Merge pull request #8 from karl0ss/reworked

Reworked

bazarr-ai-sub-generator/cli.py

@@ -2,8 +2,6 @@ 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():
     """
@@ -12,15 +10,20 @@ def main():
     Parses command line arguments, processes the inputs using the specified options,
     and performs transcription or translation based on the specified task.
     """
+    # Create an ArgumentParser object with a specific formatter for default values
     parser = argparse.ArgumentParser(
         formatter_class=argparse.ArgumentDefaultsHelpFormatter
     )
+    
+    # Add argument for selecting the Whisper model
     parser.add_argument(
         "--model",
         default="small",
         choices=available_models(),
         help="name of the Whisper model to use",
     )
+    
+    # Add argument for specifying the device to use (CPU, CUDA, or auto-detect)
     parser.add_argument(
         "--device",
         type=str,
@@ -28,35 +31,24 @@ def main():
         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.",
-    # )
+    
+    # Add argument for processing a single file
     parser.add_argument(
         "--file",
         type=str,
         default=None,
         help="Process a single file"
     )
+    
+    # Add argument for processing all videos in a folder
     parser.add_argument(
         "--folder",
         type=str,
         default=None,
         help="Process all videos in folder"
     )
+    
+    # Add argument for specifying the task: transcribe or translate
     parser.add_argument(
         "--show",
         type=str,
@@ -64,6 +56,8 @@ def main():
         help="whether to perform X->X speech recognition ('transcribe') \
                               or X->English translation ('translate')",
     )
+    
+    # Add argument for setting the origin language of the video, with auto-detection as default
     parser.add_argument(
         "--language",
         type=str,
@@ -72,16 +66,20 @@ def main():
         help="What is the origin language of the video? \
                               If unset, it is detected automatically.",
     )
+    
+    # Add argument for selecting the backend: whisper or faster_whisper
     parser.add_argument(
         "--backend",
         type=str,
         default="whisper",
         choices=["whisper", "faster_whisper"],
     )
+    
+    # Parse the command line arguments into a dictionary
     args = parser.parse_args().__dict__
-
+    
+    # Call the process function with the parsed arguments
     process(args)
 
-
 if __name__ == "__main__":
     main()

bazarr-ai-sub-generator/main.py

@@ -2,8 +2,9 @@ import os
 import warnings
 import tempfile
 import time
+from typing import List, Dict, Any
 from utils.files import filename, write_srt
-from utils.ffmpeg import get_audio, add_subtitles_to_mp4
+from utils.ffmpeg import get_audio, add_subtitles_to_mp4, check_for_subtitles
 from utils.bazarr import get_wanted_episodes, get_episode_details, sync_series
 from utils.sonarr import update_show_in_sonarr
 from utils.faster_whisper import WhisperAI as fasterWhisperAI
@@ -11,57 +12,101 @@ from utils.whisper import WhisperAI
 from utils.decorator import measure_time
 
 
-
-def folder_flow(folder, model_args, args, backend):
-        print(f"Processing {folder}")
-        files = os.listdir(folder)
-        for file in files:
-            print(f"processing {file}")
-            path = folder+file
-            try:
-                audios = get_audio([path], 0, None)
-                subtitles = get_subtitles(audios, tempfile.gettempdir(), model_args, args, backend)
-
-                add_subtitles_to_mp4(subtitles)
-                time.sleep(5)
-            except Exception as ex:
-                print(f"skipping file due to - {ex}")
-
-def file_flow(show, model_args, args, backend):
-        print(f"Processing {show}")
-        try:
-            audios = get_audio([show], 0, None)
-            subtitles = get_subtitles(audios, tempfile.gettempdir(), model_args, args, backend)
-
-            add_subtitles_to_mp4(subtitles)
-            time.sleep(5)
-        except Exception as ex:
-            print(f"skipping file due to - {ex}")
-
-def bazzar_flow(show, model_args, args, backend):
+def process_audio_and_subtitles(file_path: str, model_args: Dict[str, Any], args: Dict[str, Any], backend: str) -> None:
+    """Processes audio extraction and subtitle generation for a given file.
+
+    Args:
+        file_path (str): Path to the video file.
+        model_args (Dict[str, Any]): Model arguments for subtitle generation.
+        args (Dict[str, Any]): Additional arguments for subtitle generation.
+        backend (str): Backend to use ('whisper' or 'faster_whisper').
+
+    Returns:
+        None
+    """
+    try:
+        audios = get_audio([file_path], 0, None)
+        subtitles = get_subtitles(audios, tempfile.gettempdir(), model_args, args, backend)
+        add_subtitles_to_mp4(subtitles)
+        time.sleep(5)
+    except Exception as ex:
+        print(f"Skipping file {file_path} due to - {ex}")
+
+
+def folder_flow(folder: str, model_args: Dict[str, Any], args: Dict[str, Any], backend: str) -> None:
+    """Processes all files within a specified folder.
+
+    Args:
+        folder (str): Path to the folder containing video files.
+        model_args (Dict[str, Any]): Model arguments for subtitle generation.
+        args (Dict[str, Any]): Additional arguments for subtitle generation.
+        backend (str): Backend to use ('whisper' or 'faster_whisper').
+
+    Returns:
+        None
+    """
+    print(f"Processing folder {folder}")
+    files = os.listdir(folder)
+    for file in files:
+        path = os.path.join(folder, file)
+        print(f"Processing file {path}")
+        if not check_for_subtitles(path):
+            process_audio_and_subtitles(path, model_args, args, backend)
+
+
+def file_flow(file_path: str, model_args: Dict[str, Any], args: Dict[str, Any], backend: str) -> None:
+    """Processes a single specified file.
+
+    Args:
+        file_path (str): Path to the video file.
+        model_args (Dict[str, Any]): Model arguments for subtitle generation.
+        args (Dict[str, Any]): Additional arguments for subtitle generation.
+        backend (str): Backend to use ('whisper' or 'faster_whisper').
+
+    Returns:
+        None
+    """
+    print(f"Processing file {file_path}")
+    if not check_for_subtitles(file_path):
+        process_audio_and_subtitles(file_path, model_args, args, backend)
+
+
+def bazzar_flow(show: str, model_args: Dict[str, Any], args: Dict[str, Any], backend: str) -> None:
+    """Processes episodes needing subtitles from Bazarr API.
+
+    Args:
+        show (str): The show name.
+        model_args (Dict[str, Any]): Model arguments for subtitle generation.
+        args (Dict[str, Any]): Additional arguments for subtitle generation.
+        backend (str): Backend to use ('whisper' or 'faster_whisper').
+
+    Returns:
+        None
+    """
     list_of_episodes_needing_subtitles = get_wanted_episodes(show)
-    print(
-        f"Found {list_of_episodes_needing_subtitles['total']} episodes needing subtitles."
-    )
+    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"])
-        try:
-            audios = get_audio([episode_data["path"]], 0, None)
-            subtitles = get_subtitles(audios, tempfile.gettempdir(), model_args, args, backend)
-
-            add_subtitles_to_mp4(subtitles)
-            update_show_in_sonarr(episode["sonarrSeriesId"])
-            time.sleep(5)
-            sync_series()
-        except Exception as ex:
-            print(f"skipping file due to - {ex}")
+        process_audio_and_subtitles(episode_data["path"], model_args, args, backend)
+        update_show_in_sonarr(episode["sonarrSeriesId"])
+        sync_series()
 
 
 @measure_time
-def get_subtitles(
-    audio_paths: list, output_dir: str, model_args: dict, transcribe_args: dict, backend: str
-):
+def get_subtitles(audio_paths: List[str], output_dir: str, model_args: Dict[str, Any], transcribe_args: Dict[str, Any], backend: str) -> Dict[str, str]:
+    """Generates subtitles for given audio files using the specified model.
+
+    Args:
+        audio_paths (List[str]): List of paths to the audio files.
+        output_dir (str): Directory to save the generated subtitle files.
+        model_args (Dict[str, Any]): Model arguments for subtitle generation.
+        transcribe_args (Dict[str, Any]): Transcription arguments for subtitle generation.
+        backend (str): Backend to use ('whisper' or 'faster_whisper').
+
+    Returns:
+        Dict[str, str]: A dictionary mapping audio file paths to generated subtitle file paths.
+    """
     if backend == 'whisper':
         model = WhisperAI(model_args, transcribe_args)
     else:
@@ -82,8 +127,15 @@ def get_subtitles(
     return subtitles_path
 
 
-def process(args: dict):
+def process(args: Dict[str, Any]) -> None:
+    """Main entry point to determine which processing flow to use.
+
+    Args:
+        args (Dict[str, Any]): Dictionary of arguments including model, language, show, file, folder, and backend.
 
+    Returns:
+        None
+    """
     model_name: str = args.pop("model")
     language: str = args.pop("language")
     show: str = args.pop("show")
@@ -92,16 +144,12 @@ def process(args: dict):
     backend: str = args.pop("backend")
 
     if model_name.endswith(".en"):
-        warnings.warn(
-            f"{model_name} is an English-only model, forcing English detection."
-        )
+        warnings.warn(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":
         args["language"] = language
 
-    model_args = {}
-    model_args["device"] = args.pop("device")
+    model_args = {"device": args.pop("device")}
 
     if file:
         file_flow(file, model_args, args, backend)

bazarr-ai-sub-generator/utils/ffmpeg.py

@@ -4,6 +4,18 @@ import ffmpeg
 from .files import filename
 
 
+def check_for_subtitles(video_path:str):
+    # Probe the video file to get information about its streams
+    probe = ffmpeg.probe(video_path)
+    
+    # Check if there are any subtitle streams
+    for stream in probe['streams']:
+        if stream['codec_type'] == 'subtitle':
+            print("File has subtitles")
+            return True
+    
+    return False
+
 def get_audio(paths: list, audio_channel_index: int, sample_interval: list):
     temp_dir = tempfile.gettempdir()