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See-through Portable

Upload a single anime character illustration to automatically decompose it into fully-inpainted semantic layers with depth ordering, exported as a layered PSD file.

A one-click portable launcher based on See-through (Apache 2.0 License).

繁體中文說明

Features

  • Automatically decompose anime character images into up to 23 semantic layers:
    • Hair: front hair, back hair
    • Head: head, face, nose, mouth
    • Eyes: eyewhite, irides, eyelash, eyebrow
    • Accessories: headwear, eyewear, earwear, neckwear
    • Body: ears, neck
    • Clothing: topwear, bottomwear, legwear, footwear, handwear
    • Other: tail, wings, objects
  • Every layer is fully inpainted, not simply cropped
  • Automatic depth ordering for each layer
  • Export as PSD file
  • Gradio web interface with English / Chinese toggle

System Requirements

  • OS: Windows 10 / 11
  • Python: 3.10 - 3.12 (if not installed, run.bat will automatically install Python 3.12 via winget)
  • GPU: NVIDIA GPU with at least 8 GB VRAM (GTX 10 series to RTX 50 series supported)
  • NVIDIA Driver: Version 560 or above (latest version recommended)
  • Disk Space: ~20 GB (including model downloads)

Usage

  1. Download zip from Releases and extract, or clone this repository
  2. Double-click run.bat
  3. First run will automatically create a virtual environment and install all dependencies (~10-20 minutes)
  4. Browser will automatically open the Gradio interface
  5. Upload an image and click "Start Processing"

Warning

The first time you process an image, models will be downloaded automatically (~13 GB). They will not be re-downloaded afterward.

Manual Model Download

If automatic download is too slow or your network is unstable, you can download models manually.

This project uses two HuggingFace models:

Model Size Link
LayerDiff (Layer Decomposition) ~9.5 GB layerdifforg/seethroughv0.0.2_layerdiff3d
Marigold (Depth Estimation) ~3.3 GB 24yearsold/seethroughv0.0.1_marigold

Using huggingface-cli

Run run.bat once to set up the virtual environment, then open a command prompt:

cd your\path\see-through-portable
venv\Scripts\activate
huggingface-cli download layerdifforg/seethroughv0.0.2_layerdiff3d --cache-dir models/hub
huggingface-cli download 24yearsold/seethroughv0.0.1_marigold --cache-dir models/hub

Parameters

Parameter Default Description
Random Seed 42 Different seeds produce different decomposition results
Resolution 1280 Higher = better quality but slower and more VRAM. Image is center-padded to square
Inference Steps 30 Denoising steps. More = better quality but slower. Not recommended to change
Left/Right Split OFF Split gloves, eyes, ears, etc. into separate left/right layers
Cache Tag Embeddings ON Pre-compute text embeddings and unload text encoders, saves ~2 GB VRAM with zero speed penalty
Group Offload OFF Move model blocks on/off GPU as needed. Drastically reduces VRAM but 2-3x slower
Depth Resolution -1 -1 = same as layer resolution. Lower values save VRAM with slightly reduced depth accuracy. Custom default: 768 (model training resolution)

VRAM Optimization Guide

12 GB+ VRAM (e.g. RTX 3060 12G, RTX 4070 and above): Default settings are fine. Cache Tag Embeddings is already enabled by default.

8-12 GB VRAM (e.g. RTX 3060 8G, RTX 4060): Try the following in order, from least to most impact on speed:

  1. Cache Tag Embeddings = ON (already enabled by default) — Saves ~2 GB with zero speed penalty
  2. Lower Depth Resolution — Uncheck "Depth resolution same as layers", defaults to 768 (model training resolution), adjustable. Saves VRAM with slightly reduced depth accuracy
  3. Lower Resolution — e.g. 1024 instead of 1280, reduces both VRAM and computation time
  4. Group Offload = ON — Last resort. Drastically reduces VRAM but 2-3x slower

Output

Output files are located in the workspace/layerdiff_output/ folder:

  • <image_name>.psd — Multi-layer PSD file
  • <image_name>/ — Individual layer PNG files

FAQ

Q: run.bat closes immediately? A: Right-click run.bat > Edit, check that the file encoding is UTF-8 with BOM or ANSI. Or run run.bat directly in cmd to see error messages.

Q: run.bat is blocked by Windows SmartScreen? A: Click "More info" → "Run anyway".

Q: "No compatible Python (3.10 - 3.12) found"? A: run.bat will automatically install Python 3.12 via winget. After installation, close the window and double-click run.bat again.

Q: How to uninstall the auto-installed Python? A: Open a command prompt and run: winget uninstall Python.Python.3.12

Q: "No NVIDIA GPU with CUDA detected"? A: Make sure you have NVIDIA driver version 560 or above. Download the latest driver: https://www.nvidia.com/download/index.aspx . AMD GPUs are not supported.

Q: "CUDA error: no kernel image is available"? A: Your GPU is too old. This tool requires at least an NVIDIA GTX 10 series GPU.

Q: C++ compiler error during dependency installation? A: Install Visual Studio Build Tools.

Q: Model download was interrupted? A: Run run.bat again. The download will resume from where it left off.

Q: Does the folder path with spaces or special characters cause issues? A: It is recommended to extract the package to a simple path, e.g. D:\see-through-portable, avoiding paths with spaces or special characters.

Q: How long does it take to process one image? A: Processing time varies greatly depending on GPU performance and image resolution.

Credits

This project is based on See-through by shitagaki-lab, licensed under Apache 2.0.

License

Apache License 2.0

About

One-click portable launcher for See-through anime layer decomposition | 上傳一張動漫角色插圖,自動分解為完整修補的語義圖層並依深度排序,匯出為多圖層 PSD 檔案。

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