README.md

---
title: "SD Dataset Automaker: Scrap image → Face similarity → +Tag"
emoji: 🎴💆📦
colorFrom: indigo
colorTo: pink
sdk: gradio
sdk_version: 6.0.1
app_file: app.py
pinned: false
license: mit
---

# 🎴 SD Dataset Automaker

Anime character dataset generator for LoRA/fine-tuning.

## ⚡ Quick Start

1. Find show on [fancaps.net](https://fancaps.net) → copy URL
2. Upload 3-5 reference faces of target character
3. Run → download ZIP with images + captions

## 🎛️ Parameters

| Param | Default | Description |
|-------|---------|-------------|
| URL | — | `fancaps.net/.../showimages.php?ID-Name` |
| Refs | — | 3-5 face images of target character |
| Character | auto | Output name & tag (optional) |
| Max Downloads | 200 | Frames to scrape |
| Similarity | 32 | Lower = stricter (25-30 strict, 35+ loose) |
| Trigger Word | — | Prepends to all captions |

## 🔌 MCP Server

[![MCP](https://img.shields.io/badge/MCP-enabled-ff69b4)](https://huggingface.co/docs/hub/spaces-mcp-servers)

**SSE:** `https://nekochu-sd-dataset-automaker.hf.space/gradio_api/mcp/sse`

<details>
<summary>Claude Desktop config</summary>

```json
{
  "mcpServers": {
    "sd-dataset-automaker": {
      "command": "npx",
      "args": ["mcp-remote", "https://nekochu-sd-dataset-automaker.hf.space/gradio_api/mcp/sse"]
    }
  }
}
```
</details>

<details>
<summary>Python API (Gallery)</summary>

```python
from gradio_client import Client, handle_file

client = Client("Nekochu/SD-Dataset-Automaker")
zip_path, log = client.predict(
    q="https://fancaps.net/anime/showimages.php?3092-Cowboy_Bebop",
    c="spike_spiegel",
    imgs=[
        {"image": handle_file("https://huggingface.co/spaces/Nekochu/SD-Dataset-Automaker/resolve/main/from_url_spike_spiegel1.jpg"), "caption": None},
        {"image": handle_file("https://huggingface.co/spaces/Nekochu/SD-Dataset-Automaker/resolve/main/from_url_spike_spiegel2.jpg"), "caption": None},
    ],
    files=None, mi=200, th=32, at="", an=True, mo=False, tv=False,
    api_name="/process"
)
print(f"ZIP: {zip_path}")
```
</details>

<details>
<summary>Python API (File - MCP compatible)</summary>

```python
from gradio_client import Client, handle_file

client = Client("Nekochu/SD-Dataset-Automaker")
zip_path, log = client.predict(
    q="https://fancaps.net/anime/showimages.php?3092-Cowboy_Bebop",
    c="spike_spiegel",
    imgs=None,  # Skip Gallery
    files=[  # Use File input (simpler schema, MCP-friendly)
        handle_file("spike_ref1.jpg"),
        handle_file("spike_ref2.jpg"),
    ],
    mi=200, th=32, at="", an=True, mo=False, tv=False,
    api_name="/process"
)
print(f"ZIP: {zip_path}")
```
</details>

---
*CPU runtime ~5-10 min* | Based on [Maximax67/LoRA-Dataset-Automaker](https://github.com/Maximax67/LoRA-Dataset-Automaker)