README.md

metadata

title: Qwen Wall Segmentation
emoji: 🪄
colorFrom: purple
colorTo: pink
sdk: gradio
sdk_version: 5.49.1
app_file: app.py
pinned: false
license: apache-2.0
short_description: Qwen Wall Segmentation

Qwen Wall Segmentation

Produces pixel-accurate wall segmentation masks from a single room photo — no segmentation model, no training data, no manual annotation.

The insight is to turn a hard segmentation problem into a trivial one. Generic wall segmentation is difficult: walls have no consistent shape, blend into ceilings and floors, and vary wildly in color and texture. Rather than fight that, this tool uses Qwen-Image-Edit-2511 to repaint only the walls a flat, perfectly uniform color — every wall forced to the same hue, saturation, and brightness — while leaving furniture, floors, windows, shadows, and lighting untouched. The model handles the semantic understanding of "what is a wall"; the uniform recolor then makes those pixels cleanly separable by color.

This sidesteps the usual failure modes of color-based segmentation (lighting gradients, shadows, multi-colored walls), because the recolor normalizes all of them away before extraction.

Outputs

For each uploaded image you get three results: the recolored edit, the binary wall mask, and an overlay of the mask on your original image.

Use cases

• Bootstrapping wall-segmentation training sets
• Interior virtual-repainting and color visualization
• AR room staging
• Cheap pseudo-labeling for downstream models

Built for the Build Small Hackathon (model ≤ 32B params).