| """Combine per-task score files into the VisSlideBench summary (Table 1 layout). |
| |
| python eval/aggregate.py --pred_dir outputs/my_model |
| |
| Each metric is averaged over the cases with a valid score for that metric. |
| Overall is the mean of the eleven metrics (CF/IF/AQ for three generation |
| tasks, SC/PQ for editing) and is reported only when all four tasks exist. |
| """ |
|
|
| import argparse |
| import json |
| import os |
|
|
| from common import load_jsonl, mean |
|
|
| GEN_TASKS = ("t2i", "template", "multi_image") |
|
|
|
|
| def main(): |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--pred_dir", required=True) |
| ap.add_argument("--by", choices=["none", "source", "prompt_type"], default="none", |
| help="Optionally split generation scores by real/synthetic source or prompt type.") |
| args = ap.parse_args() |
| score_dir = os.path.join(args.pred_dir, "scores") |
|
|
| table, metrics = {}, [] |
| for task in GEN_TASKS: |
| path = os.path.join(score_dir, f"{task}.jsonl") |
| if not os.path.exists(path): |
| continue |
| rows = load_jsonl(path) |
| groups = {"all": rows} if args.by == "none" else {} |
| if args.by != "none": |
| for r in rows: |
| groups.setdefault(r.get(args.by), []).append(r) |
| for g, rs in groups.items(): |
| entry = {m: mean(r[m] for r in rs if r.get(m) is not None) for m in ("cf", "if", "aq")} |
| entry["n"] = len(rs) |
| table[task if g == "all" else f"{task}/{g}"] = entry |
| if args.by == "none": |
| metrics += [table[task][m] for m in ("cf", "if", "aq")] |
|
|
| edit_path = os.path.join(score_dir, "edit.jsonl") |
| if os.path.exists(edit_path): |
| ok = [r for r in load_jsonl(edit_path) if "sc" in r] |
| sc, pq = mean(r["sc"] for r in ok), mean(r["pq"] for r in ok) |
| table["edit"] = {"sc": sc, "pq": pq, "n": len(ok)} |
| metrics += [sc, pq] |
|
|
| if args.by == "none" and len(metrics) == 11 and None not in metrics: |
| table["overall"] = mean(metrics) |
| print(json.dumps(table, indent=1)) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
