def main(): """Main function to evaluate the pattern discovery task.""" parser = argparse.ArgumentParser( description="mir_eval pattern discovery evaluation", formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument('-o', dest='output_file', default=None, type=str, action='store', help='Store results in json format') parser.add_argument("reference_file", action="store", help="Path to the reference file.") parser.add_argument("estimated_file", action="store", help="Path to the estimation file.") parameters = vars(parser.parse_args(sys.argv[1:])) # Load in data ref_patterns = mir_eval.io.load_patterns(parameters['reference_file']) est_patterns = mir_eval.io.load_patterns(parameters['estimated_file']) # Compute all the scores scores = mir_eval.pattern.evaluate(ref_patterns, est_patterns) print("{} vs. {}".format(os.path.basename(parameters['reference_file']), os.path.basename(parameters['estimated_file']))) eval_utilities.print_evaluation(scores) if parameters['output_file']: print('Saving results to: ', parameters['output_file']) eval_utilities.save_results(scores, parameters['output_file'])
def main(): """Main function to evaluate the pattern discovery task.""" parser = argparse.ArgumentParser(description="mir_eval pattern discovery " "evaluation", formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument('-o', dest='output_file', default=None, type=str, action='store', help='Store results in json format') parser.add_argument("reference_file", action="store", help="Path to the reference file.") parser.add_argument("estimated_file", action="store", help="Path to the estimation file.") parameters = vars(parser.parse_args(sys.argv[1:])) # Load in data ref_patterns = mir_eval.io.load_patterns(parameters['reference_file']) est_patterns = mir_eval.io.load_patterns(parameters['estimated_file']) # Compute all the scores scores = mir_eval.pattern.evaluate(ref_patterns, est_patterns) print "{} vs. {}".format(os.path.basename(parameters['reference_file']), os.path.basename(parameters['estimated_file'])) eval_utilities.print_evaluation(scores) if parameters['output_file']: print 'Saving results to: ', parameters['output_file'] eval_utilities.save_results(scores, parameters['output_file'])
action='store', help='Store results in json format') parser.add_argument('reference_file', action='store', help='path to the reference annotation file') parser.add_argument('estimated_file', action='store', help='path to the estimated annotation file') return vars(parser.parse_args(sys.argv[1:])) if __name__ == '__main__': # Get the parameters parameters = process_arguments() # Load in data reference_onsets = mir_eval.io.load_events(parameters['reference_file']) estimated_onsets = mir_eval.io.load_events(parameters['estimated_file']) # Compute all the scores scores = mir_eval.onset.evaluate(reference_onsets, estimated_onsets) print "{} vs. {}".format(os.path.basename(parameters['reference_file']), os.path.basename(parameters['estimated_file'])) eval_utilities.print_evaluation(scores) if parameters['output_file']: print 'Saving results to: ', parameters['output_file'] eval_utilities.save_results(scores, parameters['output_file'])