QwenLM/Qwen-Image-Layered

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2079 stars · 170 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Qwen-Image-Layered is a diffusion-based model and pipeline that decomposes an input image into multiple independently editable RGBA layers. Each layer can be resized, repositioned, or recolored without affecting other content, enabling high-fidelity image editing.

Use cases

• decompose an image into editable RGBA layers
• reposition or resize objects in a photo without affecting the background
• recolor isolated image elements independently
• edit occluded or layered image components
• run image-to-layered-decomposition inference with diffusers

When to choose

• you need layer-based, non-destructive image editing driven by a generative model
• you want to isolate semantic components of an image into separate RGBA layers
• you already use Hugging Face diffusers and want a drop-in pipeline

When to avoid

• you need text-to-image generation of layered output - the released weights are tuned only for image-to-layer decomposition
• you need fine-grained control over the semantic content of individual layers via prompts
• you lack a GPU or cannot run large diffusion models

Facets

library · maturity experimental

image-processing machine-learning deep-learning image-processing artificial-intelligence graphics python cross-platform image-decomposition rgba-layers diffusion-model image-editing diffusers qwen gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="QwenLM/Qwen-Image-Layered")