Flower Classification Web App

This project implements a web application for classifying flowers using a Convolutional Neural Network (CNN). The CNN model is trained on the Flower Photos dataset from TensorFlow's example datasets.

Requirements

• Python 3.x
• TensorFlow 2.x
• Gradio

Installation

1. Clone this repository:

   git clone https://github.com/H-Neethika/FlowerClassification_WebApp.git

2. Navigate into the project directory:

   cd FlowerClassification_WebApp

3. Install the required dependencies:

Usage

1. Run all the code:
2. Open your web browser and go to link that will be provided by the gradio to access the application.
3. Upload an image of a flower for classification which should be in the type of sunflowers, dandelion , rose , tulips, daisy .
4. View the predicted class label along with the confidence score for each 5 categories as shown below.