Skin Cancer

Project Overview

The Memanoma Detector is a web application designed to analyze skin images for the presence of potential skin diseases, particularly focusing on melanoma detection. Users can upload an image, and the application will process it to determine if there are any signs of skin cancer. The result will be displayed along with a confidence percentage.

Screenshot

Key Features

1. Image Upload

• Users can upload skin images directly from the first page of the website.
• Supports various image formats (e.g., JPEG, PNG).

2. Image Processing

• The uploaded image is processed to extract relevant features for analysis.

3. Skin Cancer Detection

• Utilizes advanced machine learning models to classify the image into two categories: skin cancer or normal skin.

4.Result Display

• Displays the processed image along with the classification result.
• Provides a confidence percentage indicating the likelihood of skin cancer.

Getting Started

To run the Memanoma Detector locally, follow these steps:

1. Clone the repository.

  git clone https://github.com/ankitaniket/skincancer_123.git

2. Navigate to the project directory:

cd skincancer_123

3. Install the necessary dependencies.

pip install -r requirements.txt

4. Launch the application by running the app.py file:

python app.py

Open your web browser and go to http://localhost:8000 to access the Memanoma Detector.