门.
- 它提供了一种灵活,可访问和用户友好的方法来构建和部署CV应用程序.
- 该系统通过简化互动,使用户的期望与CV操作结果保持一致.
关键词:
AgCV:代理式计算机视觉框架计算机视觉 计算机视觉 计算机视觉格洛克推理引擎 Groq推理引擎法学士 (LLM) 是一个专业.长链 (LangChain) 是一个长链.朗格图 (LangGraph) 是一个长度图.在NLP中,我们使用了NLP.管道自动化 管道自动化 管道自动化获取 - 增强世代的获取视力阻断系统 (AgenticAI) 是一种视力阻断系统.更多相关视频
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