Stop rebuilding UI by hand.
Auto UI Generator converts Figma, Photoshop exports, and screenshots into clean Unity layouts. Exports to UGUI (Unity Canvas) and UI Toolkit (UXML + USS).Supported Operating System : Windows (Required)Online Documentation: Auto UI Generator DocsWith this asset, you can convert UI layouts from Figma, Photoshop, or screenshots into Unity automatically.Auto UI Generator analyzes static UI mockups using AI-powered image detection and OCR, then generates clean, production-ready Unity hierarchies in seconds.Core CapabilitiesConverts Figma, Photoshop exports, and screenshots into Unity UGUI and UI ToolkitPreserves logical layout hierarchy, element order, and structureDetects UI elements automatically (Image, Button, Text, etc.)Reads text using OCR and generates TextMeshPro componentsMatches detected elements with your existing project spritesGenerates clean RectTransform data with correct anchoring and positioningAvoids unnecessary duplicate UI elements during generationRuns offline — no cloud services or external serversAutomatically Creates Unity ComponentsImageButtonTextMeshProUGUIScroll View (with Viewport and Content setup)RectTransform hierarchyCanvas-compatible layoutsUI Toolkit structure (UXML layout + USS styling)Smart detection of Images, Buttons, and Text from a single mockup while preserving original hierarchyBuilt-in OCR engine to extract text and generate Unity Text or TextMeshPro componentsAdaptive layout system with correct anchoring, positioning, and Z-order managementAutomatic sprite matching based on visual similarity to reuse existing project assetsClean generation of Unity UGUI (Canvas) hierarchiesExport support for UI Toolkit (UXML + USS)Scroll View auto-setup (Viewport + Content)Duplicate element prevention during generationFully offline processing (no cloud or external servers required)Custom ML-Based UI Element ClassificationThe package uses a trained classical machine learning classifier to detect button-like UI elements from design mockups. Each candidate image is processed through grayscale normalization, Canny edge detection, and morphological refinement. Feature extraction combines HOG descriptors, edge-focused HOG, Hu Moments, and edge density metrics. These features are scaled and evaluated by the trained model to produce robust classification with confidence scoring.Feature Engineering for Fast, Lightweight InferenceInstead of relying on heavy deep learning stacks for every UI shape decision, the system uses handcrafted computer vision features (HOG + geometric descriptors). This design keeps inference fast, lightweight, and stable for production pipelines while preserving strong detection quality on common UI patterns.OCR Integration via ONNX RuntimeThe package integrates RapidOCR (ONNX-based) to extract text directly from flattened mockups. OCR results are cleaned and normalized, then mapped into Unity-ready text components, reducing manual text recreation effort and improving end-to-end automation.Intelligent Layout & Geometry ProcessingBounding boxes, spatial relationships, and geometric analysis are used to infer element hierarchy, relative positioning, and layout structure. This enables cleaner UI reconstruction in Unity, including responsive anchoring behavior and consistent visual ordering.Fully Offline AI PipelineAll inference runs locally using OpenCV, scikit-image, ONNX Runtime, and a bundled trained model. No cloud calls or external AI APIs are required, making the workflow privacy-friendly, deterministic, and suitable for offline production environments.
