Sketch2App

Converts hand-drawn wireframes (paper or tablet sketches) into clickable HTML/CSS prototypes by combining computer vision for element detection with automatic interaction flow inference. Uses OCR and shape recognition to identify UI components (buttons, text fields, navigation elements) and their spatial relationships, then generates a functional prototype with basic interactivity without manual recreation.

Identifies and classifies hand-drawn UI components (buttons, text fields, checkboxes, navigation bars, images) using computer vision and machine learning models trained on sketch patterns. Analyzes shape, size, position, and contextual cues to determine component type and semantic role within the layout, enabling automatic code generation for each identified element.

Automatically infers navigation and interaction flows from spatial relationships and element positioning in sketches, creating clickable connections between screens without explicit user annotation. Analyzes button placement, proximity to navigation elements, and layout patterns to generate reasonable default interactions (e.g., button clicks navigate to next screen, form submissions trigger confirmation screens).

Applies computer vision preprocessing to raw sketch images to improve OCR and element detection accuracy, including contrast enhancement, skew correction, noise reduction, and line thickening. Normalizes variations in pen pressure, ink consistency, and image quality to create a standardized input for downstream ML models, compensating for the inherent variability of hand-drawn input.

Generates functional HTML and CSS code from detected UI elements and inferred layouts, creating a responsive prototype that can be previewed in a web browser. Maps detected components to semantic HTML elements (buttons, inputs, divs) and generates CSS for positioning, sizing, and basic styling based on sketch appearance (colors, text styles, spacing inferred from sketch).

Extracts handwritten and printed text from sketch images using optical character recognition (OCR), converting hand-drawn labels, button text, and form field placeholders into machine-readable text. Handles variable handwriting styles, sketch-specific text characteristics (often larger, less uniform than printed text), and contextual text placement to populate generated prototypes with actual content.

Provides a web-based preview environment where generated prototypes can be viewed, interacted with, and tested in real-time without export or additional tools. Enables clicking through navigation flows, testing form inputs, and validating interaction logic directly in the browser, with responsive preview modes for different screen sizes.

Exports generated prototypes as downloadable HTML/CSS files that can be imported into code editors, version control systems, or development environments for further customization and refinement. Provides clean, readable code structure with comments and semantic HTML to enable developers to extend functionality, integrate with backends, or apply design system standards.