FFHQ-Reference / README.md
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---
language:
- en
pretty_name: FFHQ Proxy Reference
size_categories:
- 10K<n<100K
tags:
- image-restoration
- portrait-upscaling
- face-super-resolution
- aesthetic-refinement
license: creativeml-openrail-m
task_categories:
- image-to-image
---
# FFHQ Proxy Reference
## Overview
**FFHQ Proxy Reference** is a **reference-only dataset repository** designed to integrate high-quality human face images into advanced image restoration and portrait upscaling pipelines.
This repository acts as a **proxy schema and access reference** for the official FFHQ dataset and is optimized for:
- Facial detail preservation
- Portrait-focused super-resolution (up to 8K)
- Identity-consistent restoration workflows
> **Important**
> This repository does **not host image files**.
> All images must be obtained directly from the official FFHQ source and loaded locally or via private storage using a custom dataset loader.
---
## Intended Use
This dataset reference is designed for:
- Portrait upscaling models
- Face restoration and enhancement pipelines
- Aesthetic refinement workflows
- High-resolution facial reconstruction tasks
It is **not** intended to redistribute FFHQ images or bypass licensing restrictions.
---
## Dataset Structure (Expected)
Each sample is expected to follow this structure when loaded locally:
```
| Field | Type | Description |
|------|------|------------|
| `image` | `Image` | High-quality face image |
| `resolution` | `int` | Image resolution indicator |
| `source` | `string` | Original dataset reference |
```
---
## Data Source
- **Primary Source (Official FFHQ):**
https://github.com/NVlabs/ffhq-dataset
- **Mirror / Access Reference:**
Google Drive (official distribution channel).
All images remain under the **original FFHQ license and terms**.
---
## Integration Notes
- Hugging Face **does not ingest Google Drive folders directly**
- This repository serves as:
- A dataset reference
- A schema definition
- A controlled integration point for private pipelines
To use the data, users must:
1. Download FFHQ locally from the official source
2. Load images using a custom `dataset.py` or local loader
3. Ensure compliance with FFHQ licensing
---
## Example Usage
```python
from datasets import load_dataset
dataset = load_dataset(
"Legitking4pf/FFHQ-Proxy-Reference",
data_dir="/path/to/local/ffhq"
)
```
## Licensing
- **Repository contents:** CreativeML Open RAIL-M.
- **Image data:** Governed entirely by the original FFHQ license.
This repository does not grant redistribution rights for FFHQ images.
## Disclaimer
This dataset is a proxy reference only. It exists to standardize integration and does not replace or mirror the original dataset.
- **Users are responsible for:**
- Data access
- Storage
- Licensing compliance
- Copy code
---