| from __future__ import annotations | |
| import argparse | |
| import json | |
| from common import load_config | |
| from dynafall.train_eval import evaluate_checkpoint | |
| SCENARIOS = [ | |
| ("clean", 0.0), | |
| ("missing", 0.10), | |
| ("missing", 0.20), | |
| ("missing", 0.30), | |
| ("lower_body", 0.0), | |
| ("upper_body", 0.0), | |
| ("low_conf", 0.0), | |
| ] | |
| def main() -> None: | |
| ap = argparse.ArgumentParser() | |
| ap.add_argument("--dataset", required=True) | |
| ap.add_argument("--methods", nargs="+", default=["stgcn", "agcn", "ctrgcn", "posec3d", "tcnte", "dynafall"]) | |
| ap.add_argument("--config", default="configs/default.yaml") | |
| args = ap.parse_args() | |
| cfg = load_config(args.config) | |
| results = [] | |
| for method in args.methods: | |
| for mode, amount in SCENARIOS: | |
| name = f"{mode}_{int(amount * 100)}" if mode == "missing" else mode | |
| result = evaluate_checkpoint( | |
| args.dataset, | |
| method, | |
| cfg, | |
| robustness=mode, | |
| missing_amount=amount, | |
| tag=f"robust_{name}", | |
| ) | |
| result["scenario"] = name | |
| results.append(result) | |
| print(json.dumps(result, indent=2)) | |
| print(json.dumps(results, indent=2)) | |
| if __name__ == "__main__": | |
| main() | |