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| from typing import Iterator | |
| from io import StringIO | |
| import os | |
| import pathlib | |
| import tempfile | |
| # External programs | |
| import whisper | |
| import ffmpeg | |
| # UI | |
| import gradio as gr | |
| from src.download import ExceededMaximumDuration, download_url | |
| from src.utils import slugify, write_srt, write_vtt | |
| from src.vad import NonSpeechStrategy, PeriodicTranscriptionConfig, TranscriptionConfig, VadPeriodicTranscription, VadSileroTranscription | |
| # Limitations (set to -1 to disable) | |
| DEFAULT_INPUT_AUDIO_MAX_DURATION = 600 # seconds | |
| # Whether or not to automatically delete all uploaded files, to save disk space | |
| DELETE_UPLOADED_FILES = True | |
| # Gradio seems to truncate files without keeping the extension, so we need to truncate the file prefix ourself | |
| MAX_FILE_PREFIX_LENGTH = 17 | |
| LANGUAGES = [ | |
| "English", "Chinese", "German", "Spanish", "Russian", "Korean", | |
| "French", "Japanese", "Portuguese", "Turkish", "Polish", "Catalan", | |
| "Dutch", "Arabic", "Swedish", "Italian", "Indonesian", "Hindi", | |
| "Finnish", "Vietnamese", "Hebrew", "Ukrainian", "Greek", "Malay", | |
| "Czech", "Romanian", "Danish", "Hungarian", "Tamil", "Norwegian", | |
| "Thai", "Urdu", "Croatian", "Bulgarian", "Lithuanian", "Latin", | |
| "Maori", "Malayalam", "Welsh", "Slovak", "Telugu", "Persian", | |
| "Latvian", "Bengali", "Serbian", "Azerbaijani", "Slovenian", | |
| "Kannada", "Estonian", "Macedonian", "Breton", "Basque", "Icelandic", | |
| "Armenian", "Nepali", "Mongolian", "Bosnian", "Kazakh", "Albanian", | |
| "Swahili", "Galician", "Marathi", "Punjabi", "Sinhala", "Khmer", | |
| "Shona", "Yoruba", "Somali", "Afrikaans", "Occitan", "Georgian", | |
| "Belarusian", "Tajik", "Sindhi", "Gujarati", "Amharic", "Yiddish", | |
| "Lao", "Uzbek", "Faroese", "Haitian Creole", "Pashto", "Turkmen", | |
| "Nynorsk", "Maltese", "Sanskrit", "Luxembourgish", "Myanmar", "Tibetan", | |
| "Tagalog", "Malagasy", "Assamese", "Tatar", "Hawaiian", "Lingala", | |
| "Hausa", "Bashkir", "Javanese", "Sundanese" | |
| ] | |
| class WhisperTranscriber: | |
| def __init__(self, inputAudioMaxDuration: float = DEFAULT_INPUT_AUDIO_MAX_DURATION, deleteUploadedFiles: bool = DELETE_UPLOADED_FILES): | |
| self.model_cache = dict() | |
| self.vad_model = None | |
| self.inputAudioMaxDuration = inputAudioMaxDuration | |
| self.deleteUploadedFiles = deleteUploadedFiles | |
| def transcribe_webui(self, modelName, languageName, urlData, uploadFile, microphoneData, task, vad, vadMergeWindow, vadMaxMergeSize, vadPadding, vadPromptWindow): | |
| try: | |
| source, sourceName = self.__get_source(urlData, uploadFile, microphoneData) | |
| try: | |
| selectedLanguage = languageName.lower() if len(languageName) > 0 else None | |
| selectedModel = modelName if modelName is not None else "base" | |
| model = self.model_cache.get(selectedModel, None) | |
| if not model: | |
| model = whisper.load_model(selectedModel) | |
| self.model_cache[selectedModel] = model | |
| # Execute whisper | |
| result = self.transcribe_file(model, source, selectedLanguage, task, vad, vadMergeWindow, vadMaxMergeSize, vadPadding, vadPromptWindow) | |
| # Write result | |
| downloadDirectory = tempfile.mkdtemp() | |
| filePrefix = slugify(sourceName, allow_unicode=True) | |
| download, text, vtt = self.write_result(result, filePrefix, downloadDirectory) | |
| return download, text, vtt | |
| finally: | |
| # Cleanup source | |
| if self.deleteUploadedFiles: | |
| print("Deleting source file " + source) | |
| os.remove(source) | |
| except ExceededMaximumDuration as e: | |
| return [], ("[ERROR]: Maximum remote video length is " + str(e.maxDuration) + "s, file was " + str(e.videoDuration) + "s"), "[ERROR]" | |
| def transcribe_file(self, model: whisper.Whisper, audio_path: str, language: str, task: str = None, vad: str = None, | |
| vadMergeWindow: float = 5, vadMaxMergeSize: float = 150, vadPadding: float = 1, vadPromptWindow: float = 1, **decodeOptions: dict): | |
| initial_prompt = decodeOptions.pop('initial_prompt', None) | |
| if ('task' in decodeOptions): | |
| task = decodeOptions.pop('task') | |
| # Callable for processing an audio file | |
| whisperCallable = lambda audio, segment_index, prompt, detected_language : model.transcribe(audio, \ | |
| language=language if language else detected_language, task=task, \ | |
| initial_prompt=self._concat_prompt(initial_prompt, prompt) if segment_index == 0 else prompt, \ | |
| **decodeOptions) | |
| # The results | |
| if (vad == 'silero-vad'): | |
| # Silero VAD where non-speech gaps are transcribed | |
| process_gaps = self._create_silero_config(NonSpeechStrategy.CREATE_SEGMENT, vadMergeWindow, vadMaxMergeSize, vadPadding, vadPromptWindow) | |
| result = self.vad_model.transcribe(audio_path, whisperCallable, process_gaps) | |
| elif (vad == 'silero-vad-skip-gaps'): | |
| # Silero VAD where non-speech gaps are simply ignored | |
| skip_gaps = self._create_silero_config(NonSpeechStrategy.SKIP, vadMergeWindow, vadMaxMergeSize, vadPadding, vadPromptWindow) | |
| result = self.vad_model.transcribe(audio_path, whisperCallable, skip_gaps) | |
| elif (vad == 'silero-vad-expand-into-gaps'): | |
| # Use Silero VAD where speech-segments are expanded into non-speech gaps | |
| expand_gaps = self._create_silero_config(NonSpeechStrategy.EXPAND_SEGMENT, vadMergeWindow, vadMaxMergeSize, vadPadding, vadPromptWindow) | |
| result = self.vad_model.transcribe(audio_path, whisperCallable, expand_gaps) | |
| elif (vad == 'periodic-vad'): | |
| # Very simple VAD - mark every 5 minutes as speech. This makes it less likely that Whisper enters an infinite loop, but | |
| # it may create a break in the middle of a sentence, causing some artifacts. | |
| periodic_vad = VadPeriodicTranscription() | |
| result = periodic_vad.transcribe(audio_path, whisperCallable, PeriodicTranscriptionConfig(periodic_duration=vadMaxMergeSize, max_prompt_window=vadPromptWindow)) | |
| else: | |
| # Default VAD | |
| result = whisperCallable(audio_path, 0, None, None) | |
| return result | |
| def _concat_prompt(self, prompt1, prompt2): | |
| if (prompt1 is None): | |
| return prompt2 | |
| elif (prompt2 is None): | |
| return prompt1 | |
| else: | |
| return prompt1 + " " + prompt2 | |
| def _create_silero_config(self, non_speech_strategy: NonSpeechStrategy, vadMergeWindow: float = 5, vadMaxMergeSize: float = 150, vadPadding: float = 1, vadPromptWindow: float = 1): | |
| # Use Silero VAD | |
| if (self.vad_model is None): | |
| self.vad_model = VadSileroTranscription() | |
| config = TranscriptionConfig(non_speech_strategy = non_speech_strategy, | |
| max_silent_period=vadMergeWindow, max_merge_size=vadMaxMergeSize, | |
| segment_padding_left=vadPadding, segment_padding_right=vadPadding, | |
| max_prompt_window=vadPromptWindow) | |
| return config | |
| def write_result(self, result: dict, source_name: str, output_dir: str): | |
| if not os.path.exists(output_dir): | |
| os.makedirs(output_dir) | |
| text = result["text"] | |
| language = result["language"] | |
| languageMaxLineWidth = self.__get_max_line_width(language) | |
| print("Max line width " + str(languageMaxLineWidth)) | |
| vtt = self.__get_subs(result["segments"], "vtt", languageMaxLineWidth) | |
| srt = self.__get_subs(result["segments"], "srt", languageMaxLineWidth) | |
| output_files = [] | |
| output_files.append(self.__create_file(srt, output_dir, source_name + "-subs.srt")); | |
| output_files.append(self.__create_file(vtt, output_dir, source_name + "-subs.vtt")); | |
| output_files.append(self.__create_file(text, output_dir, source_name + "-transcript.txt")); | |
| return output_files, text, vtt | |
| def clear_cache(self): | |
| self.model_cache = dict() | |
| self.vad_model = None | |
| def __get_source(self, urlData, uploadFile, microphoneData): | |
| if urlData: | |
| # Download from YouTube | |
| source = download_url(urlData, self.inputAudioMaxDuration)[0] | |
| else: | |
| # File input | |
| source = uploadFile if uploadFile is not None else microphoneData | |
| if self.inputAudioMaxDuration > 0: | |
| # Calculate audio length | |
| audioDuration = ffmpeg.probe(source)["format"]["duration"] | |
| if float(audioDuration) > self.inputAudioMaxDuration: | |
| raise ExceededMaximumDuration(videoDuration=audioDuration, maxDuration=self.inputAudioMaxDuration, message="Video is too long") | |
| file_path = pathlib.Path(source) | |
| sourceName = file_path.stem[:MAX_FILE_PREFIX_LENGTH] + file_path.suffix | |
| return source, sourceName | |
| def __get_max_line_width(self, language: str) -> int: | |
| if (language and language.lower() in ["japanese", "ja", "chinese", "zh"]): | |
| # Chinese characters and kana are wider, so limit line length to 40 characters | |
| return 40 | |
| else: | |
| # TODO: Add more languages | |
| # 80 latin characters should fit on a 1080p/720p screen | |
| return 80 | |
| def __get_subs(self, segments: Iterator[dict], format: str, maxLineWidth: int) -> str: | |
| segmentStream = StringIO() | |
| if format == 'vtt': | |
| write_vtt(segments, file=segmentStream, maxLineWidth=maxLineWidth) | |
| elif format == 'srt': | |
| write_srt(segments, file=segmentStream, maxLineWidth=maxLineWidth) | |
| else: | |
| raise Exception("Unknown format " + format) | |
| segmentStream.seek(0) | |
| return segmentStream.read() | |
| def __create_file(self, text: str, directory: str, fileName: str) -> str: | |
| # Write the text to a file | |
| with open(os.path.join(directory, fileName), 'w+', encoding="utf-8") as file: | |
| file.write(text) | |
| return file.name | |
| def create_ui(inputAudioMaxDuration, share=False, server_name: str = None): | |
| ui = WhisperTranscriber(inputAudioMaxDuration) | |
| ui_description = "Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse " | |
| ui_description += " audio and is also a multi-task model that can perform multilingual speech recognition " | |
| ui_description += " as well as speech translation and language identification. " | |
| ui_description += "\n\n\n\nFor longer audio files (>10 minutes) not in English, it is recommended that you select Silero VAD (Voice Activity Detector) in the VAD option." | |
| if inputAudioMaxDuration > 0: | |
| ui_description += "\n\n" + "Max audio file length: " + str(inputAudioMaxDuration) + " s" | |
| ui_article = "Read the [documentation here](https://huggingface.co/spaces/aadnk/whisper-webui/blob/main/docs/options.md)" | |
| demo = gr.Interface(fn=ui.transcribe_webui, description=ui_description, article=ui_article, inputs=[ | |
| gr.Dropdown(choices=["tiny", "base", "small", "medium", "large"], value="medium", label="Model"), | |
| gr.Dropdown(choices=sorted(LANGUAGES), label="Language"), | |
| gr.Text(label="URL (YouTube, etc.)"), | |
| gr.Audio(source="upload", type="filepath", label="Upload Audio"), | |
| gr.Audio(source="microphone", type="filepath", label="Microphone Input"), | |
| gr.Dropdown(choices=["transcribe", "translate"], label="Task"), | |
| gr.Dropdown(choices=["none", "silero-vad", "silero-vad-skip-gaps", "silero-vad-expand-into-gaps", "periodic-vad"], label="VAD"), | |
| gr.Number(label="VAD - Merge Window (s)", precision=0, value=5), | |
| gr.Number(label="VAD - Max Merge Size (s)", precision=0, value=30), | |
| gr.Number(label="VAD - Padding (s)", precision=None, value=1), | |
| gr.Number(label="VAD - Prompt Window (s)", precision=None, value=3) | |
| ], outputs=[ | |
| gr.File(label="Download"), | |
| gr.Text(label="Transcription"), | |
| gr.Text(label="Segments") | |
| ]) | |
| demo.launch(share=share, server_name=server_name) | |
| if __name__ == '__main__': | |
| create_ui(DEFAULT_INPUT_AUDIO_MAX_DURATION) |