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Merge pull request #98 from JSchmie/bug_fix_before_v0.2

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Bug fix before v0.2
This commit is contained in:
Jacob Schmieder
2024-05-31 14:40:26 +02:00
committed by GitHub
parent 72f57d5a7f 5ec66effc2
commit 74a37f0732
1 changed files with 45 additions and 85 deletions
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scraibe/cli.py
+45 -85
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@@ -5,17 +5,12 @@ The function includes arguments for specifying the audio files, model paths,
output formats, and other options necessary for transcription. output formats, and other options necessary for transcription.
""" """
import os import os
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
import json import json
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
from .autotranscript import Scraibe
from .misc import ParseKwargs
from whisper.tokenizer import LANGUAGES, TO_LANGUAGE_CODE from whisper.tokenizer import LANGUAGES, TO_LANGUAGE_CODE
from torch.cuda import is_available from torch.cuda import is_available
from torch import set_num_threads from torch import set_num_threads
from .autotranscript import Scraibe
def cli(): def cli():
""" """
@@ -37,22 +32,13 @@ def cli():
parser = ArgumentParser(formatter_class=ArgumentDefaultsHelpFormatter) parser = ArgumentParser(formatter_class=ArgumentDefaultsHelpFormatter)
group = parser.add_mutually_exclusive_group()
parser.add_argument("-f", "--audio-files", nargs="+", type=str, default=None, parser.add_argument("-f", "--audio-files", nargs="+", type=str, default=None,
help="List of audio files to transcribe.") help="List of audio files to transcribe.")
group.add_argument('--start-server', action='store_true', parser.add_argument("--whisper-type", type=str, default="whisper",
help='Start the Gradio app.' choices=["whisper", "whisperx"],
'If set, all other arguments are ignored' help="Type of Whisper model to use ('whisper' or 'whisperx').")
'besides --server-config or --server-kwargs.')
parser.add_argument("--server-config", type=str, default=None,
help="Path to the configy.yml file.")
parser.add_argument('--server-kwargs', nargs='*', action=ParseKwargs, default={},
help='Keyword arguments for the Gradio app.')
parser.add_argument("--whisper-model-name", default="medium", parser.add_argument("--whisper-model-name", default="medium",
help="Name of the Whisper model to use.") help="Name of the Whisper model to use.")
@@ -83,7 +69,7 @@ def cli():
parser.add_argument("--verbose-output", type=str2bool, default=True, parser.add_argument("--verbose-output", type=str2bool, default=True,
help="Enable or disable progress and debug messages.") help="Enable or disable progress and debug messages.")
parser.add_argument("--task", type=str, default='autotranscribe', # unifinished code parser.add_argument("--task", type=str, default='autotranscribe',
choices=["autotranscribe", "diarization", choices=["autotranscribe", "diarization",
"autotranscribe+translate", "translate", 'transcribe'], "autotranscribe+translate", "translate", 'transcribe'],
help="Choose to perform transcription, diarization, or translation. \ help="Choose to perform transcription, diarization, or translation. \
@@ -104,91 +90,65 @@ def cli():
out_format = arg_dict.pop("output_format") out_format = arg_dict.pop("output_format")
# seup server arg:
start_server = arg_dict.pop("start_server")
task = arg_dict.pop("task") task = arg_dict.pop("task")
if args.num_threads > 0: if args.num_threads > 0:
set_num_threads(arg_dict.pop("num_threads")) set_num_threads(arg_dict.pop("num_threads"))
class_kwargs = {'whisper_model': arg_dict.pop("whisper_model_name"), class_kwargs = {'whisper_model': arg_dict.pop("whisper_model_name"),
'whisper_type':arg_dict.pop("whisper_type"),
'dia_model': arg_dict.pop("diarization_directory"), 'dia_model': arg_dict.pop("diarization_directory"),
'use_auth_token': arg_dict.pop("hf_token")} 'use_auth_token': arg_dict.pop("hf_token"),
}
if arg_dict["whisper_model_directory"]: if arg_dict["whisper_model_directory"]:
class_kwargs["download_root"] = arg_dict.pop("whisper_model_directory") class_kwargs["download_root"] = arg_dict.pop("whisper_model_directory")
if not start_server: model = Scraibe(**class_kwargs)
model = Scraibe(**class_kwargs) if arg_dict["audio_files"]:
audio_files = arg_dict.pop("audio_files")
if arg_dict["audio_files"]: if task == "autotranscribe" or task == "autotranscribe+translate":
audio_files = arg_dict.pop("audio_files") for audio in audio_files:
if task == "autotranscribe+translate":
task = "translate"
else:
task = "transcribe"
if task == "autotranscribe" or task == "autotranscribe+translate": out = model.autotranscribe(audio, task=task, language=arg_dict.pop(
for audio in audio_files: "language"), verbose=arg_dict.pop("verbose_output"))
if task == "autotranscribe+translate": basename = audio.split("/")[-1].split(".")[0]
task = "translate" print(f'Saving {basename}.{out_format} to {out_folder}')
else: out.save(os.path.join(
task = "transcribe" out_folder, f"{basename}.{out_format}"))
out = model.autotranscribe(audio, task=task, language=arg_dict.pop( elif task == "diarization":
"language"), verbose=arg_dict.pop("verbose_output")) for audio in audio_files:
basename = audio.split("/")[-1].split(".")[0] if arg_dict.pop("verbose_output"):
print(f'Saving {basename}.{out_format} to {out_folder}') print("Verbose not implemented for diarization.")
out.save(os.path.join(
out_folder, f"{basename}.{out_format}"))
elif task == "diarization": out = model.diarization(audio)
for audio in audio_files: basename = audio.split("/")[-1].split(".")[0]
if arg_dict.pop("verbose_output"): path = os.path.join(out_folder, f"{basename}.{out_format}")
print("Verbose not implemented for diarization.")
out = model.diarization(audio) print(f'Saving {basename}.{out_format} to {out_folder}')
basename = audio.split("/")[-1].split(".")[0]
path = os.path.join(out_folder, f"{basename}.{out_format}")
print(f'Saving {basename}.{out_format} to {out_folder}') with open(path, "w") as f:
json.dump(json.dumps(out, indent=1), f)
with open(path, "w") as f: elif task == "transcribe" or task == "translate":
json.dump(json.dumps(out, indent=1), f)
elif task == "transcribe" or task == "translate": for audio in audio_files:
for audio in audio_files:
out = model.transcribe(audio, task=task,
language=arg_dict.pop("language"),
verbose=arg_dict.pop("verbose_output"))
basename = audio.split("/")[-1].split(".")[0]
path = os.path.join(out_folder, f"{basename}.{out_format}")
with open(path, "w") as f:
f.write(out)
else: # unfinished code
raise NotImplementedError("Currently not Working")
import subprocess
import sys
execute_path = os.path.join(
os.path.dirname(__file__), "app/app_starter.py")
config = arg_dict.pop("server_config")
server_kwargs = arg_dict.pop("server_kwargs")
if not config:
subprocess.run([sys.executable, execute_path,
f"--server-kwargs={server_kwargs}"])
elif not server_kwargs:
subprocess.run([sys.executable, execute_path,
f"--server-config={config}"])
elif not config and not server_kwargs:
subprocess.run([sys.executable, execute_path])
else:
subprocess.run([sys.executable, execute_path,
f"--server-config={config}", f"--server-kwargs={server_kwargs}"])
out = model.transcribe(audio, task=task,
language=arg_dict.pop("language"),
verbose=arg_dict.pop("verbose_output"))
basename = audio.split("/")[-1].split(".")[0]
path = os.path.join(out_folder, f"{basename}.{out_format}")
with open(path, "w") as f:
f.write(out)
if __name__ == "__main__": if __name__ == "__main__":
cli() cli()