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'])
