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@growwithgdp

✅ I’ll build an **AI-powered image generation system** using Stable Diffusion (fine-tuned with your dataset via LoRA/DreamBooth) that converts user inputs (dimensions, windows, doors, cladding) into realistic garden studio visuals. ✅ Includes **web interface, FastAPI backend, GPU-based generation, rate limiting, and scalable pipeline (1K–10K images/month)** with training tools for your team. ✅ MVP in **1 week**, with full deployment, documentation, and future-ready architecture.

@rocky6222

Your idea of generating customized garden studio images based on user inputs is very interesting. I understand the requirement involves training an AI model on your architectural styles and building a system where users can configure dimensions, windows, doors, and cladding to generate realistic outputs. This type of system typically involves models like Stable Diffusion with custom fine-tuning, along with a backend pipeline and web interface. I’d like to clarify a few points before proposing a proper solution: How many training images do you currently have? Do you expect photorealistic output or conceptual designs? Should generation be real-time or batch-based? Also, the current budget seems lower than the scope, so I’d be happy to suggest a phased MVP approach that fits your needs. Let’s discuss this further