No weight download
No model checkpoints, Diffusers revision choice, or local disk planning is required.
Qwen Image Layered Online
Upload one flat image and get separate transparent layers with Qwen Image Layered, with no local model setup.
One entry for every layer workflow
Upload once, continue with Layer Agent
Every layer workflow now opens the same Agent workspace. Your image is attached to a new conversation; just write a prompt and the Agent will plan the stack, rebuild hidden areas, and export aligned PNG layers or a PSD.
After upload, you will continue in the Agent workspace. No generation starts until you confirm the plan.
Agent layer workspacePreview only. No credits used.
This independent ImageToLayers tool runs fal-ai/qwen-image-layered for every 3 to 10 layer job. Upload PNG, JPG, or WebP files up to 10 MB.
A flat image has pixels, not an editable layer plan
A downloaded poster, generated illustration, or client reference may look complete while every object is fused into one bitmap. Changing the background, moving a product, or hiding a badge then becomes a selection and repainting job.
Qwen Image Layered creates a new visual decomposition from that bitmap. It generates aligned RGBA images that can be hidden, moved, or edited separately. It is still an AI reconstruction: the model decides how content is grouped and estimates pixels covered in the source.
More than background removal or format conversion
Choose by the edit you need. A new file format does not create structure, and a cutout usually gives only a subject and empty background. Qwen can produce a deeper stack for recomposition.
| Method | What you actually get | Best next move |
|---|---|---|
| PNG, JPG, or PSD conversion | The same flattened pixels inside another container. | Use it when compatibility, not editing structure, is the goal. |
| Background remover | Usually one transparent foreground cutout, sometimes with a separate background. | Use it for a clean subject cutout or a simple background swap. |
| Qwen Image Layered | A generated stack of 3 to 10 full-canvas RGBA layers. | Use it when several objects or visual regions need independent control. |
Use Qwen Image Layered without local setup
The official model can run locally, but that workflow has more moving parts than a browser upload. This page removes setup while keeping the controls that matter here.
Hosted inference removes installation work, not the need to inspect an AI result. Review edges, text, overlap, and reconstructed background before production use.
No GPU environment
There is no CUDA, driver, Python, or VRAM configuration to troubleshoot.
No ComfyUI graph
Upload, layer count, prompt, preview, and downloads stay in one focused browser workflow.
Export is already wired
Download individual PNG layers, a ZIP, or a layered PSD without building your own post-processing script.
How to split an image with Qwen Image Layered
Start with the smallest useful stack, describe the complete scene, then inspect both the composite and the isolated layers before downloading.
- 1
Upload a useful source
Choose one clear PNG, JPG, or WebP image up to 10 MB. Distinct objects, readable boundaries, and enough source resolution give the model better evidence.
- 2
Choose 3 or 4 layers first
Use 3 for a simple subject, supporting element, and background. Use 4 for another editable object. Reserve 5 to 10 for scenes with more clearly separate regions.
- 3
Describe the whole image
The optional prompt is a caption for the complete scene, including important covered content. Do not write it as a command to extract only one named object.
- 4
Generate the RGBA stack
The page sends the image, caption, layer count, and PNG setting to fal-ai/qwen-image-layered, then tracks the task until results are ready.
- 5
Inspect visibility and alignment
Toggle each result in the composite preview. Check object grouping and whether transparent edges reconstruct the scene cleanly.
- 6
Download and continue editing
Save one transparent PNG, the full ZIP, or the generated PSD. Keep the original image for comparison.
Where generated layers save the most work
The model is most valuable when you have only a flattened reference but need a practical starting point for a new composition.
Rebuild a poster when the PSD is missing
Separate the dominant subject, decorative elements, and background so a designer can test a new hierarchy. Recreate important text as native type instead of treating generated text pixels as final artwork.
Move a person or product
Put the main subject on its own transparent layer, then adjust position or scale without selecting it from scratch.
Remove a visual obstruction
Hide a generated foreground layer to reveal the model's estimate of what continues behind it. Treat that hidden area as reconstructed content, not recovered original pixels.
Replace a background
Keep several foreground objects independently editable while swapping the environment, color field, or campaign backdrop.
Recompose illustrations and social graphics
Turn a flattened concept into reusable raster pieces for layout experiments, motion tests, thumbnails, or game art mockups.
What the output contains
Each result is an aligned raster layer. Stacking the visible layers recreates the model's generated composite, while alpha transparency lets you work on each piece independently.
The PSD contains generated raster layers. It does not restore original fonts, vectors, smart objects, adjustment layers, or author-created masks from a flattened source.
Full-canvas RGBA layers
Every PNG keeps canvas alignment, so layers can be stacked without manually matching their positions.
Real alpha transparency
Transparent regions use an alpha channel rather than a white checkerboard baked into the image.
Independent raster editing
Hide, move, mask, recolor, or retouch one generated layer without changing the rest of the stack.
PNG, ZIP, and PSD downloads
Take one layer, collect all PNGs, or download a server-built PSD containing the generated raster stack.
Quality limits worth checking
Qwen Image Layered is generative decomposition, not a forensic source-file recovery system. The output can change visible details while it invents a coherent layer stack.
Overlap makes ownership ambiguous
When objects cross, the model must decide which layer owns shared edges, shadows, reflections, and partially covered pixels. Zoom in around those boundaries.
Small text is still raster content
Lettering can be grouped awkwardly or regenerated with errors. Rebuild editable copy with the correct font instead of relying on separated text pixels.
Soft effects can span layers
Hair, smoke, glass, glow, grain, and motion blur may leave halos or inconsistent transparency when a layer is moved onto a different background.
More layers are not automatically better
An excessive count can create empty, faint, or arbitrary layers. A low count can combine objects you wanted apart. Choose based on real editing actions.
Hidden content is estimated
If an object covers the background, the source contains no original pixels behind it. Any revealed continuation is a plausible generation and should be reviewed accordingly.
Qwen Image Layered FAQ
Direct answers about the online model, prompts, layer counts, transparency, PSD export, and recursive decomposition.
What is Qwen Image Layered?
It is an image decomposition model from the Qwen team. A flat image and caption become several aligned RGBA images representing a new layered scene.
Can I use Qwen Image Layered online?
Yes. This browser interface uses fal-ai/qwen-image-layered. It is an independent ImageToLayers service, not an official Qwen website or partnership.
Do I need a GPU, Python, or ComfyUI?
No. The hosted fal endpoint runs inference. Your browser handles upload, settings, status, preview, and downloads. Install locally only if you need a self-managed pipeline.
How many layers should I choose?
Choose the fewest layers that match your edits. Start with 3 for simple scenes, 4 for an extra object, and 5 to 10 only for richer images. This page does not send 2-layer jobs to Qwen.
Does the prompt control which object becomes a layer?
Not reliably. The official prompt describes the entire image, including important occluded content. The model chooses the decomposition, so a clear caption is context rather than a guaranteed layer command.
Are the generated layers transparent?
Yes. The page requests PNG and the returned layers use RGBA transparency. Check isolated edges and the composite with the visibility controls.
Does the PSD restore my original design file?
No. ImageToLayers packages generated raster images as PSD layers. It cannot recover live text, vectors, smart objects, adjustments, or original layer names.
Why are some objects combined, and can I split a layer again?
The count is a target, not one layer per named object. Download a combined PNG and upload it again for another decomposition. Review every pass because generation can alter detail.
Related image layer tools
Use the general separator for a broader workflow, or continue into a format-specific handoff for Photoshop and Canva.
Image to Layers
Open the main AI layer separator with flexible foreground and multi-object workflows.
Image to PSD
Turn a flattened image into a Photoshop-compatible document with generated raster layers.
PNG to PSD
Build a layered PSD from a PNG when Photoshop is the next editing destination.
Image to Canva Editable
Prepare separate transparent PNG assets for manual layout and text rebuilding in Canva.
Try Qwen Image Layered on your own image
Skip local model setup and manual layer rebuilding. Start with 3 or 4 layers, describe the full scene, and inspect the generated stack before downloading.
Open the Qwen layer toolQwen Image Layered is developed by the Qwen team. ImageToLayers is an independent hosted interface using the fal model endpoint. Model details: official Qwen Image Layered repository.