Skin Condition Detection and Skincare Advice

This is a Streamlit-based web application for detecting various skin conditions from uploaded images using a YOLO model. The application provides tailored skincare advice, recommended products, and prevention tips for detected conditions.

Features

• Skin Condition Detection: Detects common skin conditions like acne, wrinkles, dry skin, oily skin, eyebags, and more.
• Skincare Advice: Provides actionable advice, recommended products, and prevention tips for each detected condition.
• Interactive UI: Upload an image and view detection results with bounding boxes and confidence scores.
• Supports YOLO Models: Utilizes custom-trained YOLO models for skin condition detection.

Streamlit Deploy

🎯 Check out my streamlit app: https://facecare.streamlit.app/

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Installation

Prerequisites

• Python 3.9+
• pip package manager

Clone the Repository

git clone https://github.com/your-username/skin-condition-detection.git
cd skin-condition-detection

Install Dependencies

pip install -r requirements.txt

Additional Dependency for Deployment

If deploying on Streamlit Cloud, create a packages.txt file and include:

libgl1

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Usage

Run the Application Locally

streamlit run app.py

Upload an Image

• Upload a .jpg, .jpeg, .png, or .webp file.
• The app will display:
  • Original image with detections.
  • Skincare advice for detected conditions.

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File Structure

.
├── app.py                 # Main application file
├── requirements.txt       # Python dependencies
├── packages.txt           # Additional packages for deployment (optional)
├── skincond.pt            # YOLO model for skin condition detection
└── README.md              # Project documentation

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YOLO Model

This project uses a custom-trained YOLO model (skincond.pt) to detect six skin conditions:

• Acne
• Dry Skin
• Eyebags
• Normal Skin
• Oily Skin
• Wrinkles

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Deployment

Streamlit Cloud

1. Push the repository to GitHub.
2. Connect the repository to Streamlit Cloud.
3. Ensure the packages.txt file is included with the following:

   libgl1
   

Docker

Include the following in your Dockerfile:

RUN apt-get update && apt-get install -y libgl1

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Example Outputs

Input Image

Uploaded via Streamlit interface.

Detection Results

Skincare Advice

Condition: Acne
Advice: Keep your skin clean, avoid harsh scrubbing, and avoid touching your face frequently.
Recommended Products:
- Salicylic Acid Cleanser
- Benzoyl Peroxide Cream
- Non-comedogenic Moisturizer
Prevention Tips:
- Wash your face twice daily with a mild cleanser.
- Avoid oily makeup products.
- Maintain a balanced diet with less sugar and processed foods.

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Contributing

Contributions are welcome! Please follow these steps:

1. Fork this repository.
2. Create a new branch.
3. Commit your changes.
4. Submit a pull request.

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License

This project is licensed under the MIT License.

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Author

Developed by Pyae Linn.