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Screenshot 2024-07-19 184140


Diagnose

Skin cancer detection from your skin images.

Watch Demo Video - Click here

Project Overview

Melanoma is a type of skin cancer that can be deadly if not detected early. It accounts for 75% of skin cancer deaths. A solution which can evaluate images and alert the dermatologists about the presence of melanoma has the potential to reduce a lot of manual effort needed in diagnosis.

Our application detects the following skin diseases:

  • Actinic keratosis
  • Basal cell carcinoma
  • Dermatofibroma
  • Melanoma
  • Nevus
  • Pigmented benign keratosis
  • Seborrheic keratosis
  • Squamous cell carcinoma
  • Vascular lesion

Technology Stack Used:

  • Python
  • Machine Learning
  • Streamlit

APIs used

How it works?

Our application utilizes machine learning to predict what skin disease you may have, from your skin images! We then recommend you specialized doctors based on your type of skin diseases.

Screenshots

Screenshot 2024-07-19 185943

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Screenshot 2024-07-19 190231

Demo Video

clideo_editor_b6ab2c2619494c5cac653c9ff90865a2.1.mp4

Setting up Local Development

  1. Clone the repository
git clone https://github.com/coder12git/Diagnose.git
  1. Navigate to the project folder
cd Diagnose/
  1. Create a virtual environment
python3 -m venv venv
  1. Activate the virtual environment

for Linux and Mac:

source venv/bin/activate

for Windows:

venv\Scripts\activate
  1. Install dependencies
pip install -r requirements.txt
  1. Run the app
streamlit run ./About.py

Thanks for visiting!