Tray API

Tray API is a web application designed for food image classification using machine learning techniques. It provides various endpoints for classifying food images, detecting ingredients, recognizing cuisines, and predicting nutrition.

Features (Not finished)

• Food Image Classification: Classify images of food into various categories.
• Ingredient Detection: Identify ingredients present in food images.
• Cuisine Recognition: Recognize the cuisine type of the food.
• Nutrition Prediction: Predict nutritional information based on the food image.
• User-Friendly Interface: Easy navigation with a responsive design.
• Chatbot Assistance: Interactive chatbot for user queries.

Technologies Used

• Backend: Flask (Python)
• Frontend: HTML, CSS, JavaScript (Bootstrap for styling)
• Machine Learning: TensorFlow, Keras
• Data Storage: JSON files for blog posts and chat logs

Installation

1. Clone the repository:

   git clone https://github.com/ssbdragonfly/tray-api.git
   cd tray-api

2. Install the required packages:

   pip install -r requirements.txt

3. Set up environment variables:

   • Create a .env file and add your SECRET_KEY.

4. Run the application:

   python website/app.py

5. Access the application at http://127.0.0.1:5000.

Usage

• Home Page: Provides links to various API functionalities.
• Documentation: Comprehensive guides on how to use the API.
• Blog: Regular updates and insights about food classification and machine learning.
• Performance Metrics: View the accuracy and speed of the API.
• History: Users can view their past image classifications.
• FAQ: Answers to common questions about the service.
• Contact: Reach out to the developers for support.

Contributing

Contributions are welcome! Please fork the repository and submit a pull request for any enhancements or bug fixes.

License

This project is licensed under the MIT License.

Contact

For any inquiries, please contact:

• Shaurya Bisht: [email protected]