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| import whisper | |
| from modules.subtitle_manager import get_srt,get_vtt,safe_filename | |
| from modules.youtube_manager import get_ytdata,get_ytaudio | |
| import gradio as gr | |
| import os | |
| DEFAULT_MODEL_SIZE="tiny" | |
| class WhisperInference(): | |
| def __init__(self): | |
| print("\nInitializing Model..\n") | |
| self.current_model_size = DEFAULT_MODEL_SIZE | |
| self.model = whisper.load_model(name=DEFAULT_MODEL_SIZE,download_root="models") | |
| self.available_models = ["tiny","tiny.en"] | |
| self.available_langs = sorted(list(whisper.tokenizer.LANGUAGES.values())) | |
| def transcribe_file(self,fileobjs | |
| ,model_size,lang,subformat,istranslate, | |
| progress=gr.Progress()): | |
| def progress_callback(progress_value): | |
| progress(progress_value,desc="Transcribing..") | |
| if model_size != self.current_model_size: | |
| progress(0,desc="Initializing Model..") | |
| self.current_model_size = model_size | |
| self.model = whisper.load_model(name=model_size,download_root="models") | |
| if lang == "Automatic Detection" : | |
| lang = None | |
| progress(0,desc="Loading Audio..") | |
| files_info = {} | |
| for fileobj in fileobjs: | |
| print(f"\n\n {fileobj.name} \n\n") | |
| audio = whisper.load_audio(fileobj.name) | |
| translatable_model = ["large","large-v1","large-v2"] | |
| if istranslate and self.current_model_size in translatable_model: | |
| result = self.model.transcribe(audio=audio,language=lang,verbose=False,task="translate",progress_callback=progress_callback) | |
| else : | |
| result = self.model.transcribe(audio=audio,language=lang,verbose=False,progress_callback=progress_callback) | |
| progress(1,desc="Completed!") | |
| file_name, file_ext = os.path.splitext(os.path.basename(fileobj.orig_name)) | |
| file_name = file_name[:-9] | |
| file_name = safe_filename(file_name) | |
| if subformat == "SRT": | |
| subtitle = get_srt(result["segments"]) | |
| elif subformat == "WebVTT": | |
| subtitle = get_vtt(result["segments"]) | |
| files_info[file_name] = subtitle | |
| total_result = '' | |
| for file_name,subtitle in files_info.items(): | |
| total_result+='------------------------------------\n' | |
| total_result+=f'{file_name}\n\n' | |
| total_result+=f'{subtitle}' | |
| return f"\n\n{total_result}" | |
| def transcribe_youtube(self,youtubelink | |
| ,model_size,lang,subformat,istranslate, | |
| progress=gr.Progress()): | |
| def progress_callback(progress_value): | |
| progress(progress_value,desc="Transcribing..") | |
| if model_size != self.current_model_size: | |
| progress(0,desc="Initializing Model..") | |
| self.current_model_size = model_size | |
| self.model = whisper.load_model(name=model_size,download_root="models") | |
| if lang == "Automatic Detection" : | |
| lang = None | |
| progress(0,desc="Loading Audio from Youtube..") | |
| yt = get_ytdata(youtubelink) | |
| audio = whisper.load_audio(get_ytaudio(yt)) | |
| translatable_model = ["large","large-v1","large-v2"] | |
| if istranslate and self.current_model_size in translatable_model: | |
| result = self.model.transcribe(audio=audio,language=lang,verbose=False,task="translate",progress_callback=progress_callback) | |
| else : | |
| result = self.model.transcribe(audio=audio,language=lang,verbose=False,progress_callback=progress_callback) | |
| progress(1,desc="Completed!") | |
| file_name = safe_filename(yt.title) | |
| if subformat == "SRT": | |
| subtitle = get_srt(result["segments"]) | |
| elif subformat == "WebVTT": | |
| subtitle = get_vtt(result["segments"]) | |
| return f"\n\n{subtitle}" | |
| def transcribe_mic(self,micaudio | |
| ,model_size,lang,subformat,istranslate, | |
| progress=gr.Progress()): | |
| def progress_callback(progress_value): | |
| progress(progress_value,desc="Transcribing..") | |
| if model_size != self.current_model_size: | |
| progress(0,desc="Initializing Model..") | |
| self.current_model_size = model_size | |
| self.model = whisper.load_model(name=model_size,download_root="models") | |
| if lang == "Automatic Detection" : | |
| lang = None | |
| progress(0,desc="Loading Audio..") | |
| translatable_model = ["large","large-v1","large-v2"] | |
| if istranslate and self.current_model_size in translatable_model: | |
| result = self.model.transcribe(audio=micaudio,language=lang,verbose=False,task="translate",progress_callback=progress_callback) | |
| else : | |
| result = self.model.transcribe(audio=micaudio,language=lang,verbose=False,progress_callback=progress_callback) | |
| progress(1,desc="Completed!") | |
| if subformat == "SRT": | |
| subtitle = get_srt(result["segments"]) | |
| elif subformat == "WebVTT": | |
| subtitle = get_vtt(result["segments"]) | |
| return f"\n\n{subtitle}" | |