Datasets:
Tasks:
Image Classification
Formats:
imagefolder
Sub-tasks:
multi-class-classification
Languages:
English
Size:
1K - 10K
License:
# Ghibli Real vs AI-Generated Dataset | |
This dataset is provided in two forms: | |
### 1. `default.jsonl` | |
- One sample per line | |
- Includes: `image`, `label`, `description`, `pair_id` | |
- Use this for standard classification or image-text training | |
### 2. `pairs.jsonl` | |
- Real and fake images paired together | |
- Includes: `real_image`, `fake_image`, shared `description`, `pair_id` | |
- Use this for contrastive learning or meta-learning (e.g., ProtoNet) | |
### How to load | |
```python | |
from datasets import load_dataset | |
# Single image classification | |
samples = load_dataset("pulnip/ghibli-dataset", data_files="default.jsonl", split="train") | |
# Paired meta-learning structure | |
pairs = load_dataset("pulnip/ghibli-dataset", data_files="pairs.jsonl", split="train") | |
``` |