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a266157 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 | # AnimeSeg
<p>
<a href="https://pepy.tech/project/anime_seg"><img alt="GitHub release" src="https://static.pepy.tech/badge/anime_seg"></a>
<a href="https://github.com/suzukimain/AnimeSeg/releases"><img alt="GitHub release" src="https://img.shields.io/github/release/suzukimain/AnimeSeg.svg"></a>
<img src="https://visitor-badge.laobi.icu/badge?page_id=suzukimain.AnimeSeg" alt="Visitor Badge">
</p>
Anime Character Segmentation using Mask2Former and DINOv2 + U-Net++ with LoRA fine-tuning.
Also integrates Background Removal via [anime-segmentation](https://github.com/SkyTNT/anime-segmentation).
## sample image
<p align="center">
<img src="https://raw.githubusercontent.com/suzukimain/AnimeSeg/refs/heads/main/images/sample2.png" alt="sample image" width="100%">
</p>
## Installation
```bash
pip install anime_seg
```
## Usage
```python
from anime_seg import AnimeSegPipeline
pipe = AnimeSegPipeline.from_mask2former().to("cuda")
mask = pipe("path/to/image.jpg")
mask.save("output.png")
# Background Removal (powered by anime-segmentation)
bg_pipe = AnimeSegPipeline.from_bg_remover().to("cuda")
no_bg_img = bg_pipe("path/to/image.jpg")
no_bg_img.save("no_bg_output.png")
```
`AnimeSegPipeline()` default constructor is deprecated. Use `from_mask2former()`, `from_dinoV2()`, or `from_bg_remover()`.
## Optional: output size
```python
# Same as input size (default)
mask_same = pipe("path/to/image.jpg")
# Fixed output size
mask_fixed = pipe("path/to/image.jpg", width=1024, height=1024)
# Width/height can be specified independently
mask_w = pipe("path/to/image.jpg", width=1024)
mask_h = pipe("path/to/image.jpg", height=1024)
```
## Advanced Usage
```python
# Load specific file from HF repo
pipe = AnimeSegPipeline.from_mask2former(
repo_id="suzukimain/AnimeSeg",
filename="models/anime_seg_mask2former_v3.safetensors"
).to(device="cuda")
# DINOv2 backend
pipe_dino = AnimeSegPipeline.from_dinoV2(
filename="models/anime_seg_dinov2_v2.safetensors"
).to("cuda")
# Use PIL Image
from PIL import Image
img = Image.open("image.jpg")
mask = pipe(img)
# Background Removal (powered by anime-segmentation)
bg_pipe = AnimeSegPipeline.from_bg_remover().to("cuda")
no_bg_img = bg_pipe("path/to/image.jpg")
no_bg_img.save("no_bg_output.png")
```
## Model Files
Models should follow the naming convention:
```
models/anime_seg_{architecture}_v{version}.safetensors
```
Example:
- `models/anime_seg_dinov2_v2.safetensors`
- `models/anime_seg_mask2former_v3.safetensors`
Resolution order:
1. `config.json`
2. fallback scan by `models/anime_seg_{architecture}_v{max_version}.{ext}`
## Segmentation Classes and Mask Colors
Default `from_mask2former()` returns **12 classes**:
| ID | Class Key | RGB | Color |
|---:|---|---|---|
| 0 | background | (0, 0, 0) | Black |
| 1 | skin | (255, 220, 180) | Pale Orange |
| 2 | face | (100, 150, 255) | Blue |
| 3 | hair_main | (255, 0, 0) | Red |
| 4 | left_eye | (0, 255, 255) | Cyan |
| 5 | right_eye | (255, 255, 0) | Yellow |
| 6 | left_eyebrow | (150, 255, 0) | Yellow Green |
| 7 | right_eyebrow | (0, 255, 100) | Emerald Green |
| 8 | nose | (255, 140, 0) | Dark Orange |
| 9 | mouth | (255, 0, 150) | Magenta Pink |
| 10 | clothes | (180, 0, 255) | Purple |
| 11 | accessory | (128, 128, 0) | Olive |
`from_dinoV2()` returns **13 classes** (includes `unknown` as ID 12).
## DINOv2 Compatibility Note
Earlier versions primarily used DINOv2. Current recommendation is `from_mask2former()`, while `from_dinoV2()` remains for compatibility.
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