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made cli work with new interface

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This commit is contained in:
Jaikinator
2024-01-25 16:08:53 +01:00
parent c65dc51541
commit ef7bd6e15c
3 changed files with 100 additions and 49 deletions
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scraibe/cli.py
+57 -49
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@@ -5,10 +5,11 @@ The function includes arguments for specifying the audio files, model paths,
output formats, and other options necessary for transcription.
"""
import os
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter
from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter, Action
import json
from .autotranscript import Scraibe
from .misc import ParseKwargs
from .app.app import gradio_Interface
from whisper.tokenizer import LANGUAGES , TO_LANGUAGE_CODE
@@ -41,13 +42,15 @@ def cli():
help="List of audio files to transcribe.")
group.add_argument('--start-server', action='store_true',
help='Start the Gradio app.')
help='Start the Gradio app.' \
'If set, all other arguments are ignored' \
'besides --server-config or --server-kwargs.')
parser.add_argument("--port", type=int, default= None,
help="Port to run the Gradio app on. Defaults to 7860.")
parser.add_argument("--server-config", type=str, default= None,
help="Path to the configy.yml file.")
parser.add_argument("--server-name", type=str, default= None,
help="Name of the Gradio app. If empty 127.0.0.1 or 0.0.0.0 will be used.")
parser.add_argument('--server-kwargs', nargs='*', action=ParseKwargs, default={},
help='Keyword arguments for the Gradio app.')
parser.add_argument("--whisper-model-name", default="medium",
help="Name of the Whisper model to use.")
@@ -66,7 +69,8 @@ def cli():
help="Device to use for PyTorch inference.")
parser.add_argument("--num-threads", type=int, default=0,
help="Number of threads used by torch for CPU inference; overrides MKL_NUM_THREADS/OMP_NUM_THREADS.")
help="Number of threads used by torch for CPU inference; '\
'overrides MKL_NUM_THREADS/OMP_NUM_THREADS.")
parser.add_argument("--output-directory", "-o", type=str, default=".",
help="Directory to save the transcription outputs.")
@@ -113,55 +117,59 @@ def cli():
if arg_dict["whisper_model_directory"]:
class_kwargs["download_root"] = arg_dict.pop("whisper_model_directory")
model = Scraibe(**class_kwargs)
if arg_dict["audio_files"]:
audio_files = arg_dict.pop("audio_files")
if not start_server:
if task == "autotranscribe" or task == "autotranscribe+translate":
for audio in audio_files:
if task == "autotranscribe+translate":
task = "translate"
else:
task = "transcribe"
out = model.autotranscribe(audio,task = task, language=arg_dict.pop("language"), verbose = arg_dict.pop("verbose_output"))
basename = audio.split("/")[-1].split(".")[0]
print(f'Saving {basename}.{out_format} to {out_folder}')
out.save(os.path.join(out_folder, f"{basename}.{out_format}"))
elif task == "diarization":
for audio in audio_files:
if arg_dict.pop("verbose_output"):
print(f"Verbose not implemented for diarization.")
out = model.diarization(audio)
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)
model = Scraibe(**class_kwargs)
elif task == "transcribe" or task == "translate":
if arg_dict["audio_files"]:
audio_files = arg_dict.pop("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)
if task == "autotranscribe" or task == "autotranscribe+translate":
for audio in audio_files:
if task == "autotranscribe+translate":
task = "translate"
else:
task = "transcribe"
out = model.autotranscribe(audio,task = task, language=arg_dict.pop("language"), verbose = arg_dict.pop("verbose_output"))
basename = audio.split("/")[-1].split(".")[0]
print(f'Saving {basename}.{out_format} to {out_folder}')
out.save(os.path.join(out_folder, f"{basename}.{out_format}"))
elif task == "diarization":
for audio in audio_files:
if arg_dict.pop("verbose_output"):
print(f"Verbose not implemented for diarization.")
out = model.diarization(audio)
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)
elif task == "transcribe" or task == "translate":
for audio in audio_files:
if start_server: # unfinished code
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
import subprocess
import sys
gradio_Interface(model).queue().launch(server_port=args.port, server_name=args.server_name)
execute_path = os.path.join(os.path.dirname(__file__), "app/app_starter.py")
subprocess.run([sys.executable, execute_path])
if __name__ == "__main__":
cli()