Lovable Prompt Creator - AI Prompt Generator

## APPLICATION OVERVIEW
This web application will leverage camera functionality to recognize objects and determine their freshness. Users can capture images of products, and the app will analyze the packaging to identify the product type through text recognition. The goal is to provide a seamless experience for users looking to assess the quality of their food items through advanced image processing.

## CORE FEATURES
1. **Camera Integration**: Allows users to open the camera directly from the app and capture images of products.
2. **Object Recognition**: Utilizes machine learning algorithms to identify whether the captured product is fresh or not.
3. **Text Recognition**: Analyzes the packaging to read labels and identify the type of product using Optical Character Recognition (OCR).
4. **Results Display**: Provides a user-friendly interface to display the results of the recognition, including product freshness and type.
5. **History Log**: Maintains a history of previously scanned products for user reference.
6. **User Feedback**: Allows users to provide feedback on the accuracy of the recognition results for continuous improvement.

## DESIGN SPECIFICATIONS
- **Visual Style**: Minimalist - Clean, simple design with plenty of white space, minimal color palette, and a strong emphasis on typography.
- **Color Mode**: Light theme with dark text on light backgrounds to enhance readability and user comfort.
- **Layout**: A single-page layout with a prominent camera interface at the top, followed by results and history sections. Each section should be clearly defined with ample spacing to avoid clutter.
- **Typography**: Use modern sans-serif fonts for headings and body text, maintaining a clear hierarchy (e.g., larger bold for headings, regular weight for body text).

## TECHNICAL REQUIREMENTS
- **Framework**: React with TypeScript for strong typing and component-based architecture.
- **Styling**: Tailwind CSS for utility-first styling, ensuring responsiveness and quick design adjustments.
- **UI Components**: shadcn/ui for pre-built, customizable components that align with the minimalist aesthetic.
- **State Management**: React Context API or Zustand for managing application state across components.

## IMPLEMENTATION STEPS
1. **Set Up Project**: Initialize a new React project with TypeScript, install Tailwind CSS, and configure shadcn/ui.
2. **Camera Integration**: Implement camera functionality using the HTML5 `<video>` and `<canvas>` elements for capturing images.
3. **Object and Text Recognition**: Integrate machine learning models for object detection and OCR capabilities.
4. **Results Display**: Create components to display recognition results, including product freshness and type, ensuring they are clearly visible and easy to understand.
5. **History Log**: Develop a section to store and display previously scanned products, utilizing local storage or a simple database.
6. **User Feedback Mechanism**: Implement a feedback form for users to report inaccuracies, which could help improve the recognition algorithms over time.

## USER EXPERIENCE
The user experience will focus on simplicity and efficiency. Users will open the app and immediately see the camera interface, allowing them to take a picture with minimal distractions. Once the image is captured, results will be displayed quickly, showing whether the product is fresh and what type of product it is. Users can easily navigate to their history log to view past scans and provide feedback on the results, enhancing engagement and usability. The overall design will ensure that users have a pleasant and intuitive experience while using the app.