import json import argparse import os import datetime def evaluate_accuracy(output_file, gt_file, result_file): # Initialize result dictionary process_result = False result = False comments = "" # 1. Check if output file exists, is not empty, and has correct format if os.path.exists(output_file) and os.path.getsize(output_file) > 0: try: with open(output_file, "r") as f: output_data = json.load(f) if 'prediction' not in output_data: comments += "Error: Output JSON file does not contain 'prediction' key.\n" else: process_result = True # File check passed except Exception as e: comments += f"Error: Could not read output file - {str(e)}\n" else: comments += "Error: Output file does not exist or is empty.\n" # 2. Check if ground truth file exists, is not empty, and has correct format if os.path.exists(gt_file) and os.path.getsize(gt_file) > 0: try: with open(gt_file, "r") as f: gt_data = json.load(f) if 'prediction' not in gt_data: comments += "Error: Ground truth JSON file does not contain 'prediction' key.\n" except Exception as e: comments += f"Error: Could not read ground truth file - {str(e)}\n" else: comments += "Error: Ground truth file does not exist or is empty.\n" # 3. Compare predictions between output and ground truth if process_result: correct = output_data['prediction'] == gt_data['prediction'] result = correct comments += f"Comparison result: {'Match' if correct else 'Mismatch'}\n" # 4. Get current timestamp time_point = datetime.datetime.now().strftime("%Y-%m-%dT%H:%M:%S") # 5. Prepare output dictionary result_dict = { "Process": process_result, "Result": result, "TimePoint": time_point, "comments": comments } # 6. Write results to jsonl file with open(result_file, "a", encoding="utf-8") as result_f: result_f.write(json.dumps(result_dict, default=str) + "\n") # Print to terminal print(f"Process: {process_result}") print(f"Result: {result}") print(f"Comments: {comments}") if __name__ == "__main__": # Parse command line arguments using argparse parser = argparse.ArgumentParser(description="Evaluate the accuracy of speaker recognition task.") parser.add_argument("--output", type=str, help="Path to the output.json file") parser.add_argument("--groundtruth", type=str, help="Path to the ground truth (gt.json) file") parser.add_argument("--result", type=str, default="evaluation_result.jsonl", help="Path to store the evaluation results in JSONL format") # Parse command line arguments args = parser.parse_args() # Call evaluation function evaluate_accuracy(args.output, args.groundtruth, args.result)