1. [add] 将日志文件打到本地；

PaddlePaddle_DeepSpeech2/infer_path.py

@@ -7,6 +7,7 @@ from paddlespeech.cli import ASRExecutor
 from PaddlePaddle_DeepSpeech2.data_utils.audio_process import AudioInferProcess
 from PaddlePaddle_DeepSpeech2.utils.predict import Predictor
 from PaddlePaddle_DeepSpeech2.utils.audio_vad import crop_audio_vad
+from detect_with_asr import write_to_sheet
 import os
 
 normal_speed = 4
@@ -41,7 +42,7 @@ normal_speed = 4
 
 
 # 使用paddle deepspeech进行语音识别
-def predict_long_audio_with_paddle(wav_path, pre_time, state):
+def predict_long_audio_with_paddle(wav_path, pre_time, book_name, sheet_name, state):
     # 获取数据生成器，处理数据和获取字典需要
     vocab_path = './PaddlePaddle_DeepSpeech2/dataset/zh_vocab.txt'
     mean_std_path = './PaddlePaddle_DeepSpeech2/dataset/mean_std.npz'
@@ -87,13 +88,16 @@ def predict_long_audio_with_paddle(wav_path, pre_time, state):
         )
         if text:
             if i == 0 or (i > 0 and time_stamps[i][0] - last_time >= 1):
-                recommend_lens = int(time_stamps[i][0] * normal_speed) if i == 0 else int(
-                    (time_stamps[i][0] - last_time) * normal_speed)
-                narratages.append(["", "", "", "插入旁白，推荐字数为%d" % recommend_lens])
-            narratages.append(
+                recommend_lens = int((time_stamps[i][0] - last_time) * normal_speed)
+                # narratages.append(["", "", "", "插入旁白，推荐字数为%d" % recommend_lens])
+                write_to_sheet(book_name, sheet_name, ["", "", "", "插入旁白，推荐字数为%d" % recommend_lens])
+            # narratages.append([round(time_stamps[i][0] + pre_time, 2), round(time_stamps[i][1] + pre_time, 2),
+            # text, ''])
+            write_to_sheet(book_name, sheet_name,
                            [round(time_stamps[i][0] + pre_time, 2), round(time_stamps[i][1] + pre_time, 2), text, ''])
             last_time = time_stamps[i][1]
-        print("第%d个分割音频 对应时间为%.2f-%.2f 识别结果: %s" % (i, time_stamps[i][0] + pre_time, time_stamps[i][1] + pre_time, text))
+        print(
+            "第%d个分割音频 对应时间为%.2f-%.2f 识别结果: %s" % (i, time_stamps[i][0] + pre_time, time_stamps[i][1] + pre_time, text))
         state[0] = float((i + 1) / len(audios_path)) if state[0] is None or state[0] < 0.99 else 0.99
     print("最终结果，消耗时间：%d, 识别结果: %s" % (round((time.time() - start) * 1000), texts))
 

detect_with_asr.py

@@ -8,6 +8,48 @@ from openpyxl.styles import PatternFill, Alignment
 from split_wav import *
 
 
+def create_sheet(path, sheet_name, value):
+    """
+        根据给定的表头，初始化表格，
+        :param path: str, 表格(book)的存储位置
+        :param sheet_name: str, 表(sheet)的名字
+        :param value: list, 表头内容为['起始时间','终止时间','字幕','建议','旁边解说脚本']
+        :return: None
+    """
+    index = len(value)
+    workbook = openpyxl.Workbook()
+    sheet = workbook.active
+    sheet.title = sheet_name
+    # 将字幕对应的那一列扩宽一些
+    sheet.column_dimensions['C'].width = 50
+    sheet.column_dimensions['D'].width = 30
+    for i in range(0, index):
+        for j in range(0, len(value[i])):
+            sheet.cell(row=i + 1, column=j + 1, value=str(value[i][j]))
+    workbook.save(path)
+
+
+def write_to_sheet(path, sheet_name, value):
+    """
+    向已存在的表格中写入数据
+    :param path:
+    :param sheet_name:
+    :param value:
+    :return:
+    """
+    index = len(value)
+    workbook = openpyxl.load_workbook(path)
+    sheet = workbook.get_sheet_by_name(sheet_name)
+    cur_row = sheet.max_row
+    for j in range(0, index):
+        sheet.cell(row=cur_row + 1, column=j + 1, value=str(value[j]))
+        if value[j] == '' or '插入旁白' in str(value[j]):
+            sheet.cell(row=cur_row + 1, column=j + 1).fill = PatternFill(fill_type='solid', fgColor='ffff00')
+        if j == 2:
+            sheet.cell(row=cur_row + 1, column=j + 1).alignment = Alignment(wrapText=True)
+    workbook.save(path)
+
+
 def trans_to_mono(wav_path):
     """
     将音频的通道数channel转换为1
@@ -53,15 +95,16 @@ def detect_with_asr(video_path, book_path, start_time=0, end_time=-1, state=None
     # audio_path = trans_to_mono(total_wav_path)
 
     # xlsx中的表格名为“旁白插入位置建议”
+    if os.path.exists(book_path):
+        os.remove(book_path)
     book_name_xlsx = book_path
     sheet_name_xlsx = "旁白插入位置建议"
+    table_head = [["起始时间", "终止时间", "字幕", '建议', '解说脚本']]
+    create_sheet(book_name_xlsx, sheet_name_xlsx, table_head)
 
-    sys.path.append("./PaddlePaddle_DeepSpeech2")
+    sys.path.append("PaddlePaddle_DeepSpeech2")
     from infer_path import predict_long_audio_with_paddle
-    table_head = [["起始时间", "终止时间", "字幕", '建议', '解说脚本']]
-    table_content = table_head + predict_long_audio_with_paddle(audio_path, start_time, state)
-    from detect_with_ocr import write_excel_xlsx
-    write_excel_xlsx(book_name_xlsx, sheet_name_xlsx, table_content)
+    predict_long_audio_with_paddle(audio_path, start_time, book_name_xlsx, sheet_name_xlsx, state)
     # 删除中间文件
     shutil.rmtree(tmp_root)
     state[0] = 1

detect_with_ocr.py

-import time
+import os
+# import time
 
 import cv2
 import numpy as np
 from paddleocr import PaddleOCR
 import difflib
-import openpyxl
-from openpyxl.styles import PatternFill, Alignment
+# from openpyxl.styles import PatternFill, Alignment
+# from openpyxl import Workbook
 import re
+from detect_with_asr import create_sheet, write_to_sheet
 
 # 字幕的上下边界
 up_b, down_b = 0, 0
@@ -138,15 +140,15 @@ def detect_subtitle(img):
     bottom_position = None
     if len(res) == 0:
         return None
-    log = []
+    # log = []
     possible_txt = []
     for x in res:
         rect, (txt, confidence) = x
         font_size = rect[2][1] - rect[0][1]
         mid = (rect[0][0] + rect[1][0]) / 2
         gradient = np.arctan(abs((rect[1][1] - rect[0][1]) / (rect[1][0] - rect[0][0])))
-        log.append("文本：{}，置信度：{}，中心点：{}，斜率：{}，字体大小：{}".format(txt, confidence, mid / img.shape[1], gradient, font_size))
-        # 置信度>0.7 & 斜率<0.1 & 字幕偏移量<=25 & 字幕中心在画面宽的0.4-0.6之间
+        # log.append("文本：{}，置信度：{}，中心点：{}，斜率：{}，字体大小：{}".format(txt, confidence, mid / img.shape[1], gradient,
+        # font_size)) 置信度>0.7 & 斜率<0.1 & 字幕偏移量<=25 & 字幕中心在画面宽的0.4-0.6之间
         if confidence > 0.7 and gradient < 0.1 and 0.4 < mid / img.shape[1] < 0.6 and \
                 abs(rect[0][1] - 30) + abs(img.shape[0] - rect[2][1] - 30) <= 25:
             subTitle += txt
@@ -161,12 +163,15 @@ def detect_subtitle(img):
     return None
 
 
-def process_video(video_path, begin, end, state):
+def process_video(video_path, begin, end, book_path, sheet_name, state):
     """
     处理视频，主要完成对字幕的捕捉以及根据字幕分析得出旁白可能位置的任务
     :param video_path: 待处理视频的路径
     :param begin: 电影的实际开始位置（秒）
     :param end: 电影除演职表外的实际结束位置（秒）
+    :param book_path: 输出表格地址
+    :param sheet_name: 输出表格中的表名
+    :param state: 用于通信的状态关键字
     :return:
     """
     video = cv2.VideoCapture(video_path)
@@ -203,9 +208,11 @@ def process_video(video_path, begin, end, state):
                     print('--------------------------------------------------')
                     recommend_lens = int(res[-1][0] * normal_speed) if len(res) == 1 else int(
                         (res[-1][0] - res[-2][1]) * normal_speed)
-                    narratage_recommend.append(['', '', '', '插入旁白，推荐字数为%d' % recommend_lens])
+                    # narratage_recommend.append(['', '', '', '插入旁白，推荐字数为%d' % recommend_lens])
+                    write_to_sheet(book_path, sheet_name, ['', '', '', '插入旁白，推荐字数为%d' % recommend_lens])
                 print(start_time, end_time, lastSubTitle)
-                narratage_recommend.append([round(start_time, 2), round(end_time, 2), lastSubTitle, ''])
+                # narratage_recommend.append([round(start_time, 2), round(end_time, 2), lastSubTitle, ''])
+                write_to_sheet(book_path, sheet_name, [round(start_time, 2), round(end_time, 2), lastSubTitle, ''])
             # 两句话连在一起，但是两句话不一样
             elif lastSubTitle is not None and subTitle is not None:
                 if string_similar(lastSubTitle, subTitle) < 0.7:
@@ -215,9 +222,11 @@ def process_video(video_path, begin, end, state):
                         print('--------------------------------------------------')
                         recommend_lens = int(res[-1][0] * normal_speed) if len(res) == 1 else int(
                             (res[-1][0] - res[-2][1]) * normal_speed)
-                        narratage_recommend.append(['', '', '', '插入旁白，推荐字数为%d' % recommend_lens])
+                        # narratage_recommend.append(['', '', '', '插入旁白，推荐字数为%d' % recommend_lens])
+                        write_to_sheet(book_path, sheet_name, ['', '', '', '插入旁白，推荐字数为%d' % recommend_lens])
                     print(start_time, end_time, lastSubTitle)
-                    narratage_recommend.append([round(start_time, 2), round(end_time, 2), lastSubTitle, ''])
+                    # narratage_recommend.append([round(start_time, 2), round(end_time, 2), lastSubTitle, ''])
+                    write_to_sheet(book_path, sheet_name, [round(start_time, 2), round(end_time, 2), lastSubTitle, ''])
                     start_time = end_time
                 else:
                     lastSubTitle = subTitle if len(subTitle) > len(lastSubTitle) else lastSubTitle
@@ -229,35 +238,38 @@ def process_video(video_path, begin, end, state):
                 print('--------------------------------------------------')
                 recommend_lens = int(res[-1][0] * normal_speed) if len(res) == 1 else int(
                     (res[-1][0] - res[-2][1]) * normal_speed)
-                narratage_recommend.append(['', '', '', '插入旁白，推荐字数为%d' % recommend_lens])
+                # narratage_recommend.append(['', '', '', '插入旁白，推荐字数为%d' % recommend_lens])
+                write_to_sheet(book_path, sheet_name, ['', '', '', '插入旁白，推荐字数为%d' % recommend_lens])
                 break
     return narratage_recommend
 
 
-def write_excel_xlsx(path, sheet_name, value):
-    """
-    将旁白推荐信息输出表格
-    :param path: 输出表格的存储路径
-    :param sheet_name:表格中的表名
-    :param value:输出到表格中的信息
-    :return:
-    """
-    index = len(value)
-    workbook = openpyxl.Workbook()
-    sheet = workbook.active
-    sheet.title = sheet_name
-    # 将字幕对应的那一列扩宽一些
-    sheet.column_dimensions['C'].width = 50
-    sheet.column_dimensions['D'].width = 30
-    for i in range(0, index):
-        for j in range(0, len(value[i])):
-            sheet.cell(row=i + 1, column=j + 1, value=str(value[i][j])).alignment = Alignment(wrapText=True)
-            if value[i][j] == '' or '插入旁白' in str(value[i][j]) or value[i][j] == '翻译':
-                sheet.cell(row=i + 1, column=j + 1).fill = PatternFill(fill_type='solid', fgColor='ffff00')
-    workbook.save(path)
+# def write_excel_xlsx(path, sheet_name, value):
+#     """
+#     将旁白推荐信息输出表格
+#     :param path: 输出表格的存储路径
+#     :param sheet_name:表格中的表名
+#     :param value:输出到表格中的信息
+#     :return:
+#     """
+#     index = len(value)
+#     workbook = Workbook()
+#     sheet = workbook.active
+#     sheet.title = sheet_name
+#     # 将字幕对应的那一列扩宽一些
+#     sheet.column_dimensions['C'].width = 50
+#     sheet.column_dimensions['D'].width = 30
+#     for i in range(0, index):
+#         for j in range(0, len(value[i])):
+#             sheet.cell(row=i + 1, column=j + 1, value=str(value[i][j])).alignment = Alignment(wrapText=True)
+#             if value[i][j] == '' or '插入旁白' in str(value[i][j]) or value[i][j] == '翻译':
+#                 sheet.cell(row=i + 1, column=j + 1).fill = PatternFill(fill_type='solid', fgColor='ffff00')
+#     workbook.save(path)
 
 
 def detect_with_ocr(video_path, book_path, start_time, end_time, state):
+    if os.path.exists(book_path):
+        os.remove(book_path)
     book_name_xlsx = book_path
     sheet_name_xlsx = "旁白插入位置建议"
 
@@ -267,14 +279,12 @@ def detect_with_ocr(video_path, book_path, start_time, end_time, state):
 
     # 获取并构建输出信息
     table_head = [["起始时间", "终止时间", "字幕", '建议', '解说脚本']]
-    table_content = table_head + process_video(video_path, start_time, end_time, state)
-
-    # 输出旁白位置推荐信息到表格
-    write_excel_xlsx(book_name_xlsx, sheet_name_xlsx, table_content)
-    state[0] = 1.00
+    create_sheet(book_name_xlsx, sheet_name_xlsx, table_head)
+    process_video(video_path, start_time, end_time, book_name_xlsx, sheet_name_xlsx, state)
 
 
 if __name__ == '__main__':
-    video_path = "D:/heelo/hysxm_1.mp4"
-    book_path = '何以笙箫默.xlsx'
-    detect_with_ocr(video_path, book_path, 0, 300, [None])
+    pass
+    # video_path = "D:/heelo/hysxm_1.mp4"
+    # book_path = '何以笙箫默.xlsx'
+    # detect_with_ocr(video_path, book_path, 0, 300, [None])

main_gui.py

 # -*- coding:utf-8 -*-
 import threading
+import time
+import traceback
+
 from mttkinter import mtTkinter as tk
 from tkinter import filedialog, ttk, messagebox
+import sys
+import io
 import os
-import ffmpeg
+import datetime
 from speech_synthesis import ss_and_export
 import ctypes
 import inspect
@@ -20,6 +25,55 @@ window.iconbitmap("eagle_2.ico")
 video_duration = ""
 
 
+def create_detail_day():
+    daytime = datetime.datetime.now().strftime('day' + '%Y_%m_%d')
+    return daytime
+
+
+def make_print_to_file(path='./'):
+    class Logger(object):
+        def __init__(self, filename="detect_with_ocr.log", path='./'):
+            if not os.path.exists(path):
+                os.mkdir(path)
+            sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
+            self.terminal = sys.stdout
+            self.log = open(os.path.join(path, filename), "a", encoding='utf8')
+            print(path)
+
+        def write(self, message):
+            self.terminal.write(message)
+            self.log.write(message)
+
+        def flush(self):
+            pass
+
+    sys.stdout = Logger(create_detail_day() + '.log', path=path)
+
+
+# 复写线程，用于解决主线程无法步骤子线程中异常的问题
+class RunThread(threading.Thread):  # The timer class is derived from the class threading.Thread
+    def __init__(self, funcName, name, args=()):
+        threading.Thread.__init__(self)
+        self._args = args
+        self._funcName = funcName
+        self._name = name
+        self.exitcode = 0
+        self.exception = None
+        self.exc_traceback = ''
+
+    def run(self):  # Overwrite run() method, put what you want the thread do here
+        try:
+            self._run()
+        except Exception as e:
+            print(e)
+            self.exitcode = 1  # 如果线程异常退出，将该标志位设置为1，正常退出为0
+            self.exception = e
+            self.exc_traceback = ''.join(traceback.format_exception(*sys.exc_info()))  # 在改成员变量中记录异常信息
+
+    def _run(self):
+        self._funcName(*self._args)
+
+
 def open_video_file():
     """
     打开文件
@@ -33,26 +87,7 @@ def open_video_file():
         inputFilePath.set(video_path)
         # 获取视频的时长等信息，初始化开始结束时间
         startTime.set("00:00:00")
-        info = ffmpeg.probe(video_path)
-        vs = next(c for c in info['streams'] if c['codec_type'] == 'video')
         global video_duration
-        try:
-            duration = int(float(vs['duration']))
-            hours = int(duration / 3600)
-            minutes = int(duration / 60 - 60 * hours)
-            seconds = int(duration - 60 * minutes - 3600 * hours)
-            endTime.set("%02d:%02d:%02d" % (hours, minutes, seconds))
-            video_duration = endTime.get()
-        except KeyError:
-            flag = False
-            for k in vs['tags'].keys():
-                k_l = str.lower(k)
-                if 'duration' in k_l:
-                    duration = vs['tags'][k].split(':')
-                    endTime.set("%02d:%02d:%02d" % (int(duration[0]), int(duration[1]), float(duration[2])))
-                    video_duration = endTime.get()
-                    flag = True
-            if not flag:
         video = cv2.VideoCapture(video_path)
         fps = video.get(cv2.CAP_PROP_FPS)
         duration = video.get(cv2.CAP_PROP_FRAME_COUNT) / fps
@@ -197,20 +232,45 @@ def start_detect():
     processState.set("开始检测")
     # 多线程同步进行检测和进度条更新
     state = [None]
-    threads = [
-        threading.Thread(target=start_process, args=(progressbar_1, progress_1, state, 100000), name="startProgress1"),
-        threading.Thread(target=detect,
+    threads = []
+    t = RunThread(funcName=start_process, args=(progressbar_1, progress_1, state, 100000), name="startProgress1")
+    t.setDaemon(True)
+    threads.append(t)
+    t = RunThread(funcName=detect,
                   args=(video_path, start_time, end_time, book_path, state, hasSubtitle.get()),
-                         name="detect")]
+                  name="detect")
+    t.setDaemon(True)
+    threads.append(t)
+
     for t in threads:
         t.start()
-    # 线程完成任务后结束线程
+
+    # 线程完成任务后结束线程，一旦有一个线程结束就判断是否是意外中断
+    while 1:
+        alive = True
         for t in threads:
-        t.join()
-    # 将进度条的进度拉满到100%，并给出“任务已完成”的提示
-    progressbar_1['value'] = 100
-    progress_1['text'] = '100.0%'
+            alive = alive and t.is_alive()
+        if not alive:
+            break
+        time.sleep(5)
+
+    for t in threads:
+        if t.exitcode != 0:
+            print("Exception in", t.getName())
+            messagebox.showerror("错误", "运行出错，请联系开发者处理")
+            processState.set("任务中断")
+            progress_state = progressbar_1['value']
+            progressbar_1.stop()
+            progressbar_1['value'] = progress_state
+            stopDetection.config(state=tk.DISABLED)
+            startDetection.config(state=tk.ACTIVE)
+            return
+
+    # 若不是意外中断，则将进度条的进度拉满到100%，并给出“任务已完成”的提示
     processState.set("任务已完成")
+    progressbar_1.stop()
+    progressbar_1['value'] = 100
+    progress_1['text'] = "100.00%"
     # 检测完成后，将“停止检测”按钮设置为不可点击状态，”开始检测“按钮设置为可点击状态
     stopDetection.config(state=tk.DISABLED)
     startDetection.config(state=tk.ACTIVE)
@@ -348,21 +408,43 @@ def start_synthesis():
 
     # 多线程同时实现语音合成+字幕导出、进度条
     state = [None]
-    threads = [
-        threading.Thread(target=start_process, args=(progressbar_2, progress_2, state, 100000), name="startProgress2"),
-        threading.Thread(target=ss_and_export,
-                         args=(video_path, sheet_path, audio_dir, speed, caption_path, state), name="ssAndExport")]
+    threads = []
+    t = RunThread(funcName=ss_and_export,
+                  args=(video_path, sheet_path, audio_dir, speed, caption_path, state), name="ssAndExport")
+    t.setDaemon(True)
+    threads.append(t)
+    t = RunThread(funcName=start_process, args=(progressbar_2, progress_2, state, 100000), name="startProgress2")
+    t.setDaemon(True)
+    threads.append(t)
+
     for t in threads:
         t.start()
+
+    # 查询线程是否有结束的，一旦一个结束，另一个也结束
+    while 1:
+        alive = True
+        for t in threads:
+            alive = alive and t.is_alive()
+        if not alive:
+            break
+        time.sleep(5)
+
     for t in threads:
-        t.join()
-    processState_2.set("语音和字幕已导出完毕")
+        if t.exitcode != 0:
+            print("Exception in", t.getName())
+            messagebox.showerror("错误", "运行出错，请联系开发者处理")
+            processState.set("任务中断")
+            progress_state = progressbar_2['value']
+            progressbar_2.stop()
+            progressbar_2['value'] = progress_state
+            startSynthesis.config(state=tk.ACTIVE)
+            stopSynthesis.config(state=tk.DISABLED)
+            return
     startSynthesis.config(state=tk.ACTIVE)
     stopSynthesis.config(state=tk.DISABLED)
 
 
 def stop_synthesis():
-    print(threading.enumerate())
     for x in threading.enumerate():
         if x.getName() in ["startSynthesis", "startProgress2", "ssAndExport"]:
             _async_raise(x.ident, SystemExit)
@@ -593,6 +675,8 @@ def on_closing():
         window.destroy()
 
 
+thread_it(make_print_to_file(os.path.join(os.getcwd(), 'log')), name="logging")
+
 window.protocol("WM_DELETE_WINDOW", on_closing)
 
 # 刷新显示

speech_synthesis.py

@@ -3,7 +3,7 @@ import os
 import argparse
 import time
 
-from azure.cognitiveservices.speech import AudioDataStream, SpeechConfig, SpeechSynthesizer
+from azure.cognitiveservices.speech import AudioDataStream, SpeechConfig, SpeechSynthesizer, ResultReason
 from azure.cognitiveservices.speech.audio import AudioOutputConfig
 import openpyxl
 
@@ -36,8 +36,18 @@ def speech_synthesis(text, output_file, speed):
 
     audio_config = AudioOutputConfig(filename=audio_path)
     synthesizer = SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
+    result = synthesizer.speak_text(text)
+    print(result.reason)
 
-    synthesizer.speak_text(text)
+    while result.reason == ResultReason.Canceled:
+        cancellation_details = result.cancellation_details
+        print("取消的原因", cancellation_details.reason)
+        time.sleep(1)
+        synthesizer.stop_speaking()
+        del synthesizer
+        synthesizer = SpeechSynthesizer(speech_config=speech_config, audio_config=audio_config)
+        result = synthesizer.speak_text(text)
+        print(result.reason)
 
     if float(speed) != 1.0:
         change_speed(output_file, speed)
@@ -100,13 +110,21 @@ def get_narratage_text(sheet_content, speed):
             else:
                 # 如果旁白中有换行符，即分为n段，则按照换行符进行分割，并间隔0.5s
                 text_split = text.split('\n')
-                if subtitle[i] is None:
+                # 如果旁白有对应的时间戳（是这段大旁白里的特定位置）
+                if start_time[i] is not None and end_time[i] is not None:
+                    cur_start = float(start_time[i])
+                    cur_end = float(end_time[i])
+                elif subtitle[i] is None:
                     cur_start = float(end_time[i - 1]) + 0.1 if i > 0 else 0
-                    cur_end = float(start_time[i + 1])
+                    # 如果是最后一句旁白，后面没有字幕及时间戳了，就先把cur_end置为-1
+                    cur_end = float(start_time[i + 1]) if i + 1 < len(start_time) else -1
                 else:
+                    # 有字幕，可覆盖字幕
                     cur_start = float(start_time[i])
                     cur_end = float(end_time[i])
                 for x in text_split:
+                    if len(x) == 0:
+                        continue
                     cur_end = max(cur_end, cur_start + (len(x) / normal_speed + normal_interval) / speed)
                     narratage_text.append(x)
                     narratage_start_time.append(cur_start)
@@ -208,7 +226,6 @@ def ss_and_export(video_path, sheet_path, output_dir, speed, caption_file, state
         wav_path = os.path.join(root_path, '%.2f.wav' % start_timestamp[i])
         narratage_paths.append(wav_path)
         speech_synthesis(text, wav_path, speed)
-        time.sleep(2)
         print("目前正在处理{}".format(wav_path))
         if state is not None:
             state[0] = float((i + 1) / len(narratages)) * 0.97