The open-source bridge for integrating generative fashion AI into enterprise PHP ecosystems.
Fashion-PHP is a specialized, open-source AI orchestration framework designed to bridge the gap between high-performance Python-based fashion models (such as VITON-HD, OOTDiffusion, and Stable Diffusion) and the massive global footprint of PHP-based e-commerce platforms like Magento, WooCommerce, and Shopware. By 2026, Fashion-PHP has evolved from a simple API wrapper into a comprehensive middleware solution that utilizes PHP 8.4’s FFI (Foreign Function Interface) and Swoole-based asynchronous processing to handle heavy AI inference tasks. The architecture focuses on decoupling the heavy GPU-bound image generation from the web-server logic, utilizing a robust worker-queue system backed by Redis. This allows developers to implement features like real-time virtual try-ons, AI-generated model photography from flat-lay images, and automated garment segmentation directly within their existing PHP codebase. Its positioning in 2026 is critical for legacy e-commerce modernization, providing a cost-effective, self-hosted alternative to expensive SaaS fashion-AI APIs, while maintaining strict data privacy by allowing on-premise model deployment.
Uses Swoole to handle concurrent AI inference requests without blocking the PHP process.
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Automatic extraction of style attributes into high-dimensional vector embeddings.
Internal scheduler that distributes generation tasks across multiple GPU nodes.
Direct FFI bindings to execute lightweight classification models without leaving the PHP environment.
AI-driven mask generation that identifies sleeves, collars, and hems with 98% precision.
Converts product metadata (SQL) into optimized prompts for Stable Diffusion.
Integration with ONNX Runtime for client-side processing of simple filters.
Retailers have flat-lay images but cannot afford professional models for 10,000 SKUs.
Registry Updated:2/7/2026
High return rates due to customers not knowing how clothes will fit.
Low average order value (AOV).