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Updated: Sep 17, 2025

Using Computer Vision Libraries to Streamline Nuclei Quantification

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Published on: June 6, 2025

AgCV: An Agentic framework for automating computer vision application.

Arav Saxena¹, Archana Y Chaudhari¹, Anilkumar Gupta²

¹Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India.

|July 4, 2025

Summary

This summary is machine-generated.

The Agentic Computer Vision (AgCV) framework automates complex computer vision tasks using autonomous agents and natural language commands. This approach enhances accessibility and flexibility for diverse CV applications.

Keywords:

AgCV: Agentic Computer Vision Framework Computer vision Groq Inferencing Engine LLM LangChain LangGraph NLP Pipeline automation Retrieval-Augmented Generation Vision block system (AgenticAI)

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Area of Science:

Computer Science
Artificial Intelligence
Machine Learning

Background:

Traditional computer vision (CV) pipelines often require significant technical expertise.
Automating complex CV tasks can be challenging due to intricate workflows and diverse requirements.

Purpose of the Study:

To introduce the Agentic Computer Vision (AgCV) framework for automating complex CV tasks.
To enable end-users to configure CV operations through natural language commands, reducing the need for specialized knowledge.

Main Methods:

Leveraging LangGraph for agent communication and workflow orchestration.
Integrating natural language processing (NLP) and deep learning models for task execution.
Utilizing Retrieval-Augmented Generation (RAG) for enhanced agent capabilities and user interaction.

Main Results:

The AgCV framework successfully automates a range of CV tasks, including object identification, classification, and image segmentation.
User-driven configuration of CV pipelines is achieved through intuitive natural language commands.
The framework demonstrates adaptability and scalability across different domains and user needs.

Conclusions:

The AgCV framework significantly lowers the barrier to entry for utilizing advanced CV capabilities.
It offers a flexible, accessible, and user-friendly approach to building and deploying CV applications.
The system aligns user expectations with CV operation outcomes through simplified interaction.