Flower-Detection-using-Pytorch-Ligthning

This repository contains the code for the Flower Detection using Pytorch Lightning. The dataset used for this project is Flower Classification dataset from Kaggle. The dataset contains 4242 images of flowers. The dataset is divided into 5 categories: Daisy, Dandelion, Rose, Sunflower, and Tulip. The dataset is divided into 70% training and 30% validation.

Requirements

The requirements for the project are:

• Pytorch
• Pytorch Lightning
• Torchvision
• Matplotlib
• Numpy
• Pandas
• Scikit-learn

Usage

To train the model, run the following command:

python train.py

To run inference on the model, run the following command:

python inference.py

Results

The model achieved an accuracy of 85% on the validation set.