LayerTracer

April 1, 2025 · View on GitHub

LayerTracer: Cognitive-Aligned Layered SVG Synthesis via Diffusion Transformer
Yiren Song, Danze Chen, and Mike Zheng Shou
Show Lab, National University of Singapore

arXiv


Installation

1. Environment setup

git clone https://github.com/showlab/LayerTracer.git
cd LayerTracer

conda create -n layertracer python=3.11.10
conda activate layertracer

2. Requirements installation

pip install --upgrade -r requirements.txt

LoRa models

You can download the trained checkpoints of LoRA for text2sequence inference. Below are the details of available models:

ModelDescriptionResolution
flux_lora_icon_blacklineThis model is used to generate nine grid icon images with black lines.768,768
flux_lora_emojiThis model is used to generate four grid emoji and icon images.1024,1024

Inference

1. Text 2 Sequence

According to the actual situation, replace all model paths, file paths, and parameters in scripts/text2sequence.sh.

chmod +x scripts/text2sequence.sh
scripts/text2sequence.sh

NOTICE

When generating 9-grid images using prompts, please modify your prompt according to the examples provided below to avoid generating irrelevant content. Add this prefix to your prompt:

# nine-grid icon
sks, This is a nine square grid image that describes the process of creating SVG icon images, ...
# or
sks, a set of nine icons, each representing ...

# four-grid emoji
sks, This is a four square grid image that describes the process of creating SVG emoji images, ...

2. Image 2 Sequence

2.1 Merge LoRA to flux.1

Use our scripts/lora_merge.sh template script to merge the LoRA （flux_lora_icon_blackline and flux_lora_emoji) to flux.1 checkpoints for further recraft training. Note that the merged model may take up around 50GB of your memory space.

chmod +x scripts/lora_merge.sh
scripts/lora_merge.sh

2.2 Recraft model

According to the actual situation, replace all model paths, file paths, and parameters in scripts/image2sequence.sh.

The icon_lora_weights is a Recraft model used for generating 9-grid black line icon images. Simply replace the corresponding paths in scripts/image2sequence.sh to use it.

chmod +x scripts/image2sequence.sh
scripts/image2sequence.sh

QuickStart

9grid Sequence(blackline) to SVG

python layertracer_icon_9grid.py --input input/icon.png --output output/
  • --input : Input image path.
  • --output : Output directory.
  • --colormode: choices=['color', 'binary'], Color mode for SVG conversion.
  • --mode : choices=['spline', 'polygon', 'none'], Tracing mode for SVG conversion.
  • --filter_speckle : Speckle filter threshold.
  • --color_precision : Color precision for SVG conversion.
  • --corner_threshold: Corner detection threshold.
  • --length_threshold : Length threshold for path simplification, in [3.5, 10].
  • --splice_threshold : Splice threshold for path merging.
  • --path_precision : Path precision for SVG conversion.

4grid Sequence to SVG

You can customize the parameters, just like the above process:

python layertracer_emoji_4grid.py --input input/emoji.png --output output/

Dataset

Citation

@inproceedings{Song2025LayerTracerCL,
  title={LayerTracer: Cognitive-Aligned Layered SVG Synthesis via Diffusion Transformer},
  author={Yiren Song and Danze Chen and Mike Zheng Shou},
  year={2025},
  url={https://api.semanticscholar.org/CorpusID:276094351}
}