update compute_det_ctc

examples/hi_xiaowen/s0/run_ctc.sh

@@ -1,6 +1,6 @@
 #!/bin/bash
 # Copyright 2021  Binbin Zhang(binbzha@qq.com)
-#           2023  dujing(thuduj12@163.com)
+#           2023  Jing Du(thuduj12@163.com)
 
 . ./path.sh
 
@@ -29,9 +29,6 @@ trainbase=true
 trainbase_dir=data/base
 trainbase_config=conf/ds_tcn_ctc_base.yaml
 trainbase_exp=exp/base
-if $trainbase; then
-  checkpoint=$trainbase_exp/final.pt
-fi
 
 if [ ${stage} -le -3 ] && [ ${stop_stage} -ge -3 ]; then
   echo "Download and extracte all datasets"
@@ -131,7 +128,8 @@ if [ ${stage} -le 1 ] && [ ${stop_stage} -ge 1 ] && [ $trainbase == true ]; then
       --num_keywords $num_keywords \
       --min_duration 50 \
       --seed 666 \
-      $cmvn_opts
+      $cmvn_opts \
+      --checkpoint $trainbase_exp/23.pt
 fi
 
 if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
@@ -141,6 +139,18 @@ if [ ${stage} -le 2 ] && [ ${stop_stage} -ge 2 ]; then
   $norm_mean && cmvn_opts="--cmvn_file data/train/global_cmvn"
   $norm_var && cmvn_opts="$cmvn_opts --norm_var"
   num_gpus=$(echo $gpus | awk -F ',' '{print NF}')
+
+  if $trainbase; then
+    echo "Use the base model you trained as checkpoint: $trainbase_exp/final.pt"
+    checkpoint=$trainbase_exp/final.pt
+  else
+    echo "Use the base model trained with WenetSpeech as checkpoint: mobvoi_kws_transcription/final.pt"
+    if [ ! -d mobvoi_kws_transcription ] ;then
+      git clone https://www.modelscope.cn/datasets/thuduj12/mobvoi_kws_transcription.git
+    fi
+    checkpoint=mobvoi_kws_transcription/final.pt
+  fi
+
   torchrun --standalone --nnodes=1 --nproc_per_node=$num_gpus \
     wekws/bin/train.py --gpus $gpus \
       --config $config \
@@ -176,7 +186,7 @@ if [ ${stage} -le 3 ] && [ ${stop_stage} -ge 3 ]; then
     --lexicon_file data/lexicon.txt
 
   python wekws/bin/compute_det_ctc.py \
-      --keyword 嗨小问,你好问问 \
+      --keywords 嗨小问,你好问问 \
       --test_data data/test/data.list \
       --window_shift $window_shift \
       --step 0.001  \

wekws/bin/compute_det_ctc.py

@@ -16,10 +16,8 @@
 
 import argparse, logging, glob
 import json, re, os, numpy as np
-import matplotlib.font_manager as fm
 import matplotlib.pyplot as plt
-
+import pypinyin
-font = fm.FontProperties(size=15)
 
 def split_mixed_label(input_str):
     tokens = []
@@ -41,7 +39,6 @@ def space_mixed_label(input_str):
     return space_str.strip()
 
 def load_label_and_score(keywords_list, label_file, score_file):
-    # score_table: {uttid: [keywordlist]}
     score_table = {}
     with open(score_file, 'r', encoding='utf8') as fin:
         # read score file and store in table
@@ -84,7 +81,6 @@ def load_label_and_score(keywords_list, label_file, score_file):
         assert 'duration' in obj
 
         key = obj['key']
-        # wav_file = obj['wav']
         txt = "".join(obj['tok'])
         txt = space_mixed_label(txt)
         txt_regstr_lrblk = ' ' + txt + ' '
@@ -125,12 +121,8 @@ def load_stats_file(stats_file):
     values.reverse()
     return np.array(values)
 
-def plot_det(dets_dir, figure_file, det_title="DetCurve"):
+def plot_det(dets_dir, figure_file, xlim=5, x_step=1, ylim=35, y_step=5):
-    xlim = '[0,2]'
+    det_title = "DetCurve"
-    # xstep = kwargs.get('xstep', '1')
-    ylim = '[15,30]'
-    # ystep = kwargs.get('ystep', '5')
-
     plt.figure(dpi=200)
     plt.rcParams['xtick.direction'] = 'in'
     plt.rcParams['ytick.direction'] = 'in'
@@ -138,33 +130,25 @@ def plot_det(dets_dir, figure_file, det_title="DetCurve"):
 
     for file in glob.glob(f'{dets_dir}/*stats*.txt'):
         logging.info(f'reading det data from {file}')
-        label = os.path.basename(file).split('.')[0]
+        label = os.path.basename(file).split('.')[1]
+        label = "".join(pypinyin.lazy_pinyin(label))
         values = load_stats_file(file)
         plt.plot(values[:, 0], values[:, 1], label=label)
 
-    xlim_splits = xlim.strip().replace('[', '').replace(']', '').split(',')
+    plt.xlim([0, xlim])
-    assert len(xlim_splits) == 2
+    plt.ylim([0, ylim])
-    ylim_splits = ylim.strip().replace('[', '').replace(']', '').split(',')
+    plt.xticks(range(0, xlim + x_step, x_step))
-    assert len(ylim_splits) == 2
+    plt.yticks(range(0, ylim + y_step, y_step))
-
-    plt.xlim(float(xlim_splits[0]), float(xlim_splits[1]))
-    plt.ylim(float(ylim_splits[0]), float(ylim_splits[1]))
-
-    # 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.ylabel('False Rejection Rate (%)')
-    plt.title(det_title, fontproperties=font)
     plt.grid(linestyle='--')
-    # plt.legend(loc='best', fontsize=6)
+    plt.legend(loc='best', fontsize=6)
-    plt.legend(loc='upper right', fontsize=5)
-    # plt.show()
     plt.savefig(figure_file)
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser(description='compute det curve')
     parser.add_argument('--test_data', required=True, help='label file')
-    parser.add_argument('--keyword', type=str, default=None, help='keyword label')
+    parser.add_argument('--keywords', type=str, default=None, help='keywords, split with comma(,)')
     parser.add_argument('--score_file', required=True, help='score file')
     parser.add_argument('--step', type=float, default=0.01,
                         help='threshold step')
@@ -178,10 +162,22 @@ if __name__ == '__main__':
                         required=False,
                         default=None,
                         help='det curve path, default is stats_dir/det.png')
+    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=75,
+        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()
     window_shift = args.window_shift
-    keywords_list = args.keyword.strip().split(',')
+    keywords_list = args.keywords.strip().split(',')
     keyword_filler_table = load_label_and_score(keywords_list, args.test_data, args.score_file)
 
     for keyword in keywords_list:
@@ -238,4 +234,4 @@ if __name__ == '__main__':
         det_curve_path = args.det_curve_path
     else:
         det_curve_path = os.path.join(stats_dir, 'det.png')
-    plot_det(stats_dir, det_curve_path)
+    plot_det(stats_dir, det_curve_path, args.xlim, args.x_step, args.ylim, args.y_step)