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README.md

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+---
+license: mit
+task_categories:
+  - image-classification
+tags:
+  - synthetic-data
+  - text-to-image
+  - data-augmentation
+  - zero-shot
+  - few-shot
+  - computer-vision
+pretty_name: SynthBench
+size_categories:
+  - 1K<n<10K
+---
+
+# SynthBench
+
+Benchmark dataset for evaluating synthetic data generation methods for visual classification. Contains real iPhone photos, FLUX text-to-image generated images, and programmatically augmented synthetic images across 6 object classes.
+
+## Classes
+
+mouse, pen, phone, laptop, water bottle, Rubik's cube
+
+## Dataset Structure
+
+```
+data/
+├── raw/                    # 308 raw iPhone photos (HEIC converted to JPEG)
+├── real/                   # 309 preprocessed images (224x224), train/test split
+│   ├── train/
+│   └── test/
+├── synthetic_t2i/          # 1,774 FLUX text-to-image generated images
+├── synthetic_aug/          # 1,801 programmatically augmented synthetic images
+└── synthetic_t2i_lowdiv/   # 597 low-diversity T2I images (ablation)
+
+models/
+├── real_baseline.pth       # ResNet-18 trained on real data only
+├── t2i_zero_shot.pth       # ResNet-18 trained on T2I synthetic data (zero-shot)
+└── aug_zero_shot.pth       # ResNet-18 trained on augmented synthetic data (zero-shot)
+```
+
+## Usage
+
+```python
+from huggingface_hub import snapshot_download
+
+# Download everything
+snapshot_download(repo_id="LakshC/SynthBench", repo_type="dataset")
+
+# Download only real images
+snapshot_download(repo_id="LakshC/SynthBench", repo_type="dataset", allow_patterns="data/real/*")
+```
+
+Or via CLI:
+
+```bash
+huggingface-cli download LakshC/SynthBench --repo-type dataset
+```
+
+## Associated Code
+
+GitHub: [https://github.com/LakshC/SynthBench](https://github.com/LakshC/SynthBench)
+
+## Model
+
+All checkpoints are ResNet-18 (via `timm`), fine-tuned for 6-class classification.