[kws] add code for plotting det curve (#52)

* [kws] add code for plotting det curve

* format

* format

* format

* format

* [kws] add code for plotting det curve

format

format

format

format

* set xlim and ylim by parameter

* set xlim and ylim optional

* update help information

* update parser type

* Update run.sh

examples/hey_snips/s0/run.sh

@@ -106,6 +106,14 @@ 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 \
+    --xlim 10 \
+    --x_step 2 \
+    --ylim 10 \
+    --y_step 2
 fi
 
 

kws/bin/plot_det_curve.py

@@ -0,0 +1,98 @@
+# 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) * 100])
+    values.reverse()
+    return np.array(values)
+
+
+def plot_det_curve(
+        keywords,
+        stats_dir,
+        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):
+        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, 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__':
+    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')
+    parser.add_argument(
+        '--xlim',
+        type=int,
+        default=5,
+        help='xlim：range of x-axis, x is false alarm per hour')
+    parser.add_argument('--x_step', type=int, default=1, help='step on x-axis')
+    parser.add_argument(
+        '--ylim',
+        type=int,
+        default=35,
+        help='ylim：range of y-axis, y is false rejection rate')
+    parser.add_argument('--y_step', type=int, default=5, help='step on y-axis')
+
+    args = parser.parse_args()
+
+    keywords = args.keywords.strip().split(', ')
+    plot_det_curve(
+        keywords,
+        args.stats_dir,
+        args.figure_file,
+        args.xlim,
+        args.x_step,
+        args.ylim,
+        args.y_step)

requirements.txt

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