scripts/make_composites.py

"""Generate per-label composite verification images from the dataset.

Creates composites/<split>/label_<N>.png for each digit and split.
These are checked into the repo for visual verification.

Usage:
    uv run python scripts/make_composites.py
"""

import os
import io
import pandas as pd
from PIL import Image

if __name__ != "__main__":
    import sys; sys.exit(0)

CELL = 36
MAX_COLS = 50


def make_composite(images, cell=CELL, max_cols=MAX_COLS):
    if not images:
        return None
    cols = min(max_cols, len(images))
    rows = (len(images) + cols - 1) // cols
    sheet = Image.new("L", (cols * cell, rows * cell), 0)
    for idx, img in enumerate(images):
        r, c = idx // cols, idx % cols
        sheet.paste(img.resize((cell, cell)), (c * cell, r * cell))
    return sheet


for split in ["train", "validation"]:
    df = pd.read_parquet(f"data/{split}-00000-of-00001.parquet")
    out_dir = f"composites/{split}"
    os.makedirs(out_dir, exist_ok=True)

    for label in sorted(df["label"].unique()):
        subset = df[df["label"] == label]
        # Only racing sources (skip mnist, racing_aug)
        racing = subset[~subset["source"].isin(["mnist", "racing_aug"])]
        if len(racing) == 0:
            continue

        images = [
            Image.open(io.BytesIO(row["image"]["bytes"])).convert("L")
            for _, row in racing.iterrows()
        ]
        sheet = make_composite(images)
        if sheet:
            path = f"{out_dir}/label_{label}.png"
            sheet.save(path)
            print(f"{split} label={label}: {len(images)} racing images -> {path}")

print("\nDone")