• Open CV with Generative AI and LLM

  • 著者： Anand V
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Open CV with Generative AI and LLM

著者： Anand V
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  • OpenCV, a computer vision library, with Large Language Models (LLMs), which are AI systems designed to understand and generate human language. It covers the fundamentals of both technologies, including their key features and applications. The guide then explores the building blocks for integration, focusing on data preprocessing, feature extraction, and communication between OpenCV and LLMs. It further delves into practical implementations of this integration, covering various tasks like image captioning, object detection with contextual understanding, visual question answering, and scene text
    Anand V
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あらすじ・解説

OpenCV, a computer vision library, with Large Language Models (LLMs), which are AI systems designed to understand and generate human language. It covers the fundamentals of both technologies, including their key features and applications. The guide then explores the building blocks for integration, focusing on data preprocessing, feature extraction, and communication between OpenCV and LLMs. It further delves into practical implementations of this integration, covering various tasks like image captioning, object detection with contextual understanding, visual question answering, and scene text
Anand V
続きを読む 一部表示
エピソード
  • Open CV with Generative AI and LLM

    Open CV with Generative AI and LLM
    2024/10/16

    OpenCV, a computer vision library, with Large Language Models (LLMs), which are AI systems designed to understand and generate human language. It covers the fundamentals of both technologies, including their key features and applications. The guide then explores the building blocks for integration, focusing on data preprocessing, feature extraction, and communication between OpenCV and LLMs. It further delves into practical implementations of this integration, covering various tasks like image captioning, object detection with contextual understanding, visual question answering, and scene text recognition. Finally, the document discusses tools, best practices, and future directions in this field, highlighting emerging technologies, potential applications, and research challenges.

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    12 分

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