|
|
|
|
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
|
|
|
|
#
|
|
|
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
|
|
|
# you may not use this file except in compliance with the License.
|
|
|
|
|
# You may obtain a copy of the License at
|
|
|
|
|
#
|
|
|
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
|
|
|
#
|
|
|
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
|
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
|
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
|
|
|
# See the License for the specific language governing permissions and
|
|
|
|
|
# limitations under the License.
|
|
|
|
|
# Modified from wekws(https://github.com/wenet-e2e/wekws)
|
|
|
|
|
import argparse
|
|
|
|
|
import os
|
|
|
|
|
|
|
|
|
|
import matplotlib.pyplot as plt
|
|
|
|
|
import numpy as np
|
|
|
|
|
|
|
|
|
|
# yapf: disable
|
|
|
|
|
parser = argparse.ArgumentParser(__doc__)
|
|
|
|
|
parser.add_argument('--keyword_label', type=str, required=True, help='keyword string shown on image')
|
|
|
|
|
parser.add_argument('--stats_file', type=str, required=True, help='output file of detection error tradeoff')
|
|
|
|
|
parser.add_argument('--img_file', type=str, default='./det.png', help='output det image')
|
|
|
|
|
args = parser.parse_args()
|
|
|
|
|
# yapf: enable
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def load_stats_file(stats_file):
|
|
|
|
|
values = []
|
|
|
|
|
with open(stats_file, 'r', encoding='utf8') as fin:
|
|
|
|
|
for line in fin:
|
|
|
|
|
arr = line.strip().split()
|
|
|
|
|
threshold, fa_per_hour, frr = arr
|
|
|
|
|
values.append([float(fa_per_hour), float(frr) * 100])
|
|
|
|
|
values.reverse()
|
|
|
|
|
return np.array(values)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
def plot_det_curve(keywords, stats_file, figure_file, xlim, x_step, ylim,
|
|
|
|
|
y_step):
|
|
|
|
|
plt.figure(dpi=200)
|
|
|
|
|
plt.rcParams['xtick.direction'] = 'in'
|
|
|
|
|
plt.rcParams['ytick.direction'] = 'in'
|
|
|
|
|
plt.rcParams['font.size'] = 12
|
|
|
|
|
|
|
|
|
|
for index, keyword in enumerate(keywords):
|
|
|
|
|
values = load_stats_file(stats_file)
|
|
|
|
|
plt.plot(values[:, 0], values[:, 1], label=keyword)
|
|
|
|
|
|
|
|
|
|
plt.xlim([0, xlim])
|
|
|
|
|
plt.ylim([0, ylim])
|
|
|
|
|
plt.xticks(range(0, xlim + x_step, x_step))
|
|
|
|
|
plt.yticks(range(0, ylim + y_step, y_step))
|
|
|
|
|
plt.xlabel('False Alarm Per Hour')
|
|
|
|
|
plt.ylabel('False Rejection Rate (\\%)')
|
|
|
|
|
plt.grid(linestyle='--')
|
|
|
|
|
plt.legend(loc='best', fontsize=16)
|
|
|
|
|
plt.savefig(figure_file)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
if __name__ == '__main__':
|
|
|
|
|
img_file = os.path.abspath(args.img_file)
|
|
|
|
|
stats_file = os.path.abspath(args.stats_file)
|
|
|
|
|
plot_det_curve([args.keyword_label], stats_file, img_file, 10, 2, 10, 2)
|
|
|
|
|
|
|
|
|
|
print('DET curve image saved to: {}'.format(img_file))
|
