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Splits one anime character illustration into separate, fully filled-in layers with depth order and gives you a layered PSD file. For illustrators, animators and researchers.
See-through: Layer Decomposition is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.
pip install -U huggingface_hub hf download 24yearsold/see-through-demo --repo-type space --local-dir see-through-demo cd see-through-demo
See-through: Layer Decomposition is a Gradio demo that takes one anime character illustration and splits it into separate semantic layers. Hidden parts of each layer are filled in, the layers come with a depth order, and the result is a layered PSD file. It runs on ZeroGPU hardware, so you can try it in a browser.
It suits illustrators, animators and researchers who want an illustration broken into editable layers without cutting it apart by hand.
| Industry | Who uses it | How they use it | Example |
|---|---|---|---|
| Illustration | Artists | Turn a flat finished picture into editable layers | Upload a character and open the PSD |
| Animation | Animators | Get layers with depth order to start from | Move the separated parts of one character |
| AI research | Researchers | Try the See-through pipeline on new images | Compare the layers with the paper's examples |
If your picture is not an anime character, you can skip it, since the model is made for that style.
| Use case | Who | What they get back |
|---|---|---|
| Split an illustration | Artists | A layered PSD with the parts separated |
| Prepare for animation | Animators | Layers with depth order |
| Test the pipeline | Researchers | Results from the three-stage pipeline |
pip install -U huggingface_hub hf download 24yearsold/see-through-demo --repo-type space --local-dir see-through-demo cd see-through-demo pip install gradio==6.12.0 pip install -r requirements.txt python app.py
Upload an illustration, run it and download the PSD. Square pictures work best, and other shapes are cropped from the center.
| Tool | What it does |
|---|---|
| LayerDiff 3D | Generates transparent layers with a diffusion model built on SDXL |
| Marigold Depth | Estimates a rough depth map tuned for anime pictures |
| Post-processing | Sorts the layers into a stack and exports the PSD |
Upload a square illustration of one character and press Submit. After a minute or two, you download a PSD in which the hair, clothes and other parts sit on their own layers.
Start with a clean, square picture of one character and leave the seed alone. Open the PSD in your editor and look at the layers.
The demo runs the full See-through pipeline, which joins layer generation, depth estimation and layer stacking. It uses a newer model checkpoint than the paper, so results may not match the paper's exactly. The repository also holds a data pipeline README and notes on PSD stratification.
The demo uses a newer checkpoint than the paper, so it may not reproduce the paper's numbers exactly.
Splits one anime character illustration into separate, fully filled-in layers with depth order and gives you a layered PSD file. For illustrators, animators and researchers.
Made by 24yearsold on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face.
What it is: See-through: Layer Decomposition is a Gradio demo that takes one anime character illustration and splits it into separate semantic layers. Hidden parts of each layer are filled in, the layers come with a depth order, and the result is a layered PSD file. It runs on ZeroGPU hardware, so you can try it in a browser.
Who it suits: It suits illustrators, animators and researchers who want an illustration broken into editable layers without cutting it apart by hand.
Industry | Who uses it | How they use it | Example
Illustration | Artists | Turn a flat finished picture into editable layers | Upload a character and open the PSD
Animation | Animators | Get layers with depth order to start from | Move the separated parts of one character
AI research | Researchers | Try the See-through pipeline on new images | Compare the layers with the paper's examples
If your picture is not an anime character, you can skip it, since the model is made for that style.
Where to use it:
Use case | Who | What they get back
Split an illustration | Artists | A layered PSD with the parts separated
Prepare for animation | Animators | Layers with depth order
Test the pipeline | Researchers | Results from the three-stage pipeline
How to set it up:
pip install -U huggingface_hub
hf download 24yearsold/see-through-demo --repo-type space --local-dir see-through-demo
cd see-through-demo
pip install gradio==6.12.0
pip install -r requirements.txt
python app.py
How to use it: Upload an illustration, run it and download the PSD. Square pictures work best, and other shapes are cropped from the center.
Tool | What it does
LayerDiff 3D | Generates transparent layers with a diffusion model built on SDXL
Marigold Depth | Estimates a rough depth map tuned for anime pictures
Post-processing | Sorts the layers into a stack and exports the PSD
Example: Upload a square illustration of one character and press Submit. After a minute or two, you download a PSD in which the hair, clothes and other parts sit on their own layers.
For newcomers and experts: Start with a clean, square picture of one character and leave the seed alone. Open the PSD in your editor and look at the layers.
The demo runs the full See-through pipeline, which joins layer generation, depth estimation and layer stacking. It uses a newer model checkpoint than the paper, so results may not match the paper's exactly. The repository also holds a data pipeline README and notes on PSD stratification.
You upload a character illustration
LayerDiff 3D makes the transparent layers
Marigold Depth estimates the depth order
Post-processing exports a layered PSD
Good to know: The demo uses a newer checkpoint than the paper, so it may not reproduce the paper's numbers exactly.
Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself.
README.md 5 KB
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