Refactor the AI Analysis Pipeline into a Modular Plugin Architecture

[Komal2008]

Description

The current AI analysis flow is tightly coupled, making it difficult to extend with new analysis modules.

Refactor the pipeline into a modular plugin-based architecture where each analysis stage (image quality, damage detection, fraud assessment, decision engine) is implemented as an independent component.

Objectives

• Decouple AI modules.
• Improve maintainability.
• Make it easy to add new analyzers.
• Reduce code duplication.

Proposed Structure

src/
├── analyzers/
│   ├── image_quality.py
│   ├── damage_detector.py
│   ├── fraud_detector.py
│   └── severity_estimator.py
│
├── pipeline.py
└── decision_engine.py

Acceptance Criteria

• Existing functionality remains unchanged.
• Analysis modules are independent.
• New analyzers can be added with minimal code changes.
• Documentation updated.

Difficulty

Hard

[Payal29037]

Hi! I'd like to work on this issue as part of ECSoC. Could you please assign it to me?

[Sk-Uruj]

Heyyy @Komal2008 as i am currently deep diving into computer vision i would love to work on this issue ! Kindly assign it to me