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