Spaces:
Sleeping
Sleeping
File size: 3,399 Bytes
1fe2f2f |
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 |
from utils.bad_words import words
import re
from models.whisper import model
import random
import string
import subprocess
class Wash:
def __init__(self, custom_db = None):
self.db = words
if(custom_db):
self.db = custom_db
@staticmethod
def clean(phrase):
return re.sub(r'\s+', ' ', phrase.lower())
@staticmethod
def tokenize(phrase):
with_punctuation = re.sub(r'[^a-zA-Z\s]', '', phrase).split()
without_punctuation = re.sub(r'[^a-zA-Z\s]', '', phrase).split()
return with_punctuation + without_punctuation
def words(self):
return self.db
def check_word(self, word):
word = word.replace(" ", "")
bad_words = self.words()
tokens = self.tokenize(word)
for token in tokens:
if token in bad_words:
return True
return False
def generate_random_name(self, length):
letters = string.ascii_lowercase
return ''.join(random.choice(letters) for _ in range(length))
def insert_beep(self, itensList, original_file, offset=0):
if not itensList:
return
output = self.generate_random_name(8) + ".wav"
filter_str = "[0]volume=0:enable=\'"
for i, item in enumerate(itensList):
start = item["start"]
end = item["end"]
start_plus_offset = round(start + offset, 2)
end_minus_offset = round(end - offset, 2)
filter_str += f'between(t,{start_plus_offset},{end_minus_offset})'
if i != len(itensList) - 1:
filter_str += '+'
else:
filter_str += "\'"
for item in itensList:
start = round(item["start"], 2)
end = round(item["end"], 2)
start_plus_offset = round(start + offset, 2)
end_minus_offset = round(end - offset, 2)
filter_str += f'[main{start}];'
filter_str += f'sine=d={round(end_minus_offset - start_plus_offset, 2)}:f=1000,adelay={start_plus_offset * 1000}s,pan=stereo|FL=c0|FR=c0[beep{start}];'
filter_str += f'[main{start}][beep{start}]amix=inputs=2:duration=longest'
filter_str = filter_str.rstrip(',')
ffmpeg_cmd = [
"ffmpeg",
"-i",
original_file,
"-filter_complex",
filter_str,
output
]
result = subprocess.run(ffmpeg_cmd)
return output
def process_audio(self, audio_path, offset):
bad_time = []
segments, info = model.transcribe(audio_path, word_timestamps=True, beam_size=1, best_of=1)
for segment in segments:
for word in segment.words:
is_profane = self.check_word(word.word)
if(is_profane):
bad_time.append({
"start": word.start,
"end": word.end,
})
result = self.insert_beep(bad_time, audio_path, offset)
if(result):
return result
return audio_path
def check(self, phrase):
cleaned_phrase = self.clean(phrase)
cleaned_phrase = phrase.replace(" ", "")
tokens = self.tokenize(cleaned_phrase)
bad_words = self.words()
for token in tokens:
if token in bad_words:
return True
return False |