| import os |
| import argparse |
| import sys |
| import json |
| from omnigibson.utils.python_utils import recursively_convert_to_torch |
| from omnigibson.utils.config_utils import TorchEncoder |
| import bddl |
| from gello.utils.qa_utils import * |
| from gello.utils.b1k_utils import aggregate_episode_validation |
|
|
|
|
| def get_valid_tasks(): |
| return set(activity for activity in os.listdir(os.path.join(bddl.__path__[0], "activity_definitions"))) |
|
|
|
|
| def evaluate_qa_metrics(fpath, task): |
| |
| assert task in get_valid_tasks(), f"Got invalid task: {task}!" |
|
|
| dir_path = os.path.dirname(fpath) |
| fname = os.path.basename(fpath) |
| results_fpath = os.path.join(dir_path, fname.replace(".json", "_qa_results.json")) |
| with open(fpath, "r") as f: |
| all_episodes_metrics = json.load(f) |
| all_episodes_metrics = recursively_convert_to_torch(all_episodes_metrics) |
|
|
| all_episodes_results = dict() |
| for episode_id, all_episode_metrics in all_episodes_metrics.items(): |
| success, results = aggregate_episode_validation(task=task, all_episode_metrics=all_episode_metrics) |
| all_episodes_results[episode_id] = { |
| "success": success, |
| "results": results, |
| } |
|
|
| with open(results_fpath, "w+") as f: |
| json.dump(all_episodes_results, f, cls=TorchEncoder, indent=4) |
|
|
|
|
| def main(): |
| parser = argparse.ArgumentParser(description="Compute Success / Failure based on aggregated QA metrics") |
| parser.add_argument("--task", required=True, help="Name of the task to check") |
| parser.add_argument("--files", required=True, nargs="*", help="Individual aggregated episode metric file(s) to process") |
| args = parser.parse_args() |
|
|
| |
| for fpath in args.files: |
| if not os.path.exists(fpath): |
| print(f"Error: File {fpath} does not exist", file=sys.stderr) |
| continue |
|
|
| evaluate_qa_metrics(fpath, args.task) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|