File size: 2,100 Bytes
77731f3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | #!/usr/bin/env python3
from __future__ import annotations
import argparse
from pathlib import Path
from _common import candidate_by_id, cell_set, read_json, read_jsonl, safe_div, selected_ids, universe_cells, write_csv
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description="Evaluate selected-view coverage.")
parser.add_argument("--candidates", type=Path, required=True)
parser.add_argument("--selected", type=Path, required=True)
parser.add_argument("--validity", type=Path, default=None)
parser.add_argument("--output", type=Path, required=True)
return parser.parse_args()
def main() -> None:
args = parse_args()
candidates = read_jsonl(args.candidates)
selected_doc = read_json(args.selected)
by_id = candidate_by_id(candidates)
universe = universe_cells(candidates)
covered: set[str] = set()
missing_ids: list[str] = []
for cid in selected_ids(selected_doc):
if cid not in by_id:
missing_ids.append(cid)
continue
covered.update(cell_set(by_id[cid]))
invalid_rate = ""
if args.validity and args.validity.exists():
validity_rows = read_jsonl(args.validity)
invalid_rate = round(
safe_div(sum(1 for row in validity_rows if not bool(row.get("valid", False))), len(validity_rows)),
6,
)
write_csv(
args.output,
[
{
"scene_id": selected_doc.get("scene_id", "unknown"),
"method": selected_doc.get("method", "unknown"),
"num_candidates": len(candidates),
"num_selected": len(selected_doc.get("selected_viewpoints", [])),
"universe_cells": len(universe),
"covered_cells": len(covered),
"coverage": round(safe_div(len(covered), max(1, len(universe))), 6),
"invalid_rate": invalid_rate,
"missing_selected_ids": ";".join(missing_ids),
}
],
)
print(f"Wrote {args.output}")
if __name__ == "__main__":
main()
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