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# Copyright (c) Microsoft Corporation.
# Licensed under the MIT license.
import logging
import sys
import json
import numpy as np
def read_answers(filename):
answers={}
with open(filename) as f:
for line in f:
line=line.strip()
js=json.loads(line)
answers[js['idx']]=js['target']
return answers
def read_predictions(filename):
predictions={}
with open(filename) as f:
for line in f:
line=line.strip()
idx,label=line.split()
predictions[int(idx)]=int(label)
return predictions
def calculate_scores(answers,predictions):
Acc=[]
for key in answers:
if key not in predictions:
logging.error("Missing prediction for index {}.".format(key))
sys.exit()
Acc.append(answers[key]==predictions[key])
scores={}
scores['Acc']=np.mean(Acc)
return scores
def main():
import argparse
parser = argparse.ArgumentParser(description='Evaluate leaderboard predictions for Defect Detection dataset.')
parser.add_argument('--answers', '-a',help="filename of the labels, in txt format.")
parser.add_argument('--predictions', '-p',help="filename of the leaderboard predictions, in txt format.")
args = parser.parse_args()
answers=read_answers(args.answers)
predictions=read_predictions(args.predictions)
scores=calculate_scores(answers,predictions)
print(scores)
if __name__ == '__main__':
main()
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