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import argparse
import pandas as pd

def main(
    input_csv: str,
    out_counts: str = "num_raters_per_video.csv",
    out_stats_all: str = "video_stats_all.csv",
    out_stats_filtered: str = "video_stats_filtered.csv",
    min_raters: int = 2,
):
    # 1) 데이터 λ‘œλ“œ
    df = pd.read_csv(input_csv)

    # μˆ«μžν˜• 보μž₯ (문자/빈칸 μ„žμ˜€μ„ λ•Œ λŒ€λΉ„)
    for col in ["action_consistency", "physical_plausibility"]:
        if col in df.columns:
            df[col] = pd.to_numeric(df[col], errors="coerce")

    # 2) λΉ„λ””μ˜€λ³„ 고유 ν‰κ°€μž 수
    counts = (
        df.groupby("video_id")["participant_id"]
        .nunique()
        .reset_index(name="num_raters")
    )
    counts.to_csv(out_counts, index=False)

    # 3) λΉ„λ””μ˜€λ³„ 톡계 (평균/ν‘œμ€€νŽΈμ°¨/ν‘œλ³Έμˆ˜)
    agg_map = {
        "participant_id": pd.Series.nunique,  # 고유 ν‰κ°€μž 수
        "action_consistency": ["mean", "std", "count"],
        "physical_plausibility": ["mean", "std", "count"],
    }

    stats = df.groupby("video_id").agg(agg_map)
    # 컬럼 평탄화
    stats.columns = [
        "num_raters",
        "action_mean", "action_std", "action_count",
        "physical_mean", "physical_std", "physical_count",
    ]
    stats = stats.reset_index()

    # 3-1) (선택) λ³€λ™κ³„μˆ˜(CV)도 참고용으둜 μΆ”κ°€
    stats["action_cv"] = stats["action_std"] / stats["action_mean"]
    stats["physical_cv"] = stats["physical_std"] / stats["physical_mean"]

    # μ €μž₯ (λͺ¨λ“  λΉ„λ””μ˜€)
    stats.to_csv(out_stats_all, index=False)

    # 4) μ΅œμ†Œ ν‰κ°€μž 수 μ΄μƒλ§Œ 필터링
    stats_filtered = stats[stats["num_raters"] >= min_raters].copy()
    stats_filtered.to_csv(out_stats_filtered, index=False)

    # 5) μš”μ•½ ν”„λ¦°νŠΈ
    print("βœ… μ €μž₯ μ™„λ£Œ")
    print(f"- λΉ„λ””μ˜€λ³„ ν‰κ°€μž 수: {out_counts}")
    print(f"- λΉ„λ””μ˜€λ³„ 톡계(전체): {out_stats_all}")
    print(f"- λΉ„λ””μ˜€λ³„ 톡계(ν‰κ°€μž {min_raters}λͺ… 이상): {out_stats_filtered}")

if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Human eval 뢄석 슀크립트")
    parser.add_argument("--input_csv", type=str, required=True, help="원본 CSV 경둜")
    parser.add_argument("--out_counts", type=str, default="num_raters_per_video.csv")
    parser.add_argument("--out_stats_all", type=str, default="video_stats_all.csv")
    parser.add_argument("--out_stats_filtered", type=str, default="video_stats_filtered.csv")
    parser.add_argument("--min_raters", type=int, default=2, help="μ΅œμ†Œ ν‰κ°€μž 수 κΈ°μ€€")
    args = parser.parse_args()

    main(
        input_csv=args.input_csv,
        out_counts=args.out_counts,
        out_stats_all=args.out_stats_all,
        out_stats_filtered=args.out_stats_filtered,
        min_raters=args.min_raters,
    )