ANIME-SEG

Introduction

ANIME-SEG is an image segmentation model designed for anime-style images. It leverages ONNX and Safetensors for efficient model deployment. The model is integrated into the Hugging Face Hub using the PyTorchModelHubMixin, enabling easy access and usage.

Architecture

The model is constructed using PyTorch and is compatible with the model hub mixin, allowing seamless integration and functionality on the Hugging Face platform. It is specifically optimized for segmenting anime images, utilizing advancements in deep learning image processing.

Training

The training script for ANIME-SEG can be downloaded directly from the repository. It requires pytorch_lightning, kornia, timm, and a recent version of the huggingface_hub library to run. The model is trained using these libraries to ensure high performance and accuracy in segmenting anime-style images.

Guide: Running Locally

To run ANIME-SEG locally, follow these steps:

1. Download the Training Script:

   wget https://raw.githubusercontent.com/SkyTNT/anime-segmentation/refs/heads/main/train.py
   

2. Install Required Libraries:

   pip install pytorch_lightning kornia timm "huggingface_hub>=0.22"
   

3. Load and Use the Model:

   from train import AnimeSegmentation
   model = AnimeSegmentation.from_pretrained("skytnt/anime-seg")
   

For optimal performance, it is recommended to use cloud GPU services such as AWS, Google Cloud, or Azure to run the model, especially for large-scale image data.

License

The model and its associated resources are subject to the licensing terms specified in the Hugging Face repository. Please refer to the repository for detailed license information.