[kws] add code for plotting det curve

format

format

format

format

examples/hey_snips/s0/run.sh

@@ -106,6 +106,10 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
       --score_file $result_dir/score.txt \
       --stats_file $result_dir/stats.${keyword}.txt
   done
+  python kws/bin/plot_det_curve.py \
+    --keywords 'Hey_Snips' \
+    --stats_dir $result_dir \
+    --figure_file $result_dir/det.png
 fi
 
 

kws/bin/plot_det_curve.py

@@ -0,0 +1,74 @@
+# Copyright (c) 2021 Binbin Zhang(binbzha@qq.com)
+#                    Menglong Xu
+#
+# 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.
+
+import argparse
+import os
+import numpy as np
+import matplotlib.pyplot as plt
+
+
+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)])
+    values.reverse()
+    return np.array(values)
+
+
+def plot_det_curve(keywords, stats_dir, figure_file):
+    plt.figure(dpi=200)
+    plt.rcParams['xtick.direction'] = 'in'
+    plt.rcParams['ytick.direction'] = 'in'
+    plt.rcParams['text.usetex'] = True
+    plt.rcParams['font.size'] = 12
+
+    for index, keyword in enumerate(keywords):
+        stats_file = os.path.join(stats_dir, 'stats.' + str(index) + '.txt')
+        values = load_stats_file(stats_file)
+        plt.plot(values[:, 0], values[:, 1], label=keyword)
+
+    plt.xlim([0, 5])
+    plt.ylim([0, 0.35])
+    plt.xticks([0, 1, 2, 3, 4, 5], ['0', '1', '2', '3', '4', '5'])
+    plt.yticks([0, 0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35],
+               ['0', '5', '10', '15', '20', '25', '30', '35'])
+    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__':
+    parser = argparse.ArgumentParser(description='plot det curve')
+    parser.add_argument(
+        '--keywords',
+        required=True,
+        help=('keywords, must in the same order as in "dict/words.txt", ' +
+              'separated by ", "')
+    )
+    parser.add_argument('--stats_dir', required=True, help='dir of stats files')
+    parser.add_argument(
+        '--figure_file',
+        required=True,
+        help='path to save det curve')
+
+    args = parser.parse_args()
+
+    keywords = args.keywords.strip().split(', ')
+    plot_det_curve(keywords, args.stats_dir, args.figure_file)

requirements.txt

@@ -2,3 +2,4 @@ flake8==3.8.2
 pyyaml>=5.1
 tensorboard
 tensorboardX
+matplotlib