PicMenu: Convert text menus into beautiful graphic menus

General Introduction

PicMenu is an innovative AI tool that transforms traditional paper menus into vivid and intuitive picture menus through a simple photo operation. The tool not only automatically generates high-quality images of each dish, but also provides rich information about the dishes, providing a new solution for the digital transformation of the restaurant industry.

Online demo: (Chinese not adapted) https://www.picmenu.co/

Function List

• Menu Image Generation: Generate high quality images of each dish by taking photos.
• Menu Information Extraction: Use AI models to extract menu item information from images.
• Structured Data Generation: Generate structured data (JSON format) containing dish information.
• Detailed information on dishes: In the future, detailed information on ingredients, sources, calories, flavors, etc. will be provided.
• Multi-language support: plan to extend multi-language support to provide menu display in multiple languages.
• Labeling system: A labeling system for dishes, such as spicy and vegetarian, will be introduced to facilitate personalized choices.
• Data Analysis and Monitoring: Integrate with Plausible and Helicone for data analysis and performance monitoring.

Using Help

Installation process

1. Cloning Warehouse:git clone https://github.com/Nutlope/picmenu
2. establish .env file and add the Together AI API key:TOGETHER_API_KEY=
3. Create an S3 storage bucket and add credentials to the .env file. All required values are in the .env.example Documentation.
4. (of a computer) run npm install cap (a poem) npm run dev to install dependencies and run them locally.

Usage Process

1. Photo upload: Users just need to take a photo of the menu and upload it, the system will automatically recognize and extract the dish information.
2. Dish Image Generation: The system generates a high quality image of each dish and displays it on the interface.
3. Display of dish information: Clicking on the image of a dish, the system will display detailed information about the dish (e.g., ingredients, sources, calories, flavors, etc.).
4. Tag filtering: Users can filter dishes based on tags (e.g. spicy, vegetarian, etc.) to facilitate personalized selection.
5. Data Analytics: Integrated Plausible and Helicone tools analyze and monitor user behavior and system performance to help optimize the user experience.

future functions

• Enhancing the realism of dish images: by improving the image generation algorithm, the generated dish images are more realistic.
• Infinite scrolling function: optimize the loading state and improve user experience.
• Multi-language support: Extend multi-language support to provide menu display in more languages.
• Label Filtering System: Introduces a label-based filtering system that facilitates users to filter dishes according to their dietary preferences.