"""Read one observation directly from a downloaded dataset's tar archive."""
import argparse
import io
import json
import tarfile
from pathlib import Path

import numpy as np
import pyarrow.parquet as pq
from PIL import Image


def load_sample(root, subject, frame_id, camera_id):
    root = Path(root)
    records = pq.read_table(root / "metadata/subjects" / f"{subject}.parquet", filters=[
        ("subject_id", "=", subject), ("frame_id", "=", frame_id), ("camera_id", "=", camera_id)
    ]).to_pylist()
    if len(records) != 1:
        raise ValueError(f"Expected one observation, got {len(records)}")
    record = records[0]
    with tarfile.open(root / record["archive_path"], "r:") as archive:
        with Image.open(io.BytesIO(archive.extractfile(record["image_member"]).read())) as image:
            rgb = np.asarray(image).copy()
        with Image.open(io.BytesIO(archive.extractfile(record["segmentation_member"]).read())) as image:
            segmentation = np.asarray(image).copy()
    with np.load(root / record["registration_path"], allow_pickle=False) as data:
        row = record["registration_row"]
        assert str(data["frame_ids"][row]) == frame_id
        geometry = {key: data[key][row].copy() for key in (
            "identity", "expression", "pose", "translation", "v_offsets", "vertices_world", "joints_world"
        )}
    cameras = json.loads((root / "metadata/cameras.json").read_text())
    return {"image": rgb, "segmentation": segmentation, "foreground": segmentation > 0,
            "camera": cameras[subject][camera_id], "metadata": record, **geometry}


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("--root", type=Path, required=True)
    parser.add_argument("--subject", required=True)
    parser.add_argument("--frame", required=True)
    parser.add_argument("--camera", required=True)
    args = parser.parse_args()
    sample = load_sample(args.root, args.subject, args.frame, args.camera)
    print({k: (list(v.shape) if isinstance(v, np.ndarray) else v) for k, v in sample.items()})