# Skinpy Extended

<p align="center">
  <img src="https://raw.githubusercontent.com/Bonenk/skinpy-extended/master/examples/render/reconstructed_skin.png" alt="2D Texture" height="250" style="vertical-align: middle;">
  <span style="vertical-align: middle; font-size: 2em;"> &nbsp; ➔ &nbsp; </span>
  <img src="https://raw.githubusercontent.com/Bonenk/skinpy-extended/master/examples/render/bidirectional_render.png" alt="Verified Render" height="250" style="vertical-align: middle;">
  <span style="vertical-align: middle; font-size: 2em;"> &nbsp; ➔ &nbsp; </span>
  <img src="https://raw.githubusercontent.com/Bonenk/skinpy-extended/master/examples/render/reconstructed_skin.png" alt="2D Texture" height="250" style="vertical-align: middle;">
</p>

A Python library for Minecraft skins, focusing on high-fidelity rendering, texture reconstruction, and bi-directional mapping.

## Motivation

This project is a fork and extension of the archived [skinpy](https://github.com/t-mart/skinpy/) library. We aim to revitalize the project with advanced features inspired by modern high-performance renderers like [nmsr-rs](https://github.com/NickAcPT/nmsr-rs).

Our core goal is to provide a simple, Pythonic way to bridge the gap between 2D skin textures and 3D renders, enabling seamless mapping in both directions.

### AI Dataset Preparation
Modern AI models require high-quality, structured data. By providing bi-directional mapping between 2D textures and 3D renders, **Skinpy Extended** acts as a powerful tool for **dataset preparation** in the field of skin generation and processing.

- **Automated Dataset Generation:** Efficiently create thousands of consistent perspective renders from raw skin textures to feed into training pipelines for GANs, Diffusion models, or Vision Transformers.
- **Bi-directional Ground Truth:** Leverage the ability to reconstruct textures from renders to validate model performance and calculate loss between generated renders and original textures.
- **Structured Mapping:** Streamlining the process of preparing datasets that help models understand Minecraft's unique texture-to-model mapping, enabling high-fidelity regeneration based on AI-processed outputs.

## Features

- **2D to 3D Mapping:** Render high-quality isometric views of any Minecraft skin.
- **3D to 2D Reconstruction:** Reconstruct original 64x64 skin textures from rendered images.
- **Granular Control:** Access and modify pixels at the skin, body part, or individual face level using 3D coordinates.
- **Dataset Preparation:** Perfect for generating large-scale, consistent datasets of skin renders and their corresponding textures.
- **CLI & API:** Use the built-in command-line tool or integrate the flexible Python API into your own projects.

## Installation

```shell
pip install skinpy-extended
```

## Quickstart

### Loading and Saving

```python
from skinpy import Skin

# Load a skin from a file
skin = Skin.from_path("steve.png")

# Save the skin texture back to a file
skin.to_image().save("steve_copy.png")
```

### Rendering a Perspective View

```python
from skinpy import Skin, Perspective

skin = Skin.from_path("steve.png")

# Create a perspective (Front-Right-Up)
perspective = Perspective.new(
    x="right",
    y="front",
    z="up",
    scaling_factor=20
)

# Render and save
skin.to_isometric_image(perspective).save("render.png")
```

### Reconstructing a Skin from a Render

```python
from PIL import Image
from skinpy import Skin

# Load a combined render (e.g. front and back views)
render_img = Image.open("render.png").convert("RGBA")

# Map the render back to a 3D Skin object
skin = Skin.from_combined_render(render_img, scale=20)

# Extract the original 2D texture
skin.to_image().save("reconstructed.png")
```

## Coordinate System

Skinpy uses a coordinate system with the origin at the left-down-front of the skin from the perspective of an observer looking at the skin.

![coordinate system](https://github.com/Bonenk/skinpy-extended/raw/master/docs/coordsys.png)

## Development & Contributing

We welcome contributions to expand the library's capabilities! Areas of interest include:
- Support for Slim (Alex-style) models.
- Support for secondary layers (overlays/hats).
- Improved rendering performance.

Feel free to open issues or submit pull requests.

## Credits

- Originally created by [Tim Martin](https://github.com/t-mart) and [Steven Van Ingelgem](https://github.com/svaningelgem).
- Maintained and extended by [Bonenk](https://github.com/Bonenk).
- Logic inspired by [nmsr-rs](https://github.com/NickAcPT/nmsr-rs).

## License

MIT
