VaseVQA / README.md
Qizhen Lan
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# VASEVQA Dataset
A Visual Question Answering dataset for ancient vase analysis and description.
## Dataset Overview
- **Total Images**: 31,773 vase images
- **Format**: Conversational QA pairs in LLaVA format
- **Domain**: Ancient Greek/Roman pottery and vases
## Data Structure
### Single-view Dataset
- **Training**: `data_train_single_llava_vasevl_v9.json` (9,354 samples)
- **Testing**: `data_test_single_llava_vasevl_v9.json` (2,339 samples)
- Format: One image per conversation
### Multi-view Dataset
- **Training**: `data_train_multi_llava_vasevl_v6_fixed.json` (25,544 samples)
- **Testing**: `data_test_multi_llava_vasevl_v6_fixed.json` (6,229 samples)
- Format: Multiple images per conversation with proper `<image>` tokens
## Question Types
Each vase is annotated with questions about:
- Fabric (e.g., ATHENIAN)
- Technique (e.g., BLACK-FIGURE, RED-FIGURE)
- Shape name (e.g., LEKYTHOS, MASTOID)
- Provenance/origin
- Dating information
- Attribution details
- Decorative descriptions
- Overall comprehensive information
## JSON Format
```json
{
"id": "sample_id",
"images": "images/filename.jpg" | ["image1.jpg", "image2.jpg"],
"conversations": [
{
"from": "human",
"value": "<image>\nWhat is the fabric of the vase?"
},
{
"from": "gpt",
"value": "The fabric of the vase is ATHENIAN."
}
]
}
```
## Files
- `images/`: Directory containing 31,773 vase images
- `descriptions.csv`: Original metadata source
- `fix_multi_data.py`: Script for adding image tokens to multi-view data