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@@ -16,10 +16,6 @@ tags:
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  - psd
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  - photoshop
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  - image-decomposition
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- widget:
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- - text: sloth cartoon final decomposed layer
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- output:
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- url: assets/sloth_3.png
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  ---
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  > [!NOTE]
@@ -28,7 +24,6 @@ widget:
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  > - **End-to-End PSD Packaging**: Bundled with a packaging pipeline that exports generated layers directly into a multi-layer Adobe Photoshop (`.psd`) file.
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  > - **GGUF Quantization & Web Studio**: Optimized with [Unsloth Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) GGUFs for lightweight local inference, accompanied by a local **Layer Studio** web UI.
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-
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  <div>
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  <div style="display: flex; gap: 5px; align-items: center; ">
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  <a href="https://github.com/unslothai/unsloth/">
@@ -43,30 +38,18 @@ widget:
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  </div>
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  </div>
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- ### Sample
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-
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- <table>
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- <tr>
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- <td><img src="assets/sloth_main.png" width="200"></td>
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- <td><img src="assets/sloth_1.png" width="200"></td>
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- </tr>
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- <tr>
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- <td><img src="assets/sloth_2.png" width="200"></td>
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- <td><img src="assets/sloth_3.png" width="200"></td>
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- </tr>
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- </table>
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-
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-
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  ---
 
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  <p align="center">
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- <img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/layered/qwen-image-layered-logo.png" width="800"/>
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- <p>
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- <p align="center">&nbsp&nbsp🤗 <a href="https://huggingface.co/Qwen/Qwen-Image-Layered">HuggingFace</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/models/Qwen/Qwen-Image-Layered">ModelScope</a>&nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://arxiv.org/abs/2512.15603">Research Paper</a> &nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://qwenlm.github.io/blog/qwen-image-layered/">Blog</a> &nbsp&nbsp | &nbsp&nbsp 🤗 <a href="https://huggingface.co/spaces/Qwen/Qwen-Image-Layered">Demo</a> &nbsp&nbsp
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  </p>
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  <p align="center">
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- <img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/layered/layered.JPG" width="1024"/>
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- <p>
 
 
 
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  ## Introduction
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@@ -109,7 +92,7 @@ pipeline = pipeline.to("cuda")
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  # (Optional) Load custom designer LoRA adapter
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  # pipeline.load_lora_weights("path/to/designer-lora")
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- image = Image.open("assets/test_image.png").convert("RGBA")
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  inputs = {
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  "image": image,
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  "generator": torch.Generator(device='cuda').manual_seed(42),
@@ -142,40 +125,22 @@ python package_psd.py --composite source.png --layers layer_00.png layer_01.png
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  ---
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- ## Showcase
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- ### Layered Decomposition in Application
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- Given an image, Qwen-Image-Layered can decompose it into several RGBA layers:
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- ![Example Image](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/layered/幻灯片1.JPG)
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-
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- After decomposition, edits are applied exclusively to the target layer, physically isolating it from the rest of the content, and thereby fundamentally ensuring consistency across edits.
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-
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- For example, we can recolor the first layer and keep all other content untouched:
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- ![Example Image](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/layered/幻灯片2.JPG)
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- We can also replace the second layer from a girl to a boy (The target layer is edited using Qwen-Image-Edit):
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- ![Example Image](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/layered/幻灯片3.JPG)
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-
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- Here, we revise the text to "Qwen-Image" (The target layer is edited using Qwen-Image-Edit):
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- ![Example Image](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/layered/幻灯片4.JPG)
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-
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- Furthermore, the layered structure naturally supports elementary operations. For example, we can delete unwanted objects cleanly:
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- ![Example Image](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/layered/幻灯片5.JPG)
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-
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- We can also resize an object without distortion:
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- ![Example Image](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/layered/幻灯片6.JPG)
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-
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- After layer decomposition, we can move objects freely within the canvas:
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- ![Example Image](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/layered/幻灯片7.JPG)
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  ### Flexible and Iterative Decomposition
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- Qwen-Image-Layered is not limited to a fixed number of layers. The model supports variable-layer decomposition. For example, we can decompose an image into either 3 or 8 layers as needed:
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-
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- ![Example Image](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/layered/幻灯片8.JPG)
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-
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- Moreover, decomposition can be applied recursively: any layer can itself be further decomposed, enabling infinite decomposition.
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-
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- ![Example Image](https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/layered/幻灯片9.JPG)
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  ## License Agreement
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@@ -183,8 +148,6 @@ Qwen-Image-Layered is licensed under Apache 2.0.
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  ## Citation
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- We kindly encourage citation of our work if you find it useful.
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-
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  ```bibtex
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  @misc{yin2025qwenimagelayered,
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  title={Qwen-Image-Layered: Towards Inherent Editability via Layer Decomposition},
 
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  - psd
17
  - photoshop
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  - image-decomposition
 
 
 
 
19
  ---
20
 
21
  > [!NOTE]
 
24
  > - **End-to-End PSD Packaging**: Bundled with a packaging pipeline that exports generated layers directly into a multi-layer Adobe Photoshop (`.psd`) file.
25
  > - **GGUF Quantization & Web Studio**: Optimized with [Unsloth Dynamic 2.0](https://docs.unsloth.ai/basics/unsloth-dynamic-2.0-ggufs) GGUFs for lightweight local inference, accompanied by a local **Layer Studio** web UI.
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27
  <div>
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  <div style="display: flex; gap: 5px; align-items: center; ">
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  <a href="https://github.com/unslothai/unsloth/">
 
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  </div>
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  </div>
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  ---
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+
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  <p align="center">
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+ <img src="https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Image/layered/layered.JPG" width="1024"/>
 
 
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  </p>
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  <p align="center">
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+ 🤗 <a href="https://huggingface.co/Qwen/Qwen-Image-Layered">Original Base Model</a> &nbsp;|&nbsp;
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+ 📑 <a href="https://arxiv.org/abs/2512.15603">Research Paper</a> &nbsp;|&nbsp;
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+ 📑 <a href="https://qwenlm.github.io/blog/qwen-image-layered/">Blog</a> &nbsp;|&nbsp;
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+ 🤗 <a href="https://huggingface.co/spaces/Qwen/Qwen-Image-Layered">Official Demo</a>
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+ </p>
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  ## Introduction
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  # (Optional) Load custom designer LoRA adapter
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  # pipeline.load_lora_weights("path/to/designer-lora")
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+ image = Image.open("input_design.png").convert("RGBA")
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  inputs = {
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  "image": image,
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  "generator": torch.Generator(device='cuda').manual_seed(42),
 
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  ---
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+ ## Capabilities
 
 
 
 
 
 
 
 
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+ ### Layer Decomposition in Application
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+ Given an input design, the model decomposes it into several RGBA layers:
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+ - **Independent Manipulation**: Edits can be applied exclusively to targeted layers, physically isolating changes from the rest of the canvas.
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+ - **Subject & Text Replacement**: Replace specific layer elements (e.g. swap subjects or text) without altering backgrounds.
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+ - **Recoloring & Styling**: Recolor specific graphics, badges, or backgrounds while preserving unaffected elements.
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+ - **Elementary Operations**:
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+ - **Clean Object Removal**: Erase elements cleanly by simply hiding or deleting layers.
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+ - **Repositioning & Resizing**: Move or resize objects freely on the canvas without distortion or background hole-filling issues.
 
 
 
 
 
 
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  ### Flexible and Iterative Decomposition
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+ - **Variable Layer Counts**: Supports decomposing images into arbitrary layer counts (e.g., 2, 4, 6, 8+ layers) depending on complexity.
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+ - **Recursive Decomposition**: Any decomposed layer can be recursively passed back into the model to break it down further into sub-components.
 
 
 
 
 
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+ ---
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  ## License Agreement
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  ## Citation
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  ```bibtex
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  @misc{yin2025qwenimagelayered,
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  title={Qwen-Image-Layered: Towards Inherent Editability via Layer Decomposition},