A web application designed to help users detect the likelihood of malignant skin cancer using advanced machine learning techniques.
The frontend is built using React and Tailwind CSS, while the backend is powered by a Python Flask API that processes uploaded images and communicates with a convolutional neural network (CNN) model. The model is trained on a dataset of skin lesion images to classify the likelihood of malignant skin cancer.
Make sure you have the following installed on your system:
- Python (Version 3.8 or higher)
- Node.js (Version 16 or higher)
- npm (comes with Node.js)
- pip (Python package manager)
- Git (optional, for cloning the repository)
git clone https://github.com/your-username/skin-cancer-classification.git
cd skin-cancer-classification Backend Setup a. Create a Virtual Environment b. Activate the Virtual Environment Windows: venv\Scripts\activate macOS/Linux: venv/bin/activate
c. Install Dependencies pip install -r requirements.txt
d. Start the Backend Server uvicorn main:app --reload --port 5000
The backend server will run at: 👉 http://127.0.0.1:5000
Frontend Setup a. Navigate to the Frontend Directory cd frontend b. Install Dependencies npm install
c. Start the Frontend Development Server npm run dev
The frontend will run at: 👉 http://127.0.0.1:5173
🧪 How to Use Find a Dermatologist 1. Go to the "Find a Dermatologist" page. 2. Enter a name in the search bar. 3. Click the Search button to view results.
🖼️ Skin Cancer Detection 1. Go to the "Home" page. 2. Upload an image of a skin lesion. 3. Click the Predict button.
