Used to track the user's bowel movements with AI camera recognition to determine the rating based on the Bristol Stool Chart. Then returns feedback to the user with a tailored course-of-action to improve their stool quality.

Stool Tracker is a dedicated health companion that simplifies the process of monitoring bowel movements. By focusing on a clean, non-intimidating user interface, the app encourages consistent logging to help users identify patterns in their digestive health.

Core Components: Intelligent Dashboard: Displays a personalized greeting and a "Weekly Summary" card that calculates your total bowel movements for the week.

Visual History (Dot Logic): A functional calendar system that uses color-coded dots to visualize frequency without overwhelming the user:

1 Dot: Once a day.

2 Dots: Twice a day.

3 Dots: Three or more times.

Action-Oriented Navigation: Features a "popped-out" center camera button for quick entry, ensuring that logging a new event is always one tap away.

Actionable Insights: A dedicated tips section provides distinguishable health advice to help users naturally improve their gut health.

• Node (v14+)
• Python (3.11+) (Note: 3.13 is currently incompatible with certain ML dependencies)

Step-by-step instructions on how to install and set up the app.

1. Clone the repository:

 git clone https://github.com/Ramenrw/stool-tracker-app.git

2. Navigate to the project directory:

   cd stool-tracker-app

3. Install NPM packages:

   npm install

4. Install project-specific libraries:

   npx expo install react-native-calendars lucide-react-native

To run the application, you need to start both the Python backend and the Expo frontend.

1. Start the Backend

cd backend
# Activate virtual environment
source venv/bin/activate  # On macOS/Linux
venv\Scripts\activate   # On Windows Command Prompt
.\venv\Scripts\Activate.ps1 # On Windows PowerShell

# Run the server
python main.py

2. Start the Frontend In a new terminal window, from the root directory:

npx expo start

3. Launch the app For Android or iOS, simply download Expo Go on your mobile device and scan the QR code shown in the frontend terminal window! For web testing, press w in the frontend terminal window.

4. Set up your configuration Ensure that the API_URL with aligns with the output of

ipconfig getifaddr en0

Frontend: React Native with Expo (TypeScript)

Backend: FastAPI (Python)

Database: SQLite

Machine Learning: TensorFlow Lite. Uses a quantized 793 KB model trained on a custom dataset of 150+ stool images for high-precision, on-device classification.

UI/Icons: Lucide-React-Native & FontAwesome5

Navigation: React Navigation (Stack & Tab)