Project Information
- Category: Desktop Application
- Client: Fiverr Customer
- Project Date: January 13, 2025
- Project Link: GitHub Repository
Skin Cancer Detection System
Project Description
A Python-based desktop application using artificial intelligence (deep learning) to detect different types of skin cancer from images. Features an intuitive Tkinter interface and leverages a custom-trained TensorFlow/Keras model for accurate image classification.
AI-Powered
Medical Technology
Deep Learning
Key Features
Image Upload
Upload skin lesion images in .jpg, .png, or .jpeg formats for analysis.
AI-Powered Prediction
Analyzes images using a trained deep learning model with high accuracy.
Detailed Results
Displays predicted disease name with confidence percentage.
Image Preview
Shows selected image within the application interface.
Intuitive UI
Modern interface with real-time feedback and error handling.
Multiple Cancer Types
Detects 7 different types of skin cancer and lesions.
Detected Skin Cancer Types
Actinic Keratoses (AKIEC)
Basal Cell Carcinoma (BCC)
Benign Keratosis (BKL)
Dermatofibroma (DF)
Melanoma (MEL)
Melanocytic Nevi (NV)
Vascular Lesions (VASC)
Technologies Used
Py
Python
TF
TensorFlow
TK
Tkinter
CV
OpenCV
Project Repository
This project is open-source and available on GitHub. Feel free to explore the code, contribute, or use it for educational purposes.
View on GitHub