Karl/bazarr-ai-sub-generator
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Merge pull request #4 from karl0ss/reworked

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13 changed files with 196 additions and 145 deletions
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53
auto_subtitle/cli.py
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@ -1,53 +0,0 @@
import argparse
from faster_whisper import available_models
from utils.constants import LANGUAGE_CODES
from main import process
from utils.convert import str2bool, str2timeinterval
def main():
"""
Main entry point for the script.
Parses command line arguments, processes the inputs using the specified options,
and performs transcription or translation based on the specified task.
"""
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("--audio_channel", default="0",
type=int, help="audio channel index to use")
parser.add_argument("--sample_interval", type=str2timeinterval, default=None,
help="generate subtitles for a specific \
fragment of the video (e.g. 01:02:05-01:03:45)")
parser.add_argument("--model", default="small",
choices=available_models(), help="name of the Whisper model to use")
parser.add_argument("--device", type=str, default="auto",
choices=["cpu", "cuda", "auto"],
help="Device to use for computation (\"cpu\", \"cuda\", \"auto\")")
parser.add_argument("--compute_type", type=str, default="default", choices=[
"int8", "int8_float32", "int8_float16", "int8_bfloat16",
"int16", "float16", "bfloat16", "float32"],
help="Type to use for computation. \
See https://opennmt.net/CTranslate2/quantization.html.")
parser.add_argument("--beam_size", type=int, default=5,
help="model parameter, tweak to increase accuracy")
parser.add_argument("--no_speech_threshold", type=float, default=0.6,
help="model parameter, tweak to increase accuracy")
parser.add_argument("--condition_on_previous_text", type=str2bool, default=True,
help="model parameter, tweak to increase accuracy")
parser.add_argument("--task", type=str, default="transcribe",
choices=["transcribe", "translate"],
help="whether to perform X->X speech recognition ('transcribe') \
or X->English translation ('translate')")
parser.add_argument("--language", type=str, default="auto",
choices=LANGUAGE_CODES,
help="What is the origin language of the video? \
If unset, it is detected automatically.")
args = parser.parse_args().__dict__
process(args)
if __name__ == '__main__':
main()

25
auto_subtitle/utils/sonarr.py
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@ -1,25 +0,0 @@
import requests
import json
import configparser
config = configparser.RawConfigParser()
config.read('config.cfg')
token = config._sections['sonarr']['token']
base_url = config._sections['sonarr']['url']
def update_show_in_soarr(show_id):
url = f"{base_url}/api/v3/command"
payload = json.dumps({
"name": "RefreshSeries",
"seriesId": show_id
})
headers = {
'Content-Type': 'application/json',
'X-Api-Key': token,
}
response = requests.request("POST", url, headers=headers, data=payload)
if response.status_code != 404:
print("Updated show in Sonarr")

0
auto_subtitle/__init__.py → bazarr-ai-sub-generator/__init__.py
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99
bazarr-ai-sub-generator/cli.py Normal file
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@ -0,0 +1,99 @@
import argparse
from faster_whisper import available_models
from utils.constants import LANGUAGE_CODES
from main import process
from utils.convert import str2bool, str2timeinterval
def main():
"""
Main entry point for the script.
Parses command line arguments, processes the inputs using the specified options,
and performs transcription or translation based on the specified task.
"""
parser = argparse.ArgumentParser(
formatter_class=argparse.ArgumentDefaultsHelpFormatter
)
parser.add_argument(
"--audio_channel", default="0", type=int, help="audio channel index to use"
)
parser.add_argument(
"--sample_interval",
type=str2timeinterval,
default=None,
help="generate subtitles for a specific \
fragment of the video (e.g. 01:02:05-01:03:45)",
)
parser.add_argument(
"--model",
default="small",
choices=available_models(),
help="name of the Whisper model to use",
)
parser.add_argument(
"--device",
type=str,
default="auto",
choices=["cpu", "cuda", "auto"],
help='Device to use for computation ("cpu", "cuda", "auto")',
)
parser.add_argument(
"--compute_type",
type=str,
default="default",
choices=[
"int8",
"int8_float32",
"int8_float16",
"int8_bfloat16",
"int16",
"float16",
"bfloat16",
"float32",
],
help="Type to use for computation. \
See https://opennmt.net/CTranslate2/quantization.html.",
)
parser.add_argument(
"--beam_size",
type=int,
default=5,
help="model parameter, tweak to increase accuracy",
)
parser.add_argument(
"--no_speech_threshold",
type=float,
default=0.6,
help="model parameter, tweak to increase accuracy",
)
parser.add_argument(
"--condition_on_previous_text",
type=str2bool,
default=True,
help="model parameter, tweak to increase accuracy",
)
parser.add_argument(
"--task",
type=str,
default="transcribe",
choices=["transcribe", "translate"],
help="whether to perform X->X speech recognition ('transcribe') \
or X->English translation ('translate')",
)
parser.add_argument(
"--language",
type=str,
default="auto",
choices=LANGUAGE_CODES,
help="What is the origin language of the video? \
If unset, it is detected automatically.",
)
args = parser.parse_args().__dict__
process(args)
if __name__ == "__main__":
main()

28
auto_subtitle/main.py → bazarr-ai-sub-generator/main.py
View File

@ -5,7 +5,7 @@ import time
from utils.files import filename, write_srt
from utils.ffmpeg import get_audio, add_subtitles_to_mp4
from utils.bazarr import get_wanted_episodes, get_episode_details, sync_series
from utils.sonarr import update_show_in_soarr
from utils.sonarr import update_show_in_sonarr
from utils.whisper import WhisperAI
@ -13,11 +13,12 @@ def process(args: dict):
model_name: str = args.pop("model")
language: str = args.pop("language")
sample_interval: str = args.pop("sample_interval")
audio_channel: str = args.pop('audio_channel')
audio_channel: str = args.pop("audio_channel")
if model_name.endswith(".en"):
warnings.warn(
f"{model_name} is an English-only model, forcing English detection.")
f"{model_name} is an English-only model, forcing English detection."
)
args["language"] = "en"
# if translate task used and language argument is set, then use it
elif language != "auto":
@ -29,29 +30,30 @@ def process(args: dict):
model_args["compute_type"] = args.pop("compute_type")
list_of_episodes_needing_subtitles = get_wanted_episodes()
print(f"Found {list_of_episodes_needing_subtitles['total']} episodes needing subtitles.")
for episode in list_of_episodes_needing_subtitles['data']:
print(
f"Found {list_of_episodes_needing_subtitles['total']} episodes needing subtitles."
)
for episode in list_of_episodes_needing_subtitles["data"]:
print(f"Processing {episode['seriesTitle']} - {episode['episode_number']}")
episode_data = get_episode_details(episode['sonarrEpisodeId'])
audios = get_audio([episode_data['path']], audio_channel, sample_interval)
episode_data = get_episode_details(episode["sonarrEpisodeId"])
audios = get_audio([episode_data["path"]], audio_channel, sample_interval)
subtitles = get_subtitles(audios, tempfile.gettempdir(), model_args, args)
add_subtitles_to_mp4(subtitles)
update_show_in_soarr(episode['sonarrSeriesId'])
update_show_in_sonarr(episode["sonarrSeriesId"])
time.sleep(5)
sync_series()
def get_subtitles(audio_paths: list, output_dir: str,
model_args: dict, transcribe_args: dict):
def get_subtitles(
audio_paths: list, output_dir: str, model_args: dict, transcribe_args: dict
):
model = WhisperAI(model_args, transcribe_args)
subtitles_path = {}
for path, audio_path in audio_paths.items():
print(
f"Generating subtitles for {filename(path)}... This might take a while."
)
print(f"Generating subtitles for {filename(path)}... This might take a while.")
srt_path = os.path.join(output_dir, f"{filename(path)}.srt")
segments = model.transcribe(audio_path)

0
auto_subtitle/utils/__init__.py → bazarr-ai-sub-generator/utils/__init__.py
View File

35
auto_subtitle/utils/bazarr.py → bazarr-ai-sub-generator/utils/bazarr.py
View File

@ -1,19 +1,18 @@
import requests
import configparser
config = configparser.RawConfigParser()
config.read('config.cfg')
token = config._sections['bazarr']['token']
base_url = config._sections['bazarr']['url']
config = configparser.RawConfigParser()
config.read("config.cfg")
token = config._sections["bazarr"]["token"]
base_url = config._sections["bazarr"]["url"]
def get_wanted_episodes():
url = f"{base_url}/api/episodes/wanted"
payload={}
headers = {
'accept': 'application/json',
'X-API-KEY': token
}
payload = {}
headers = {"accept": "application/json", "X-API-KEY": token}
response = requests.request("GET", url, headers=headers, data=payload)
@ -23,25 +22,19 @@ def get_wanted_episodes():
def get_episode_details(episode_id: str):
url = f"{base_url}/api/episodes?episodeid%5B%5D={episode_id}"
payload={}
headers = {
'accept': 'application/json',
'X-API-KEY': token
}
payload = {}
headers = {"accept": "application/json", "X-API-KEY": token}
response = requests.request("GET", url, headers=headers, data=payload)
return response.json()['data'][0]
return response.json()["data"][0]
def sync_series():
url = f"{base_url}/api/system/tasks?taskid=update_series"
payload={}
headers = {
'accept': 'application/json',
'X-API-KEY': token
}
payload = {}
headers = {"accept": "application/json", "X-API-KEY": token}
response = requests.request("POST", url, headers=headers, data=payload)
if response.status_code == 204:
print('Updated Bazarr')
print("Updated Bazarr")

0
auto_subtitle/utils/constants.py → bazarr-ai-sub-generator/utils/constants.py
View File

36
auto_subtitle/utils/convert.py → bazarr-ai-sub-generator/utils/convert.py
View File

@ -8,37 +8,42 @@ def str2bool(string: str):
if string in str2val:
return str2val[string]
raise ValueError(
f"Expected one of {set(str2val.keys())}, got {string}")
raise ValueError(f"Expected one of {set(str2val.keys())}, got {string}")
def str2timeinterval(string: str):
if string is None:
return None
if '-' not in string:
if "-" not in string:
raise ValueError(
f"Expected time interval HH:mm:ss-HH:mm:ss or HH:mm-HH:mm or ss-ss, got {string}")
f"Expected time interval HH:mm:ss-HH:mm:ss or HH:mm-HH:mm or ss-ss, got {string}"
)
intervals = string.split('-')
intervals = string.split("-")
if len(intervals) != 2:
raise ValueError(
f"Expected time interval HH:mm:ss-HH:mm:ss or HH:mm-HH:mm or ss-ss, got {string}")
f"Expected time interval HH:mm:ss-HH:mm:ss or HH:mm-HH:mm or ss-ss, got {string}"
)
start = try_parse_timestamp(intervals[0])
end = try_parse_timestamp(intervals[1])
if start >= end:
raise ValueError(
f"Expected time interval end to be higher than start, got {start} >= {end}")
f"Expected time interval end to be higher than start, got {start} >= {end}"
)
return [start, end]
def time_to_timestamp(string: str):
split_time = string.split(':')
if len(split_time) == 0 or len(split_time) > 3 or not all(x.isdigit() for x in split_time):
raise ValueError(
f"Expected HH:mm:ss or HH:mm or ss, got {string}")
split_time = string.split(":")
if (
len(split_time) == 0
or len(split_time) > 3
or not all(x.isdigit() for x in split_time)
):
raise ValueError(f"Expected HH:mm:ss or HH:mm or ss, got {string}")
if len(split_time) == 1:
return int(split_time[0])
@ -50,22 +55,21 @@ def time_to_timestamp(string: str):
def try_parse_timestamp(string: str):
timestamp = parse_timestamp(string, '%H:%M:%S')
timestamp = parse_timestamp(string, "%H:%M:%S")
if timestamp is not None:
return timestamp
timestamp = parse_timestamp(string, '%H:%M')
timestamp = parse_timestamp(string, "%H:%M")
if timestamp is not None:
return timestamp
return parse_timestamp(string, '%S')
return parse_timestamp(string, "%S")
def parse_timestamp(string: str, pattern: str):
try:
date = datetime.strptime(string, pattern)
delta = timedelta(
hours=date.hour, minutes=date.minute, seconds=date.second)
delta = timedelta(hours=date.hour, minutes=date.minute, seconds=date.second)
return int(delta.total_seconds())
except: # pylint: disable=bare-except
return None

34
auto_subtitle/utils/ffmpeg.py → bazarr-ai-sub-generator/utils/ffmpeg.py
View File

@ -15,20 +15,18 @@ def get_audio(paths: list, audio_channel_index: int, sample_interval: list):
ffmpeg_input_args = {}
if sample_interval is not None:
ffmpeg_input_args['ss'] = str(sample_interval[0])
ffmpeg_input_args["ss"] = str(sample_interval[0])
ffmpeg_output_args = {}
ffmpeg_output_args['acodec'] = "pcm_s16le"
ffmpeg_output_args['ac'] = "1"
ffmpeg_output_args['ar'] = "16k"
ffmpeg_output_args['map'] = "0:a:" + str(audio_channel_index)
ffmpeg_output_args["acodec"] = "pcm_s16le"
ffmpeg_output_args["ac"] = "1"
ffmpeg_output_args["ar"] = "16k"
ffmpeg_output_args["map"] = "0:a:" + str(audio_channel_index)
if sample_interval is not None:
ffmpeg_output_args['t'] = str(
sample_interval[1] - sample_interval[0])
ffmpeg_output_args["t"] = str(sample_interval[1] - sample_interval[0])
ffmpeg.input(path, **ffmpeg_input_args).output(
output_path,
**ffmpeg_output_args
output_path, **ffmpeg_output_args
).run(quiet=True, overwrite_output=True)
audio_paths[path] = output_path
@ -37,19 +35,25 @@ def get_audio(paths: list, audio_channel_index: int, sample_interval: list):
def add_subtitles_to_mp4(subtitles: dict):
input_file = list(subtitles.keys())[0]
subtitle_file = subtitles[input_file]
output_file = input_file
os.rename(input_file, input_file+'_edit')
os.rename(input_file, input_file + "_edit")
input_stream = ffmpeg.input(input_file+'_edit')
input_stream = ffmpeg.input(input_file + "_edit")
subtitle_stream = ffmpeg.input(subtitle_file)
# Combine input video and subtitle
output = ffmpeg.output(input_stream, subtitle_stream, output_file.replace('.mkv','.mp4'), c='copy', **{'c:s': 'mov_text'}, **{'metadata:s:s:0': 'language=eng'})
output = ffmpeg.output(
input_stream,
subtitle_stream,
output_file.replace(".mkv", ".mp4"),
c="copy",
**{"c:s": "mov_text"},
**{"metadata:s:s:0": "language=eng"},
)
ffmpeg.run(output, quiet=True, overwrite_output=True)
os.remove(input_file+'_edit')
os.remove(input_file + "_edit")
# remove tempfiles
os.remove(subtitle_file)
os.remove(subtitle_file.replace(".srt",".wav"))
os.remove(subtitle_file.replace(".srt", ".wav"))

2
auto_subtitle/utils/files.py → bazarr-ai-sub-generator/utils/files.py
View File

@ -2,6 +2,7 @@ import os
from typing import Iterator, TextIO
from .convert import format_timestamp
def write_srt(transcript: Iterator[dict], file: TextIO):
for i, segment in enumerate(transcript, start=1):
print(
@ -13,5 +14,6 @@ def write_srt(transcript: Iterator[dict], file: TextIO):
flush=True,
)
def filename(path: str):
return os.path.splitext(os.path.basename(path))[0]

24
bazarr-ai-sub-generator/utils/sonarr.py Normal file
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@ -0,0 +1,24 @@
import requests
import json
import configparser
config = configparser.RawConfigParser()
config.read("config.cfg")
token = config._sections["sonarr"]["token"]
base_url = config._sections["sonarr"]["url"]
def update_show_in_sonarr(show_id):
url = f"{base_url}/api/v3/command"
payload = json.dumps({"name": "RefreshSeries", "seriesId": show_id})
headers = {
"Content-Type": "application/json",
"X-Api-Key": token,
}
response = requests.request("POST", url, headers=headers, data=payload)
if response.status_code != 404:
print("Updated show in Sonarr")

1
auto_subtitle/utils/whisper.py → bazarr-ai-sub-generator/utils/whisper.py
View File

@ -2,6 +2,7 @@ import warnings
import faster_whisper
from tqdm import tqdm
# pylint: disable=R0903
class WhisperAI:
"""