This project is a skin disease classification website using a convolutional neural network (CNN) model built with Django. The model has been trained on a dataset consisting of approximately 15,500 images of 23 different types of skin diseases, taken from https://www.kaggle.com/datasets/shubhamgoel27/dermnet.

The dataset consists of approximately 15,500 images of 23 different types of skin diseases taken from https://www.kaggle.com/datasets/shubhamgoel27/dermnet. The dataset has been split into training and test sets.

The types of skin diseases in the dataset are:

The Convolutional Neural Network (CNN) model has been trained using the training set of images. The model has been designed to classify skin disease images into one of the five categories mentioned above. The CNN model has been implemented using Keras, which is a high-level neural networks API, written in Python and capable of running on top of TensorFlow.

The website is designed to take an image of the skin disease and classify it into one of the five categories. Follow the below steps to use the website:

Upload an image of the skin disease. Click on the "Predict" button. The website will show the category in which the skin disease image belongs with an Advice .

Clone this repository to your local machine. Install the required dependencies using the command pip install -r requirements.txt. Run the Django server using the command python manage.py runserver. Go to your web browser and navigate to http://localhost:127.0.0.1.

live demo of the skin disease classification website is available at https://youtu.be/rcorCEByhYk

This project was developed by NewGenic. If you have any questions or suggestions, please feel free to contact us at newgenic8@gmail.com. We welcome contributions to the project.