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
, shareddescription
,pair_id
- Use this for contrastive learning or meta-learning (e.g., ProtoNet)
How to load
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")