/Plant-Image-Classification-iOS-App

An intelligent application designed to assist home plant owners in growing their plants better. It incorporates machine learning models to classify and recognize plants, identify diseased or unhealthy parts, and provide recommendations for plant care. The app also includes a user-friendly interface.

Primary LanguageSwift

Plant-Image-Classification-iOS-App

An intelligent application designed to assist home plant owners in growing their plants better. It incorporates machine learning models to classify and recognize plants, identify diseased or unhealthy parts, and provide recommendations for plant care. The app also includes a user-friendly interface.

Introduction

An iOS application that uses convolutional neural networks (CNNs) to classify and recognize plants, identify diseased or unhealthy parts of the plant, and provide recommendations for plant care. The app uses the PlantVillage Dataset and a custom dataset for 50 plants to train the machine learning models. The app is built using Swift and Xcode.

Functionality

The app's functionality includes:

  • Classification and recognition of plants using machine learning models
  • Identification of diseased or unhealthy parts of the plant through segmentation
  • Recommendations and advice for plant care based on images of the plant

Design and Build Methodologies

The app is built using Swift and Xcode, and the development process involved experimentation, product genesis, and focused development. The machine learning models used in the app are based on convolutional neural networks (CNNs) and were trained using libraries such as FastAI and TensorFlow.

Machine Learning Models

The app uses convolutional neural networks (CNNs) to classify and recognize plants, identify diseased or unhealthy parts of the plant, and provide recommendations for plant care. The machine learning models used in the app are based on the PlantVillage Dataset and a custom dataset for 50 plants. The models were trained using libraries such as FastAI and TensorFlow.

User Interface

The app's user interface is designed to be user-friendly and intuitive. Users can take a picture of their plant and receive AI-generated feedback on plant health, supplemented by information on key factors such as recommended environmental conditions and watering/nutrient requirements.

Compatibility

The app is compatible with the iOS ecosystem and is built using Swift and Xcode. The app is designed to work on iOS devices running iOS 12.0 or later.

Getting Started

To get started with the Plant-Image-Classification-iOS-App, follow these steps:

  1. Clone the repository from GitHub.
  2. Open the project in Xcode.
  3. Build and run the app on a simulator or a physical device.

Prerequisites

  • Xcode 12.0 or later
  • Swift 5.0 or later
  • macOS 10.15.4 or later

Installation

  1. Clone the repository.
    git clone https://github.com/arnavhazra/Plant-Image-Classification-iOS-App.git
  2. Open the project in Xcode.
  3. Build and run the app on a simulator or a physical device.

Acknowledgments

  • The PlantVillage Dataset
  • FastAI
  • TensorFlow