Datasets:
Tasks:
Image Classification
Formats:
imagefolder
Sub-tasks:
multi-class-classification
Languages:
English
Size:
1K - 10K
License:
from datasets import load_dataset, Dataset, Features, Value, Image | |
import re | |
import os | |
import json | |
import shutil | |
features = Features({ | |
"image": Image(decode=False), | |
"caption": Value("string") | |
}) | |
ds: Dataset = load_dataset("Nechintosh/ghibli", split="train", features=features) | |
samples = list(ds) | |
def natural_key(filename: str): | |
parts = re.split(r'(\d+)', filename) | |
return [int(p) if p.isdigit() else p.lower() for p in parts] | |
samples.sort(key=lambda s: natural_key(os.path.basename(s["image"]["path"]))) | |
os.makedirs("data/real", exist_ok=True) | |
with open("metadata.jsonl", "w") as f: | |
for i, sample in enumerate(samples): | |
caption = sample["caption"] | |
src_path: str = sample["image"]["path"] | |
filename = os.path.basename(src_path) | |
dst_path = os.path.join("data/real", filename) | |
shutil.copy(src_path, dst_path) | |
f.write(json.dumps({ | |
"id": f"real-{i:05d}", | |
"image": dst_path, | |
"label": "real", | |
"description": caption, | |
}) + "\n") | |