| # Project Halide Training Data | |
| Film defect detection training data for MiniCPM-V 4.6 fine-tuning. | |
| ## Dataset | |
| **FilmDamageSimulator** (Eurographics 2023) | |
| - 10 film scans (4K resolution) | |
| - 12,137 defect annotations | |
| - 5 classes: dust, dirt, short_hair, long_hair, scratch | |
| - All bounding boxes normalized to [0.0-1.0] | |
| ## Format | |
| JSONL with structure: | |
| ## Classes | |
| | Class | Count | Color | | |
| |-------|-------|-------| | |
| | dust | 7,631 | Red | | |
| | dirt | 2,700 | Orange | | |
| | short_hair | 1,341 | Cyan | | |
| | long_hair | 399 | Green | | |
| | scratch | 66 | Yellow | | |
| ## Source | |
| Original data from [FilmDamageSimulator](https://github.com/daniela997/FilmDamageSimulator). | |
| Citation: | |