AI-Based Medicinal Plant Leaf Analysis System

surya saketh — Fri, 03 Apr 2026 14:24:31 +0000

Introduction

Medicinal plants play a critical role in traditional healthcare systems such as Ayurveda. However, identifying plant species and detecting diseases from leaf images typically requires expert knowledge.

To address this, I built a full-stack AI application that can:

Identify medicinal plants from leaf images
Detect whether the leaf is healthy or diseased
Provide structured outputs such as scientific name, medicinal properties, and care recommendations

This project combines computer vision, backend APIs, and a modern frontend into a single deployable system.

Problem Statement

The main challenges this project addresses:

Lack of accessible tools for plant identification
Difficulty in early disease detection
Dependence on domain experts
Limited awareness of medicinal uses and remedies

The goal was to build a system that makes this process automated and accessible.

Problem Statement

The main challenges this project addresses:

Lack of accessible tools for plant identification
Difficulty in early disease detection
Dependence on domain experts
Limited awareness of medicinal uses and remedies

The goal was to build a system that makes this process automated and accessible.

Tech Stack

System Architecture

The system is divided into three layers:

Frontend

Image upload interface
Displays prediction results

Backend (FastAPI)

Handles file uploads
Runs model inference
Returns structured JSON response

ML Model

Trained on labeled medicinal plant datasets
Classifies plant type and health status

Model Training Pipeline

The model training involved:

Organizing dataset into class folders
Preprocessing:

  1. Resizing to 224×224
  2. Normalization

Data augmentation:

 1. Rotationz
 2. Flipping
 3. Color jitter

Train/validation/test split

Transfer learning was used with a pretrained model to improve performance.

Prediction Workflow

User uploads a leaf image
Backend saves the image temporarily
Image is passed to the trained model
Model outputs: class_name, confidence, class_index
Backend maps the class to structured data using a knowledge file
Response is returned to frontend

Key Features

Medicinal plant identification
Disease detection (healthy vs diseased)
Confidence-based predictions
Knowledge integration (scientific name, properties, remedies)
Unknown class handling for non-medicinal inputs
Real-time API-based inference

Conclusion

This project demonstrates how AI can be used to make traditional knowledge systems more accessible. By combining computer vision with a structured knowledge base, the system provides meaningful insights beyond basic classification.

Links
GitHub Repo: https://github.com/saketh10-10/Medicinal-plant-leaf-disease-detection
LinkedIn: https://www.linkedin.com/feed/update/urn:li:activity:7428844593728688129/?originTrackingId=1XU4D7RC3aOmWI7Q%2F7P%2BGg%3D%3D

DEV Community: surya saketh

AI-Based Medicinal Plant Leaf Analysis System

Introduction

Problem Statement

Problem Statement

Tech Stack

Model Training Pipeline

Prediction Workflow

Key Features

Conclusion