https://github.com/knaveen1705/potato-leaf-disease-detection

A Potato Leaf Disease Classification system that uses deep learning to detect diseases in potato leaves. This repository contains Deep learning model and backend API to process and serve predictions.
https://github.com/knaveen1705/potato-leaf-disease-detection

cnn-classification deep-learning flaskapi tensorflow tensorflow2

Last synced: 5 days ago
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A Potato Leaf Disease Classification system that uses deep learning to detect diseases in potato leaves. This repository contains Deep learning model and backend API to process and serve predictions.

• Host: GitHub
• URL: https://github.com/knaveen1705/potato-leaf-disease-detection
• Owner: KNAVEEN1705
• Created: 2024-12-27T04:38:16.000Z (8 days ago)
• Default Branch: main
• Last Pushed: 2024-12-27T05:35:35.000Z (8 days ago)
• Last Synced: 2024-12-27T06:17:56.542Z (8 days ago)
• Topics: cnn-classification, deep-learning, flaskapi, tensorflow, tensorflow2
• Language: Jupyter Notebook
• Homepage:
• Size: 42.6 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Potato Leaf Disease Classification - Backend and Machine Learning

This repository contains the backend and machine learning code for the **Potato Leaf Disease Classification** project. The backend is built using **Flask** or **FastAPI**, and the machine learning model is built using **TensorFlow/Keras**.

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## Features

- **Machine Learning Model**: Uses a pre-trained model for classifying potato leaf diseases.

- **API**: A REST API to interact with the model, receiving image input and returning classification results.

- **Flask/FastAPI Backend**: Lightweight web framework to expose the ML model to the frontend.

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## Prerequisites

Ensure the following are installed:

- Python 3.7+

- pip (Python package installer)

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## Installation

### 1. Clone the Repository

 

`git clone https://github.com/KNAVEEN1705/potato-leaf-disease-detection.git `

### 2. Navigate to the Backend Directory

`cd potato-leaf-disease-detection/backend`

### 3. Set Up Virtual Environment (Recommended)

Create and activate a virtual environment to manage project dependencies:

`python -m venv venv`

- Activate the virtual environment:

`.\venv\Scripts\activate`

- Mac/Linux:

`source venv/bin/activate`

### 4. Install Dependencies

Install the required Python libraries:

`pip install -r requirements.txt`

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##  Running the Application

### 1. Start the Backend API

Run the backend server using Flask or FastAPI. For Flask:

`python main.py`

-------------------------------------------------------------------------------

## Frontend Code

The frontend code for this project can be found in the same repository. Access it [here](https://github.com/KNAVEEN1705/potato-leaf-disease-detection-Frontend-code).