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# /// script
# requires-python = ">=3.10"
# dependencies = [
# "pandas",
# "pyarrow",
# "pydantic",
# ]
# ///
import os
import argparse
from pathlib import Path
import pandas as pd
from pydantic import BaseModel, field_validator
IMAGE_EXT = {".jpg", ".jpeg", ".png", ".webp"}
VIDEO_EXT = {".mp4", ".webm", ".avi", ".mov"}
def clean_name(name: str) -> str:
return name.strip().replace(" ", "_")
class MemeRecord(BaseModel):
image_file_name: str = ""
video_file_name: str = ""
category: str
caption: str = ""
@field_validator("image_file_name", "video_file_name")
@classmethod
def normalize_path(cls, v: str) -> str:
return v.replace("\\", "/") if v else ""
@field_validator("category")
@classmethod
def normalize_category(cls, v: str) -> str:
return clean_name(v)
def main(root: Path):
src = root / "meme"
if not src.exists():
raise SystemExit(f"❌ Missing folder: {src}")
records: list[MemeRecord] = []
for category_dir in src.iterdir():
if not category_dir.is_dir():
continue
category = clean_name(category_dir.name)
for root_dir, _, files in os.walk(category_dir):
for file in files:
path = Path(root_dir) / file
ext = path.suffix.lower()
rel = str(path.relative_to(root))
if ext in IMAGE_EXT:
records.append(
MemeRecord(
image_file_name=rel,
video_file_name="",
category=category
)
)
elif ext in VIDEO_EXT:
records.append(
MemeRecord(
image_file_name="",
video_file_name=rel,
category=category
)
)
if not records:
raise SystemExit("❌ No media files found")
df = pd.DataFrame([r.model_dump() for r in records])
df.to_csv(root / "metadata.csv", index=False)
#df.to_parquet(root / "metadata.parquet", index=False)
print(f"✔ Indexed {len(df)} files (HF streaming safe)")
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--root", type=Path, default=Path.cwd())
args = parser.parse_args()
main(args.root)
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