FastAPI Crop Disease Prediction API

This repository contains a FastAPI application for predicting crop diseases using a trained machine learning model. The API allows users to upload an image of a crop leaf and receive a prediction regarding the disease affecting the plant.

Table of Contents

• Project Overview
• Requirements
• Installation
• Running the Application
• API Endpoints
• License

Project Overview

The API uses a pre-trained machine learning model to classify images of crop leaves into various disease categories. The model is loaded and used for inference when an image is uploaded to the /predict endpoint.

Requirements

• Python 3.9+
• Docker (optional, for containerized deployment)
• FastAPI
• TensorFlow/Keras
• Other dependencies specified in requirements.txt

Reference

Installation

Clone the Repository

git clone https://github.com/krishnaGauss/Crop-Disease-MLModelAPI.git

Running the Application

On local machine:

1)Install dependencies

pip install -r requirements.txt

2)In terminal type:

uvicorn main:app --reload

Server URL:

• The API is currently running on the URL: [https://google-clouddeploy-238365468738.us-central1.run.app/predict/] upload images to get JSON output.
• Can also refer to our another github repository for more insight : [https://github.com/krishnaGauss/Plant-Disease-Prediction-Model-Kaggle.git]

API Endpoints

• Endpoint : /predict
• Method : POST
• Description : Upload an image of a crop leaf to receive a prediction about the disease.
• Request Body : Multipart form-data with a file field named file

Customization

Feel free to reach out if you have any additional requests or questions!