Spaces:
Running
Running
File size: 9,746 Bytes
6d4ec85 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 |
import json
import os.path
import re
from timeit import default_timer as timer
from faster_whisper import WhisperModel
from loguru import logger
from app.config import config
from app.utils import utils
model_size = config.whisper.get("model_size", "large-v3")
device = config.whisper.get("device", "cpu")
compute_type = config.whisper.get("compute_type", "int8")
model = None
def create(audio_file, subtitle_file: str = ""):
global model
if not model:
model_path = f"{utils.root_dir()}/models/whisper-{model_size}"
model_bin_file = f"{model_path}/model.bin"
if not os.path.isdir(model_path) or not os.path.isfile(model_bin_file):
model_path = model_size
logger.info(
f"loading model: {model_path}, device: {device}, compute_type: {compute_type}"
)
try:
model = WhisperModel(
model_size_or_path=model_path, device=device, compute_type=compute_type
)
except Exception as e:
logger.error(
f"failed to load model: {e} \n\n"
f"********************************************\n"
f"this may be caused by network issue. \n"
f"please download the model manually and put it in the 'models' folder. \n"
f"see [README.md FAQ](https://github.com/harry0703/MoneyPrinterTurbo) for more details.\n"
f"********************************************\n\n"
)
return None
logger.info(f"start, output file: {subtitle_file}")
if not subtitle_file:
subtitle_file = f"{audio_file}.srt"
segments, info = model.transcribe(
audio_file,
beam_size=5,
word_timestamps=True,
vad_filter=True,
vad_parameters=dict(min_silence_duration_ms=500),
)
logger.info(
f"detected language: '{info.language}', probability: {info.language_probability:.2f}"
)
start = timer()
subtitles = []
def recognized(seg_text, seg_start, seg_end):
seg_text = seg_text.strip()
if not seg_text:
return
msg = "[%.2fs -> %.2fs] %s" % (seg_start, seg_end, seg_text)
logger.debug(msg)
subtitles.append(
{"msg": seg_text, "start_time": seg_start, "end_time": seg_end}
)
for segment in segments:
words_idx = 0
words_len = len(segment.words)
seg_start = 0
seg_end = 0
seg_text = ""
if segment.words:
is_segmented = False
for word in segment.words:
if not is_segmented:
seg_start = word.start
is_segmented = True
seg_end = word.end
# If it contains punctuation, then break the sentence.
seg_text += word.word
if utils.str_contains_punctuation(word.word):
# remove last char
seg_text = seg_text[:-1]
if not seg_text:
continue
recognized(seg_text, seg_start, seg_end)
is_segmented = False
seg_text = ""
if words_idx == 0 and segment.start < word.start:
seg_start = word.start
if words_idx == (words_len - 1) and segment.end > word.end:
seg_end = word.end
words_idx += 1
if not seg_text:
continue
recognized(seg_text, seg_start, seg_end)
end = timer()
diff = end - start
logger.info(f"complete, elapsed: {diff:.2f} s")
idx = 1
lines = []
for subtitle in subtitles:
text = subtitle.get("msg")
if text:
lines.append(
utils.text_to_srt(
idx, text, subtitle.get("start_time"), subtitle.get("end_time")
)
)
idx += 1
sub = "\n".join(lines) + "\n"
with open(subtitle_file, "w", encoding="utf-8") as f:
f.write(sub)
logger.info(f"subtitle file created: {subtitle_file}")
def file_to_subtitles(filename):
if not filename or not os.path.isfile(filename):
return []
times_texts = []
current_times = None
current_text = ""
index = 0
with open(filename, "r", encoding="utf-8") as f:
for line in f:
times = re.findall("([0-9]*:[0-9]*:[0-9]*,[0-9]*)", line)
if times:
current_times = line
elif line.strip() == "" and current_times:
index += 1
times_texts.append((index, current_times.strip(), current_text.strip()))
current_times, current_text = None, ""
elif current_times:
current_text += line
return times_texts
def levenshtein_distance(s1, s2):
if len(s1) < len(s2):
return levenshtein_distance(s2, s1)
if len(s2) == 0:
return len(s1)
previous_row = range(len(s2) + 1)
for i, c1 in enumerate(s1):
current_row = [i + 1]
for j, c2 in enumerate(s2):
insertions = previous_row[j + 1] + 1
deletions = current_row[j] + 1
substitutions = previous_row[j] + (c1 != c2)
current_row.append(min(insertions, deletions, substitutions))
previous_row = current_row
return previous_row[-1]
def similarity(a, b):
distance = levenshtein_distance(a.lower(), b.lower())
max_length = max(len(a), len(b))
return 1 - (distance / max_length)
def correct(subtitle_file, video_script):
subtitle_items = file_to_subtitles(subtitle_file)
script_lines = utils.split_string_by_punctuations(video_script)
corrected = False
new_subtitle_items = []
script_index = 0
subtitle_index = 0
while script_index < len(script_lines) and subtitle_index < len(subtitle_items):
script_line = script_lines[script_index].strip()
subtitle_line = subtitle_items[subtitle_index][2].strip()
if script_line == subtitle_line:
new_subtitle_items.append(subtitle_items[subtitle_index])
script_index += 1
subtitle_index += 1
else:
combined_subtitle = subtitle_line
start_time = subtitle_items[subtitle_index][1].split(" --> ")[0]
end_time = subtitle_items[subtitle_index][1].split(" --> ")[1]
next_subtitle_index = subtitle_index + 1
while next_subtitle_index < len(subtitle_items):
next_subtitle = subtitle_items[next_subtitle_index][2].strip()
if similarity(
script_line, combined_subtitle + " " + next_subtitle
) > similarity(script_line, combined_subtitle):
combined_subtitle += " " + next_subtitle
end_time = subtitle_items[next_subtitle_index][1].split(" --> ")[1]
next_subtitle_index += 1
else:
break
if similarity(script_line, combined_subtitle) > 0.8:
logger.warning(
f"Merged/Corrected - Script: {script_line}, Subtitle: {combined_subtitle}"
)
new_subtitle_items.append(
(
len(new_subtitle_items) + 1,
f"{start_time} --> {end_time}",
script_line,
)
)
corrected = True
else:
logger.warning(
f"Mismatch - Script: {script_line}, Subtitle: {combined_subtitle}"
)
new_subtitle_items.append(
(
len(new_subtitle_items) + 1,
f"{start_time} --> {end_time}",
script_line,
)
)
corrected = True
script_index += 1
subtitle_index = next_subtitle_index
# Process the remaining lines of the script.
while script_index < len(script_lines):
logger.warning(f"Extra script line: {script_lines[script_index]}")
if subtitle_index < len(subtitle_items):
new_subtitle_items.append(
(
len(new_subtitle_items) + 1,
subtitle_items[subtitle_index][1],
script_lines[script_index],
)
)
subtitle_index += 1
else:
new_subtitle_items.append(
(
len(new_subtitle_items) + 1,
"00:00:00,000 --> 00:00:00,000",
script_lines[script_index],
)
)
script_index += 1
corrected = True
if corrected:
with open(subtitle_file, "w", encoding="utf-8") as fd:
for i, item in enumerate(new_subtitle_items):
fd.write(f"{i + 1}\n{item[1]}\n{item[2]}\n\n")
logger.info("Subtitle corrected")
else:
logger.success("Subtitle is correct")
if __name__ == "__main__":
task_id = "c12fd1e6-4b0a-4d65-a075-c87abe35a072"
task_dir = utils.task_dir(task_id)
subtitle_file = f"{task_dir}/subtitle.srt"
audio_file = f"{task_dir}/audio.mp3"
subtitles = file_to_subtitles(subtitle_file)
print(subtitles)
script_file = f"{task_dir}/script.json"
with open(script_file, "r") as f:
script_content = f.read()
s = json.loads(script_content)
script = s.get("script")
correct(subtitle_file, script)
subtitle_file = f"{task_dir}/subtitle-test.srt"
create(audio_file, subtitle_file)
|