Python and Machine Learning - AI-powered floor replacement tool

(UK AND EUROPE BASED ONLY) ** Others will be reported.

We’re looking for a Python and Machine Learning expert to build the core visualization engine for an AI-powered floor replacement tool—think along the lines of HomeDesigns.ai Floor Editor or Winstars.ai Flooring Designer. This gig is all about the backend visualization: take an uploaded room image, detect the floor, and swap it with a custom texture, keeping it lean and cost-effective on a server. No fancy frontend—just a simple Python UI for testing.

**Here’s what we need:

Core Task: Use Python and OpenCV to detect floors and replace them with a custom tiled image we provide.

AI Models: Leverage or fine-tune lightweight ML models (e.g., segmentation) for accurate floor detection—good enough to keep things clean and precise. TensorFlow or PyTorch are our go-tos.

Server Efficiency: Deploy it on a low-cost server (like a small AWS/GCP instance). We want a solid balance of speed and accuracy without racking up big server bills—efficiency is the name of the game.

Simple UI: Build a basic Python UI (e.g., Tkinter or a script) so we can upload an image, select a texture, and tweak it—specifically, resize and rotate the tile/texture to fit the room. Nothing flashy, just functional.

Success Looks Like: The final image has no (or barely any) artifacting—clean edges, no weird glitches. The texture’s perspective matches the room realistically, like it belongs there. Plus, we can adjust the tile/texture size and rotation for a perfect fit.

**What We’re Looking For:

Strong Python and OpenCV skills—floor detection and texture replacement should be second nature to you.

Experience with lightweight ML models (e.g., U-Net, MobileNet) that deliver accuracy without eating resources.

Know-how to deploy on a server and keep costs low—think CPU-friendly or minimal GPU, maybe some model optimization tricks like quantization.

Ability to whip up a simple Python GUI that lets us resize and rotate textures on the fly.

A practical approach to hit our success criteria—clean output, realistic perspective, and flexible textures—without overcomplicating things.

**Project Scope & Budget:

Fixed-price job, aiming for a working prototype in 4 weeks.

This is just the visualization engine—no frontend needed.

**How to Apply:

Examples of Python/OpenCV or ML projects you’ve done (code, demos, or write-ups are awesome).
A quick rundown of how you’d tackle this—model ideas, optimization approach, etc.
Your availability and rate.