Datasets:
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README.md
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---
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# 🧠 Synthetic CelebA-StyleGAN Embedding Dataset
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## 🧩 Dataset Creation Notes
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### Overview
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This dataset was created by combining **CelebA**, **StyleGAN (FFHQ)**, and **Stable Diffusion (VAE Encoder)**
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to generate facial embeddings annotated with visual attributes.
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### 🔹 Step-by-step process
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1. **Attribute Classifier (CelebA)**
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- Trained a ResNet-based classifier on the **CelebA dataset** to predict **40 facial attributes**.
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- Achieved **~92% accuracy** on the validation set.
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- The **“Blurry”** attribute was found to have no positive samples in the generated set,
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so only **39 valid attributes** were retained in the final dataset.
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2. **Synthetic Face Generation (StyleGAN FFHQ)**
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- Used **StyleGAN trained on FFHQ** to generate approximately **3.5 million synthetic face images**.
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- Each generated image was processed by the CelebA-trained classifier to obtain its 39-dimensional attribute vector.
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3. **Embedding Extraction (Stable Diffusion VAE)**
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- Encoded each image using the **VAE encoder from Stable Diffusion v1.5**.
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- The resulting embeddings represent each image in the Stable Diffusion latent space.
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### 📦 Output Format
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Each entry in the dataset includes:
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- **`embedding`** — latent vector from Stable Diffusion’s VAE
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- **`attributes`** — 40 binary attributes predicted by the CelebA-trained classifier
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- **`source`** — `"synthetic"` (generated by StyleGAN FFHQ)
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### ⚠️ License and Intended Use
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This dataset incorporates models and data under the following research licenses:
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- **CelebA** — Non-Commercial Research License
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- **StyleGAN (FFHQ)** — NVIDIA Research License
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- **Stable Diffusion (VAE)** — CreativeML OpenRAIL-M
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Hence, this dataset is **strictly for non-commercial research and educational purposes**.
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