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subs-editor.py
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import pandas as pd
import numpy as np
# Created: May 20, 2024
# Change log:
# 1. 支持多人台词
# 2. 台词本和音频都会加上角色名
# Revised: May 29, 2024
# 1. 简化原有代码
# 2. 增加输出同角色的整段台词的srt文件，适用于需要整句台词的情况
fname = input('支持单人/多人台词，请输入csv文件名称（不带后缀）：')
option = input('1.csv转txt（角色台词本）\n2.csv转srt（单句音频）\n3.csv转srt（同场次同角色整句音频）\n请选择操作：')
fn = 'input-csv/' + fname + '.csv'
subs = pd.read_csv(fn, header=None)
subs_arr = np.array(subs)
if option == '1':
# 创建新列表来储存台词、编号、角色
csv_to_txt_list, idx_ls, name_ls = [list() for i in range(3)]
for row in range(subs_arr.shape[0]):
idx_ls.append(subs_arr[row][0]) #存储每一句的编号
name_ls.append(subs_arr[row][3]) #存储每一句的角色
char_name = '【' + subs_arr[row][3] + '】' #角色名的新格式
# 初始化，第一行为：【角色】台词1
if row == 0:
csv_to_txt_list.extend([char_name, subs_arr[row][2]])
# 其他情况需考虑：1.前后两行是否是同一角色？2.如为同一角色，前后两行编号是否连续？
# 若以上两种两况都不满足，则输出文本中需要换行，否则只需加空格，之后再添加新台词
else:
diff = idx_ls[row] - idx_ls[row-1]
if name_ls[row] == name_ls[row-1] and diff == 1:
csv_to_txt_list.append(' ')
else:
csv_to_txt_list.extend(['\n', char_name])
csv_to_txt_list.append(subs_arr[row][2])
ftxt = 'output-text/' + fname + '.txt'
f1 = open(ftxt, 'w')
csv_to_txt_list = ''.join(csv_to_txt_list)
f1.write(csv_to_txt_list)
f1.close()
print('台词本已生成！')
if option == '2':
csv_to_srt_separate_list = list()
for row in range(subs_arr.shape[0]):
char_name = '【' + subs_arr[row][3] + '】'
csv_to_srt_separate_list.extend([str(row+1), '\n', subs_arr[row][1], '\n', char_name, subs_arr[row][2], '\n\n'])
fsrt = 'output-text' + fname + '_单句' + '.srt'
f2 = open(fsrt, 'w')
csv_to_srt_separate_list = ''.join(csv_to_srt_separate_list)
f2.write(csv_to_srt_separate_list)
f2.close()
print('字幕文件（单句）已生成！')
if option == '3':
# 创建新列表来储存标号、角色、每行台词、整合后台词
# 如果是同一个角色的连贯台词，会先被储存在line_list列表中，待确认下一行不属于本场次的台词，将目前line_list中的台词整合、存储进csv_to_srt_combined_list后，清空line_list列表，用于储存下一场次的台词
idx_ls, name_ls, line_ls, csv_to_srt_combined_list = [list() for i in range(4)]
count = 0
# time_start为每一个场次的第一句台词对应的时间戳，当读取到本场次的最后一句台词时，会将time_start的结束时间更改为最后一句台词对应的结束时间
time_start = ''
for row in range(subs_arr.shape[0]):
idx_ls.append(subs_arr[row][0])
name_ls.append(subs_arr[row][3])
char_name = '【' + subs_arr[row][3] + '】'
if row == 0:
count = count + 1
csv_to_srt_combined_list.append(str(count))
line_ls.extend([char_name, subs_arr[row][2]])
time_start = subs_arr[row][1]
else:
diff = idx_ls[row] - idx_ls[row-1]
# 当处在同一角色、同一场次时，直接往line_ls里添加新的散台词
if name_ls[row] == name_ls[row-1] and diff == 1:
line_ls.append(subs_arr[row][2])
# 剩余情况（同一角色但不同场次，或不同角色），需要将目前line_ls储存进csv_to_srt_combined_list，再清空line_ls
else:
t_new_split = time_start.split()
t_end_split = subs_arr[row-1][1].split()
t_new_split[2] = t_end_split[2]
csv_to_srt_combined_list.append(' '.join(t_new_split))
csv_to_srt_combined_list.append(' '.join(line_ls))
count = count + 1
csv_to_srt_combined_list.append(str(count))
line_ls = []
line_ls.extend([char_name, subs_arr[row][2]])
time_start = subs_arr[row][1]
# 如果是最后一行，则把此行的结束时间和台词直接写入
if row == (subs_arr.shape[0] - 1):
t_new_split = time_start.split()
t_end_split = subs_arr[row][1].split()
t_new_split[2] = t_end_split[2]
csv_to_srt_combined_list.append(' '.join(t_new_split))
csv_to_srt_combined_list.append(' '.join(line_ls))
np_list = np.array(csv_to_srt_combined_list)
n = 3
m = int(len(csv_to_srt_combined_list)/n)
np_list_new = np_list.reshape(m,n)
combined_srt_list = list()
for x in range(np_list_new.shape[0]):
for y in range(np_list_new.shape[1]):
combined_srt_list.extend([np_list_new[x][y],'\n'])
combined_srt_list.append('\n')
fsrt = 'output-text/' + fname + '.srt'
f2 = open(fsrt, 'w')
csv_to_srt_list = ''.join(combined_srt_list)
f2.write(csv_to_srt_list)
f2.close()
print('字幕文件（整合）已生成！')