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| import os | |
| import argparse | |
| import gradio as gr | |
| from gradio_i18n import Translate, gettext as _ | |
| import yaml | |
| from modules.utils.paths import (FASTER_WHISPER_MODELS_DIR, DIARIZATION_MODELS_DIR, OUTPUT_DIR, WHISPER_MODELS_DIR, | |
| INSANELY_FAST_WHISPER_MODELS_DIR, NLLB_MODELS_DIR, DEFAULT_PARAMETERS_CONFIG_PATH, | |
| UVR_MODELS_DIR, I18N_YAML_PATH) | |
| from modules.utils.files_manager import load_yaml | |
| from modules.whisper.whisper_factory import WhisperFactory | |
| from modules.translation.nllb_inference import NLLBInference | |
| from modules.ui.htmls import * | |
| from modules.utils.cli_manager import str2bool | |
| from modules.utils.youtube_manager import get_ytmetas | |
| from modules.translation.deepl_api import DeepLAPI | |
| from modules.whisper.data_classes import * | |
| class App: | |
| def __init__(self, args): | |
| self.args = args | |
| self.app = gr.Blocks(css=CSS, theme=self.args.theme, delete_cache=(60, 3600)) | |
| self.i18n = Translate(I18N_YAML_PATH) | |
| self.whisper_inf = WhisperFactory.create_whisper_inference( | |
| whisper_type=self.args.whisper_type, | |
| whisper_model_dir=self.args.whisper_model_dir, | |
| faster_whisper_model_dir=self.args.faster_whisper_model_dir, | |
| insanely_fast_whisper_model_dir=self.args.insanely_fast_whisper_model_dir, | |
| uvr_model_dir=self.args.uvr_model_dir, | |
| output_dir=self.args.output_dir, | |
| ) | |
| self.nllb_inf = NLLBInference( | |
| model_dir=self.args.nllb_model_dir, | |
| output_dir=os.path.join(self.args.output_dir, "translations") | |
| ) | |
| self.deepl_api = DeepLAPI( | |
| output_dir=os.path.join(self.args.output_dir, "translations") | |
| ) | |
| self.default_params = load_yaml(DEFAULT_PARAMETERS_CONFIG_PATH) | |
| print(f"Use \"{self.args.whisper_type}\" implementation\n" | |
| f"Device \"{self.whisper_inf.device}\" is detected") | |
| def create_pipeline_inputs(self): | |
| whisper_params = self.default_params["whisper"] | |
| vad_params = self.default_params["vad"] | |
| diarization_params = self.default_params["diarization"] | |
| uvr_params = self.default_params["bgm_separation"] | |
| with gr.Row(): | |
| dd_model = gr.Dropdown(choices=self.whisper_inf.available_models, value=whisper_params["model_size"], | |
| label=_("Model")) | |
| dd_lang = gr.Dropdown(choices=self.whisper_inf.available_langs + [AUTOMATIC_DETECTION], | |
| value=AUTOMATIC_DETECTION if whisper_params["lang"] == AUTOMATIC_DETECTION.unwrap() | |
| else whisper_params["lang"], label=_("Language")) | |
| dd_file_format = gr.Dropdown(choices=["SRT", "WebVTT", "txt", "LRC"], value=whisper_params["file_format"], label=_("File Format")) | |
| with gr.Row(): | |
| cb_translate = gr.Checkbox(value=whisper_params["is_translate"], label=_("Translate to English?"), | |
| interactive=True) | |
| with gr.Row(): | |
| cb_timestamp = gr.Checkbox(value=whisper_params["add_timestamp"], | |
| label=_("Add a timestamp to the end of the filename"), | |
| interactive=True) | |
| with gr.Accordion(_("Advanced Parameters"), open=False): | |
| whisper_inputs = WhisperParams.to_gradio_inputs(defaults=whisper_params, only_advanced=True, | |
| whisper_type=self.args.whisper_type, | |
| available_compute_types=self.whisper_inf.available_compute_types, | |
| compute_type=self.whisper_inf.current_compute_type) | |
| with gr.Accordion(_("Background Music Remover Filter"), open=False): | |
| uvr_inputs = BGMSeparationParams.to_gradio_input(defaults=uvr_params, | |
| available_models=self.whisper_inf.music_separator.available_models, | |
| available_devices=self.whisper_inf.music_separator.available_devices, | |
| device=self.whisper_inf.music_separator.device) | |
| with gr.Accordion(_("Voice Detection Filter"), open=False): | |
| vad_inputs = VadParams.to_gradio_inputs(defaults=vad_params) | |
| with gr.Accordion(_("Diarization"), open=False): | |
| diarization_inputs = DiarizationParams.to_gradio_inputs(defaults=diarization_params, | |
| available_devices=self.whisper_inf.diarizer.available_device, | |
| device=self.whisper_inf.diarizer.device) | |
| dd_model.change(fn=self.on_change_models, inputs=[dd_model], outputs=[cb_translate]) | |
| pipeline_inputs = [dd_model, dd_lang, cb_translate] + whisper_inputs + vad_inputs + diarization_inputs + uvr_inputs | |
| return ( | |
| pipeline_inputs, | |
| dd_file_format, | |
| cb_timestamp | |
| ) | |
| def launch(self): | |
| translation_params = self.default_params["translation"] | |
| deepl_params = translation_params["deepl"] | |
| nllb_params = translation_params["nllb"] | |
| uvr_params = self.default_params["bgm_separation"] | |
| with self.app: | |
| with self.i18n: | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Markdown(MARKDOWN, elem_id="md_project") | |
| with gr.Tabs(): | |
| with gr.TabItem(_("File")): # tab1 | |
| with gr.Column(): | |
| input_file = gr.Files(type="filepath", label=_("Upload File here")) | |
| tb_input_folder = gr.Textbox(label="Input Folder Path (Optional)", | |
| info="Optional: Specify the folder path where the input files are located, if you prefer to use local files instead of uploading them." | |
| " Leave this field empty if you do not wish to use a local path.", | |
| visible=self.args.colab, | |
| value="") | |
| pipeline_params, dd_file_format, cb_timestamp = self.create_pipeline_inputs() | |
| with gr.Row(): | |
| btn_run = gr.Button(_("GENERATE SUBTITLE FILE"), variant="primary") | |
| with gr.Row(): | |
| tb_indicator = gr.Textbox(label=_("Output"), scale=5) | |
| files_subtitles = gr.Files(label=_("Downloadable output file"), scale=3, interactive=False) | |
| btn_openfolder = gr.Button('📂', scale=1) | |
| params = [input_file, tb_input_folder, dd_file_format, cb_timestamp] | |
| btn_run.click(fn=self.whisper_inf.transcribe_file, | |
| inputs=params + pipeline_params, | |
| outputs=[tb_indicator, files_subtitles]) | |
| btn_openfolder.click(fn=lambda: self.open_folder("outputs"), inputs=None, outputs=None) | |
| with gr.TabItem(_("Youtube")): # tab2 | |
| with gr.Row(): | |
| tb_youtubelink = gr.Textbox(label=_("Youtube Link")) | |
| with gr.Row(equal_height=True): | |
| with gr.Column(): | |
| img_thumbnail = gr.Image(label=_("Youtube Thumbnail")) | |
| with gr.Column(): | |
| tb_title = gr.Label(label=_("Youtube Title")) | |
| tb_description = gr.Textbox(label=_("Youtube Description"), max_lines=15) | |
| pipeline_params, dd_file_format, cb_timestamp = self.create_pipeline_inputs() | |
| with gr.Row(): | |
| btn_run = gr.Button(_("GENERATE SUBTITLE FILE"), variant="primary") | |
| with gr.Row(): | |
| tb_indicator = gr.Textbox(label=_("Output"), scale=5) | |
| files_subtitles = gr.Files(label=_("Downloadable output file"), scale=3) | |
| btn_openfolder = gr.Button('📂', scale=1) | |
| params = [tb_youtubelink, dd_file_format, cb_timestamp] | |
| btn_run.click(fn=self.whisper_inf.transcribe_youtube, | |
| inputs=params + pipeline_params, | |
| outputs=[tb_indicator, files_subtitles]) | |
| tb_youtubelink.change(get_ytmetas, inputs=[tb_youtubelink], | |
| outputs=[img_thumbnail, tb_title, tb_description]) | |
| btn_openfolder.click(fn=lambda: self.open_folder("outputs"), inputs=None, outputs=None) | |
| with gr.TabItem(_("Mic")): # tab3 | |
| with gr.Row(): | |
| mic_input = gr.Microphone(label=_("Record with Mic"), type="filepath", interactive=True) | |
| pipeline_params, dd_file_format, cb_timestamp = self.create_pipeline_inputs() | |
| with gr.Row(): | |
| btn_run = gr.Button(_("GENERATE SUBTITLE FILE"), variant="primary") | |
| with gr.Row(): | |
| tb_indicator = gr.Textbox(label=_("Output"), scale=5) | |
| files_subtitles = gr.Files(label=_("Downloadable output file"), scale=3) | |
| btn_openfolder = gr.Button('📂', scale=1) | |
| params = [mic_input, dd_file_format, cb_timestamp] | |
| btn_run.click(fn=self.whisper_inf.transcribe_mic, | |
| inputs=params + pipeline_params, | |
| outputs=[tb_indicator, files_subtitles]) | |
| btn_openfolder.click(fn=lambda: self.open_folder("outputs"), inputs=None, outputs=None) | |
| with gr.TabItem(_("T2T Translation")): # tab 4 | |
| with gr.Row(): | |
| file_subs = gr.Files(type="filepath", label=_("Upload Subtitle Files to translate here")) | |
| with gr.TabItem(_("DeepL API")): # sub tab1 | |
| with gr.Row(): | |
| tb_api_key = gr.Textbox(label=_("Your Auth Key (API KEY)"), | |
| value=deepl_params["api_key"]) | |
| with gr.Row(): | |
| dd_source_lang = gr.Dropdown(label=_("Source Language"), | |
| value=AUTOMATIC_DETECTION if deepl_params["source_lang"] == AUTOMATIC_DETECTION.unwrap() | |
| else deepl_params["source_lang"], | |
| choices=list(self.deepl_api.available_source_langs.keys())) | |
| dd_target_lang = gr.Dropdown(label=_("Target Language"), | |
| value=deepl_params["target_lang"], | |
| choices=list(self.deepl_api.available_target_langs.keys())) | |
| with gr.Row(): | |
| cb_is_pro = gr.Checkbox(label=_("Pro User?"), value=deepl_params["is_pro"]) | |
| with gr.Row(): | |
| cb_timestamp = gr.Checkbox(value=translation_params["add_timestamp"], | |
| label=_("Add a timestamp to the end of the filename"), | |
| interactive=True) | |
| with gr.Row(): | |
| btn_run = gr.Button(_("TRANSLATE SUBTITLE FILE"), variant="primary") | |
| with gr.Row(): | |
| tb_indicator = gr.Textbox(label=_("Output"), scale=5) | |
| files_subtitles = gr.Files(label=_("Downloadable output file"), scale=3) | |
| btn_openfolder = gr.Button('📂', scale=1) | |
| btn_run.click(fn=self.deepl_api.translate_deepl, | |
| inputs=[tb_api_key, file_subs, dd_source_lang, dd_target_lang, | |
| cb_is_pro, cb_timestamp], | |
| outputs=[tb_indicator, files_subtitles]) | |
| btn_openfolder.click( | |
| fn=lambda: self.open_folder(os.path.join(self.args.output_dir, "translations")), | |
| inputs=None, | |
| outputs=None) | |
| with gr.TabItem(_("NLLB")): # sub tab2 | |
| with gr.Row(): | |
| dd_model_size = gr.Dropdown(label=_("Model"), value=nllb_params["model_size"], | |
| choices=self.nllb_inf.available_models) | |
| dd_source_lang = gr.Dropdown(label=_("Source Language"), | |
| value=nllb_params["source_lang"], | |
| choices=self.nllb_inf.available_source_langs) | |
| dd_target_lang = gr.Dropdown(label=_("Target Language"), | |
| value=nllb_params["target_lang"], | |
| choices=self.nllb_inf.available_target_langs) | |
| with gr.Row(): | |
| nb_max_length = gr.Number(label="Max Length Per Line", value=nllb_params["max_length"], | |
| precision=0) | |
| with gr.Row(): | |
| cb_timestamp = gr.Checkbox(value=translation_params["add_timestamp"], | |
| label=_("Add a timestamp to the end of the filename"), | |
| interactive=True) | |
| with gr.Row(): | |
| btn_run = gr.Button(_("TRANSLATE SUBTITLE FILE"), variant="primary") | |
| with gr.Row(): | |
| tb_indicator = gr.Textbox(label=_("Output"), scale=5) | |
| files_subtitles = gr.Files(label=_("Downloadable output file"), scale=3) | |
| btn_openfolder = gr.Button('📂', scale=1) | |
| with gr.Column(): | |
| md_vram_table = gr.HTML(NLLB_VRAM_TABLE, elem_id="md_nllb_vram_table") | |
| btn_run.click(fn=self.nllb_inf.translate_file, | |
| inputs=[file_subs, dd_model_size, dd_source_lang, dd_target_lang, | |
| nb_max_length, cb_timestamp], | |
| outputs=[tb_indicator, files_subtitles]) | |
| btn_openfolder.click( | |
| fn=lambda: self.open_folder(os.path.join(self.args.output_dir, "translations")), | |
| inputs=None, | |
| outputs=None) | |
| with gr.TabItem(_("BGM Separation")): | |
| files_audio = gr.Files(type="filepath", label=_("Upload Audio Files to separate background music")) | |
| dd_uvr_device = gr.Dropdown(label=_("Device"), value=self.whisper_inf.music_separator.device, | |
| choices=self.whisper_inf.music_separator.available_devices) | |
| dd_uvr_model_size = gr.Dropdown(label=_("Model"), value=uvr_params["model_size"], | |
| choices=self.whisper_inf.music_separator.available_models) | |
| nb_uvr_segment_size = gr.Number(label="Segment Size", value=uvr_params["segment_size"], | |
| precision=0) | |
| cb_uvr_save_file = gr.Checkbox(label=_("Save separated files to output"), | |
| value=True, visible=False) | |
| btn_run = gr.Button(_("SEPARATE BACKGROUND MUSIC"), variant="primary") | |
| with gr.Column(): | |
| with gr.Row(): | |
| ad_instrumental = gr.Audio(label=_("Instrumental"), scale=8) | |
| btn_open_instrumental_folder = gr.Button('📂', scale=1) | |
| with gr.Row(): | |
| ad_vocals = gr.Audio(label=_("Vocals"), scale=8) | |
| btn_open_vocals_folder = gr.Button('📂', scale=1) | |
| btn_run.click(fn=self.whisper_inf.music_separator.separate_files, | |
| inputs=[files_audio, dd_uvr_model_size, dd_uvr_device, nb_uvr_segment_size, | |
| cb_uvr_save_file], | |
| outputs=[ad_instrumental, ad_vocals]) | |
| btn_open_instrumental_folder.click(inputs=None, | |
| outputs=None, | |
| fn=lambda: self.open_folder(os.path.join( | |
| self.args.output_dir, "UVR", "instrumental" | |
| ))) | |
| btn_open_vocals_folder.click(inputs=None, | |
| outputs=None, | |
| fn=lambda: self.open_folder(os.path.join( | |
| self.args.output_dir, "UVR", "vocals" | |
| ))) | |
| # Launch the app with optional gradio settings | |
| args = self.args | |
| self.app.queue( | |
| api_open=args.api_open | |
| ).launch( | |
| share=args.share, | |
| server_name=args.server_name, | |
| server_port=args.server_port, | |
| auth=(args.username, args.password) if args.username and args.password else None, | |
| root_path=args.root_path, | |
| inbrowser=args.inbrowser | |
| ) | |
| def open_folder(folder_path: str): | |
| if os.path.exists(folder_path): | |
| os.system(f"start {folder_path}") | |
| else: | |
| os.makedirs(folder_path, exist_ok=True) | |
| print(f"The directory path {folder_path} has newly created.") | |
| def on_change_models(model_size: str): | |
| translatable_model = ["large", "large-v1", "large-v2", "large-v3"] | |
| if model_size not in translatable_model: | |
| return gr.Checkbox(visible=False, value=False, interactive=False) | |
| else: | |
| return gr.Checkbox(visible=True, value=False, label="Translate to English?", interactive=True) | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--whisper_type', type=str, default=WhisperImpl.FASTER_WHISPER.value, | |
| choices=[item.value for item in WhisperImpl], | |
| help='A type of the whisper implementation (Github repo name)') | |
| parser.add_argument('--share', type=str2bool, default=False, nargs='?', const=True, help='Gradio share value') | |
| parser.add_argument('--server_name', type=str, default=None, help='Gradio server host') | |
| parser.add_argument('--server_port', type=int, default=None, help='Gradio server port') | |
| parser.add_argument('--root_path', type=str, default=None, help='Gradio root path') | |
| parser.add_argument('--username', type=str, default=None, help='Gradio authentication username') | |
| parser.add_argument('--password', type=str, default=None, help='Gradio authentication password') | |
| parser.add_argument('--theme', type=str, default=None, help='Gradio Blocks theme') | |
| parser.add_argument('--colab', type=str2bool, default=False, nargs='?', const=True, help='Is colab user or not') | |
| parser.add_argument('--api_open', type=str2bool, default=False, nargs='?', const=True, | |
| help='Enable api or not in Gradio') | |
| parser.add_argument('--inbrowser', type=str2bool, default=True, nargs='?', const=True, | |
| help='Whether to automatically start Gradio app or not') | |
| parser.add_argument('--whisper_model_dir', type=str, default=WHISPER_MODELS_DIR, | |
| help='Directory path of the whisper model') | |
| parser.add_argument('--faster_whisper_model_dir', type=str, default=FASTER_WHISPER_MODELS_DIR, | |
| help='Directory path of the faster-whisper model') | |
| parser.add_argument('--insanely_fast_whisper_model_dir', type=str, | |
| default=INSANELY_FAST_WHISPER_MODELS_DIR, | |
| help='Directory path of the insanely-fast-whisper model') | |
| parser.add_argument('--diarization_model_dir', type=str, default=DIARIZATION_MODELS_DIR, | |
| help='Directory path of the diarization model') | |
| parser.add_argument('--nllb_model_dir', type=str, default=NLLB_MODELS_DIR, | |
| help='Directory path of the Facebook NLLB model') | |
| parser.add_argument('--uvr_model_dir', type=str, default=UVR_MODELS_DIR, | |
| help='Directory path of the UVR model') | |
| parser.add_argument('--output_dir', type=str, default=OUTPUT_DIR, help='Directory path of the outputs') | |
| _args = parser.parse_args() | |
| if __name__ == "__main__": | |
| app = App(args=_args) | |
| app.launch() | |