96 lines
4.2 KiB
Python
96 lines
4.2 KiB
Python
# Copyright (c) 2021 Binbin Zhang(binbzha@qq.com)
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# 2022 Shaoqing Yu(yu954793264@163.com)
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import argparse
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import json
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from collections import defaultdict
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def load_label_and_score(keyword, label_file, score_file):
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score_table = defaultdict(list)
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with open(score_file, 'r', encoding='utf8') as fin:
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for line in fin:
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arr = line.strip().split()
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key = arr[0]
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str_list = arr[1:]
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scores = list(map(float, str_list))
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score_table[key].append(scores)
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keyword_table = {}
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filler_table = {}
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filler_duration = 0.0
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with open(label_file, 'r', encoding='utf8') as fin:
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for line in fin:
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obj = json.loads(line.strip())
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assert 'key' in obj
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assert 'txt' in obj
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assert 'duration' in obj
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key = obj['key']
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index = obj['txt']
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duration = obj['duration']
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assert key in score_table
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if index == keyword:
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keyword_table[key] = score_table[key]
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else:
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filler_table[key] = score_table[key]
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filler_duration += duration
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return keyword_table, filler_table, filler_duration
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if __name__ == '__main__':
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parser = argparse.ArgumentParser(description='compute det curve')
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parser.add_argument('--test_data', required=True, help='label file')
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parser.add_argument('--keyword', type=int, default=0, help='score file')
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parser.add_argument('--score_file', required=True, help='score file')
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parser.add_argument('--step', type=float, default=0.01, help='score file')
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parser.add_argument('--window_shift', type=int, default=50,
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help='window_shift is used to skip the frames after triggered')
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parser.add_argument('--stats_file',
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required=True,
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help='false reject/alarm stats file')
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args = parser.parse_args()
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window_shift = args.window_shift
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keyword_table, filler_table, filler_duration = load_label_and_score(
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args.keyword, args.test_data, args.score_file)
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print('Filler total duration Hours: {}'.format(filler_duration / 3600.0))
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with open(args.stats_file, 'w', encoding='utf8') as fout:
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keyword_index = int(args.stats_file.split('/')[-1].split('.')[1])
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threshold = 0.0
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while threshold <= 1.0:
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num_false_reject = 0
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# transverse the all keyword_table
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for key, scores_list in keyword_table.items():
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# computer positive test sample, use the max score of list.
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score = max(scores_list[keyword_index])
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if float(score) < threshold:
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num_false_reject += 1
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num_false_alarm = 0
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# transverse the all filler_table
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for key, scores_list in filler_table.items():
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i = 0
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score_list = scores_list[keyword_index]
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while i < len(score_list):
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if score_list[i] >= threshold:
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num_false_alarm += 1
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i += window_shift
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else:
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i += 1
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if len(keyword_table) != 0 :
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false_reject_rate = num_false_reject / len(keyword_table)
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num_false_alarm = max(num_false_alarm, 1e-6)
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if filler_duration != 0:
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false_alarm_per_hour = num_false_alarm / (filler_duration / 3600.0)
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fout.write('{:.6f} {:.6f} {:.6f}\n'.format(threshold,
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false_alarm_per_hour,
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false_reject_rate))
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threshold += args.step
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