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| import os | |
| import subprocess | |
| import json | |
| from datetime import timedelta | |
| import tempfile | |
| import re | |
| import yt_dlp | |
| import gradio as gr | |
| import groq | |
| from groq import Groq | |
| import time | |
| import psutil | |
| import os | |
| # setup groq | |
| client = Groq(api_key=os.environ.get("Groq_Api_Key")) | |
| def handle_groq_error(e, model_name): | |
| error_data = e.args[0] | |
| if isinstance(error_data, str): | |
| # Use regex to extract the JSON part of the string | |
| json_match = re.search(r'(\{.*\})', error_data) | |
| if json_match: | |
| json_str = json_match.group(1) | |
| # Ensure the JSON string is well-formed | |
| json_str = json_str.replace("'", '"') # Replace single quotes with double quotes | |
| error_data = json.loads(json_str) | |
| if isinstance(e, groq.AuthenticationError): | |
| if isinstance(error_data, dict) and 'error' in error_data and 'message' in error_data['error']: | |
| error_message = error_data['error']['message'] | |
| raise gr.Error(error_message) | |
| elif isinstance(e, groq.RateLimitError): | |
| if isinstance(error_data, dict) and 'error' in error_data and 'message' in error_data['error']: | |
| error_message = error_data['error']['message'] | |
| error_message = re.sub(r'org_[a-zA-Z0-9]+', 'org_(censored)', error_message) # censor org | |
| raise gr.Error(error_message) | |
| else: | |
| raise gr.Error(f"Error during Groq API call: {e}") | |
| # language codes for subtitle maker | |
| LANGUAGE_CODES = { | |
| "English": "en", | |
| "Chinese": "zh", | |
| "German": "de", | |
| "Spanish": "es", | |
| "Russian": "ru", | |
| "Korean": "ko", | |
| "French": "fr", | |
| "Japanese": "ja", | |
| "Portuguese": "pt", | |
| "Turkish": "tr", | |
| "Polish": "pl", | |
| "Catalan": "ca", | |
| "Dutch": "nl", | |
| "Arabic": "ar", | |
| "Swedish": "sv", | |
| "Italian": "it", | |
| "Indonesian": "id", | |
| "Hindi": "hi", | |
| "Finnish": "fi", | |
| "Vietnamese": "vi", | |
| "Hebrew": "he", | |
| "Ukrainian": "uk", | |
| "Greek": "el", | |
| "Malay": "ms", | |
| "Czech": "cs", | |
| "Romanian": "ro", | |
| "Danish": "da", | |
| "Hungarian": "hu", | |
| "Tamil": "ta", | |
| "Norwegian": "no", | |
| "Thai": "th", | |
| "Urdu": "ur", | |
| "Croatian": "hr", | |
| "Bulgarian": "bg", | |
| "Lithuanian": "lt", | |
| "Latin": "la", | |
| "Māori": "mi", | |
| "Malayalam": "ml", | |
| "Welsh": "cy", | |
| "Slovak": "sk", | |
| "Telugu": "te", | |
| "Persian": "fa", | |
| "Latvian": "lv", | |
| "Bengali": "bn", | |
| "Serbian": "sr", | |
| "Azerbaijani": "az", | |
| "Slovenian": "sl", | |
| "Kannada": "kn", | |
| "Estonian": "et", | |
| "Macedonian": "mk", | |
| "Breton": "br", | |
| "Basque": "eu", | |
| "Icelandic": "is", | |
| "Armenian": "hy", | |
| "Nepali": "ne", | |
| "Mongolian": "mn", | |
| "Bosnian": "bs", | |
| "Kazakh": "kk", | |
| "Albanian": "sq", | |
| "Swahili": "sw", | |
| "Galician": "gl", | |
| "Marathi": "mr", | |
| "Panjabi": "pa", | |
| "Sinhala": "si", | |
| "Khmer": "km", | |
| "Shona": "sn", | |
| "Yoruba": "yo", | |
| "Somali": "so", | |
| "Afrikaans": "af", | |
| "Occitan": "oc", | |
| "Georgian": "ka", | |
| "Belarusian": "be", | |
| "Tajik": "tg", | |
| "Sindhi": "sd", | |
| "Gujarati": "gu", | |
| "Amharic": "am", | |
| "Yiddish": "yi", | |
| "Lao": "lo", | |
| "Uzbek": "uz", | |
| "Faroese": "fo", | |
| "Haitian": "ht", | |
| "Pashto": "ps", | |
| "Turkmen": "tk", | |
| "Norwegian Nynorsk": "nn", | |
| "Maltese": "mt", | |
| "Sanskrit": "sa", | |
| "Luxembourgish": "lb", | |
| "Burmese": "my", | |
| "Tibetan": "bo", | |
| "Tagalog": "tl", | |
| "Malagasy": "mg", | |
| "Assamese": "as", | |
| "Tatar": "tt", | |
| "Hawaiian": "haw", | |
| "Lingala": "ln", | |
| "Hausa": "ha", | |
| "Bashkir": "ba", | |
| "jw": "jw", | |
| "Sundanese": "su", | |
| } | |
| # download link input | |
| def yt_dlp_download(link): | |
| try: | |
| ydl_opts = { | |
| 'format': 'bestvideo+bestaudio/best', # Download best video and audio or best available | |
| 'outtmpl': '%(title)s.%(ext)s', | |
| 'nocheckcertificate': True, | |
| 'ignoreerrors': False, | |
| 'no_warnings': True, | |
| 'quiet': True, | |
| } | |
| with yt_dlp.YoutubeDL(ydl_opts) as ydl: | |
| ydl.download([link]) | |
| result = ydl.extract_info(link, download=False) | |
| download_path = ydl.prepare_filename(result) | |
| return download_path | |
| except yt_dlp.utils.DownloadError as e: | |
| raise gr.Error(f"Download Error: {e}") | |
| except ValueError as e: | |
| raise gr.Error(f"Invalid Link or Format Error: {e}") | |
| except Exception as e: | |
| raise gr.Error(f"An unexpected error occurred: {e}") | |
| # helper functions | |
| def split_audio(input_file_path, chunk_size_mb): | |
| chunk_size = chunk_size_mb * 1024 * 1024 # Convert MB to bytes | |
| file_number = 1 | |
| chunks = [] | |
| with open(input_file_path, 'rb') as f: | |
| chunk = f.read(chunk_size) | |
| while chunk: | |
| chunk_name = f"{os.path.splitext(input_file_path)[0]}_part{file_number:03}.mp3" # Pad file number for correct ordering | |
| with open(chunk_name, 'wb') as chunk_file: | |
| chunk_file.write(chunk) | |
| chunks.append(chunk_name) | |
| file_number += 1 | |
| chunk = f.read(chunk_size) | |
| return chunks | |
| def merge_audio(chunks, output_file_path): | |
| with open("temp_list.txt", "w") as f: | |
| for file in chunks: | |
| f.write(f"file '{file}'\n") | |
| try: | |
| subprocess.run( | |
| [ | |
| "ffmpeg", | |
| "-f", | |
| "concat", | |
| "-safe", "0", | |
| "-i", | |
| "temp_list.txt", | |
| "-c", | |
| "copy", | |
| "-y", | |
| output_file_path | |
| ], | |
| check=True | |
| ) | |
| os.remove("temp_list.txt") | |
| for chunk in chunks: | |
| os.remove(chunk) | |
| except subprocess.CalledProcessError as e: | |
| raise gr.Error(f"Error during audio merging: {e}") | |
| # Checks file extension, size, and downsamples or splits if needed. | |
| ALLOWED_FILE_EXTENSIONS = ["mp3", "mp4", "mpeg", "mpga", "m4a", "wav", "webm"] | |
| MAX_FILE_SIZE_MB = 25 | |
| CHUNK_SIZE_MB = 25 | |
| def check_file(input_file_path): | |
| if not input_file_path: | |
| raise gr.Error("Please upload an audio/video file.") | |
| file_size_mb = os.path.getsize(input_file_path) / (1024 * 1024) | |
| file_extension = input_file_path.split(".")[-1].lower() | |
| if file_extension not in ALLOWED_FILE_EXTENSIONS: | |
| raise gr.Error(f"Invalid file type (.{file_extension}). Allowed types: {', '.join(ALLOWED_FILE_EXTENSIONS)}") | |
| if file_size_mb > MAX_FILE_SIZE_MB: | |
| gr.Warning( | |
| f"File size too large ({file_size_mb:.2f} MB). Attempting to downsample to 16kHz MP3 128kbps. Maximum size allowed: {MAX_FILE_SIZE_MB} MB" | |
| ) | |
| output_file_path = os.path.splitext(input_file_path)[0] + "_downsampled.mp3" | |
| try: | |
| subprocess.run( | |
| [ | |
| "ffmpeg", | |
| "-i", | |
| input_file_path, | |
| "-ar", | |
| "16000", | |
| "-ab", | |
| "128k", | |
| "-ac", | |
| "1", | |
| "-f", | |
| "mp3", | |
| "-y", | |
| output_file_path, | |
| ], | |
| check=True | |
| ) | |
| # Check size after downsampling | |
| downsampled_size_mb = os.path.getsize(output_file_path) / (1024 * 1024) | |
| if downsampled_size_mb > MAX_FILE_SIZE_MB: | |
| gr.Warning(f"File still too large after downsampling ({downsampled_size_mb:.2f} MB). Splitting into {CHUNK_SIZE_MB} MB chunks.") | |
| return split_audio(output_file_path, CHUNK_SIZE_MB), "split" | |
| return output_file_path, None | |
| except subprocess.CalledProcessError as e: | |
| raise gr.Error(f"Error during downsampling: {e}") | |
| return input_file_path, None | |
| # subtitle maker | |
| def format_time(seconds): | |
| hours = int(seconds // 3600) | |
| minutes = int((seconds % 3600) // 60) | |
| seconds = int(seconds % 60) | |
| milliseconds = int((seconds % 1) * 1000) | |
| return f"{hours:02}:{minutes:02}:{seconds:02},{milliseconds:03}" | |
| def json_to_srt(transcription_json): | |
| srt_lines = [] | |
| for segment in transcription_json: | |
| start_time = format_time(segment['start']) | |
| end_time = format_time(segment['end']) | |
| text = segment['text'] | |
| srt_line = f"{segment['id']+1}\n{start_time} --> {end_time}\n{text}\n" | |
| srt_lines.append(srt_line) | |
| return '\n'.join(srt_lines) | |
| def generate_subtitles(input_mode, input_file, link_input, prompt, language, auto_detect_language, model, include_video, font_selection, font_file, font_color, font_size, outline_thickness, outline_color): | |
| if input_mode == "Upload Video/Audio File": | |
| input_file_path = input_file | |
| elif input_mode == "Link Video/Audio": | |
| input_file_path = yt_dlp_download(link_input) | |
| processed_path, split_status = check_file(input_file_path) | |
| full_srt_content = "" | |
| total_duration = 0 | |
| segment_id_offset = 0 | |
| if split_status == "split": | |
| srt_chunks = [] | |
| video_chunks = [] | |
| for i, chunk_path in enumerate(processed_path): | |
| try: | |
| with open(chunk_path, "rb") as file: | |
| transcription_json_response = client.audio.transcriptions.create( | |
| file=(os.path.basename(chunk_path), file.read()), | |
| model=model, | |
| prompt=prompt, | |
| response_format="verbose_json", | |
| language=None if auto_detect_language else language, | |
| temperature=0.0, | |
| ) | |
| transcription_json = transcription_json_response.segments | |
| # Adjust timestamps and segment IDs | |
| for segment in transcription_json: | |
| segment['start'] += total_duration | |
| segment['end'] += total_duration | |
| segment['id'] += segment_id_offset | |
| segment_id_offset += len(transcription_json) | |
| total_duration += transcription_json[-1]['end'] # Update total duration | |
| srt_content = json_to_srt(transcription_json) | |
| full_srt_content += srt_content | |
| temp_srt_path = f"{os.path.splitext(chunk_path)[0]}.srt" | |
| with open(temp_srt_path, "w", encoding="utf-8") as temp_srt_file: | |
| temp_srt_file.write(srt_content) | |
| temp_srt_file.write("\n") # add a new line at the end of the srt chunk file to fix format when merged | |
| srt_chunks.append(temp_srt_path) | |
| if include_video and input_file_path.lower().endswith((".mp4", ".webm")): | |
| try: | |
| output_file_path = chunk_path.replace(os.path.splitext(chunk_path)[1], "_with_subs" + os.path.splitext(chunk_path)[1]) | |
| # Handle font selection | |
| if font_selection == "Custom Font File" and font_file: | |
| font_name = os.path.splitext(os.path.basename(font_file.name))[0] # Get font filename without extension | |
| font_dir = os.path.dirname(font_file.name) # Get font directory path | |
| elif font_selection == "Custom Font File" and not font_file: | |
| font_name = None # Let FFmpeg use its default Arial | |
| font_dir = None # No font directory | |
| gr.Warning(f"You want to use a Custom Font File, but uploaded none. Using the default Arial font.") | |
| elif font_selection == "Arial": | |
| font_name = None # Let FFmpeg use its default Arial | |
| font_dir = None # No font directory | |
| # FFmpeg command | |
| subprocess.run( | |
| [ | |
| "ffmpeg", | |
| "-y", | |
| "-i", | |
| chunk_path, | |
| "-vf", | |
| f"subtitles={temp_srt_path}:fontsdir={font_dir}:force_style='Fontname={font_name},Fontsize={int(font_size)},PrimaryColour=&H{font_color[1:]}&,OutlineColour=&H{outline_color[1:]}&,BorderStyle={int(outline_thickness)},Outline=1'", | |
| "-preset", "fast", | |
| output_file_path, | |
| ], | |
| check=True, | |
| ) | |
| video_chunks.append(output_file_path) | |
| except subprocess.CalledProcessError as e: | |
| raise gr.Error(f"Error during subtitle addition: {e}") | |
| elif include_video and not input_file_path.lower().endswith((".mp4", ".webm")): | |
| gr.Warning(f"You have checked on the 'Include Video with Subtitles', but the input file {input_file_path} isn't a video (.mp4 or .webm). Returning only the SRT File.", duration=15) | |
| except groq.AuthenticationError as e: | |
| handle_groq_error(e, model) | |
| except groq.RateLimitError as e: | |
| handle_groq_error(e, model) | |
| gr.Warning(f"API limit reached during chunk {i+1}. Returning processed chunks only.") | |
| if srt_chunks and video_chunks: | |
| merge_audio(video_chunks, 'merged_output_video.mp4') | |
| with open('merged_output.srt', 'w', encoding="utf-8") as outfile: | |
| for chunk_srt in srt_chunks: | |
| with open(chunk_srt, 'r', encoding="utf-8") as infile: | |
| outfile.write(infile.read()) | |
| return 'merged_output.srt', 'merged_output_video.mp4' | |
| else: | |
| raise gr.Error("Subtitle generation failed due to API limits.") | |
| # Merge SRT chunks | |
| final_srt_path = os.path.splitext(input_file_path)[0] + "_final.srt" | |
| with open(final_srt_path, 'w', encoding="utf-8") as outfile: | |
| for chunk_srt in srt_chunks: | |
| with open(chunk_srt, 'r', encoding="utf-8") as infile: | |
| outfile.write(infile.read()) | |
| # Merge video chunks | |
| if video_chunks: | |
| merge_audio(video_chunks, 'merged_output_video.mp4') | |
| return final_srt_path, 'merged_output_video.mp4' | |
| else: | |
| return final_srt_path, None | |
| else: # Single file processing (no splitting) | |
| try: | |
| with open(processed_path, "rb") as file: | |
| transcription_json_response = client.audio.transcriptions.create( | |
| file=(os.path.basename(processed_path), file.read()), | |
| model=model, | |
| prompt=prompt, | |
| response_format="verbose_json", | |
| language=None if auto_detect_language else language, | |
| temperature=0.0, | |
| ) | |
| transcription_json = transcription_json_response.segments | |
| srt_content = json_to_srt(transcription_json) | |
| temp_srt_path = os.path.splitext(input_file_path)[0] + ".srt" | |
| with open(temp_srt_path, "w", encoding="utf-8") as temp_srt_file: | |
| temp_srt_file.write(srt_content) | |
| if include_video and input_file_path.lower().endswith((".mp4", ".webm")): | |
| try: | |
| output_file_path = input_file_path.replace( | |
| os.path.splitext(input_file_path)[1], "_with_subs" + os.path.splitext(input_file_path)[1] | |
| ) | |
| # Handle font selection | |
| if font_selection == "Custom Font File" and font_file: | |
| font_name = os.path.splitext(os.path.basename(font_file.name))[0] # Get font filename without extension | |
| font_dir = os.path.dirname(font_file.name) # Get font directory path | |
| elif font_selection == "Custom Font File" and not font_file: | |
| font_name = None # Let FFmpeg use its default Arial | |
| font_dir = None # No font directory | |
| gr.Warning(f"You want to use a Custom Font File, but uploaded none. Using the default Arial font.") | |
| elif font_selection == "Arial": | |
| font_name = None # Let FFmpeg use its default Arial | |
| font_dir = None # No font directory | |
| # FFmpeg command | |
| subprocess.run( | |
| [ | |
| "ffmpeg", | |
| "-y", | |
| "-i", | |
| input_file_path, | |
| "-vf", | |
| f"subtitles={temp_srt_path}:fontsdir={font_dir}:force_style='FontName={font_name},Fontsize={int(font_size)},PrimaryColour=&H{font_color[1:]}&,OutlineColour=&H{outline_color[1:]}&,BorderStyle={int(outline_thickness)},Outline=1'", | |
| "-preset", "fast", | |
| output_file_path, | |
| ], | |
| check=True, | |
| ) | |
| return temp_srt_path, output_file_path | |
| except subprocess.CalledProcessError as e: | |
| raise gr.Error(f"Error during subtitle addition: {e}") | |
| elif include_video and not input_file_path.lower().endswith((".mp4", ".webm")): | |
| gr.Warning(f"You have checked on the 'Include Video with Subtitles', but the input file {input_file_path} isn't a video (.mp4 or .webm). Returning only the SRT File.", duration=15) | |
| return temp_srt_path, None | |
| except groq.AuthenticationError as e: | |
| handle_groq_error(e, model) | |
| except groq.RateLimitError as e: | |
| handle_groq_error(e, model) | |
| except ValueError as e: | |
| raise gr.Error(f"Error creating SRT file: {e}") | |
| theme = gr.themes.Soft( | |
| primary_hue="sky", | |
| secondary_hue="blue", | |
| neutral_hue="neutral" | |
| ).set( | |
| border_color_primary='*neutral_300', | |
| block_border_width='1px', | |
| block_border_width_dark='1px', | |
| block_title_border_color='*secondary_100', | |
| block_title_border_color_dark='*secondary_200', | |
| input_background_fill_focus='*secondary_300', | |
| input_border_color='*border_color_primary', | |
| input_border_color_focus='*secondary_500', | |
| input_border_width='1px', | |
| input_border_width_dark='1px', | |
| slider_color='*secondary_500', | |
| slider_color_dark='*secondary_600' | |
| ) | |
| css = """ | |
| .gradio-container{max-width: 1400px !important} | |
| h1{text-align:center} | |
| .extra-option { | |
| display: none; | |
| } | |
| .extra-option.visible { | |
| display: block; | |
| } | |
| """ | |
| with gr.Blocks(theme=theme, css=css) as interface: | |
| gr.Markdown( | |
| """ | |
| # Case Study 1 - Fast Subtitle Maker - Team 15 | |
| Team members: Arturo Lemos, David Datta, and Jose Perez. | |
| Inference by Groq API | |
| This code was adapted from the [Hugging Face Space](https://huggingface.co/spaces/Nick088/Fast-Subtitle-Maker) by Nick088 to generate subtitles for audio and video files. The model used is the [whisper-large-v3](https://console.groq.com/models/whisper-large-v3) model. You can also use the [distil-whisper-large-v3-en](https://console.groq.com/models/distil-whisper-large-v3-en) model for English language only. The subtitles are generated in the SubRip (SRT) format, which can be uploaded to any video editing app for adding subtitles to your video. You can also choose to include the video with subtitles. The video output will be in MP4 format with the subtitles added. You can also customize the font, font color, font size, outline thickness, and outline color of the subtitles. | |
| """ | |
| ) | |
| with gr.Column(): | |
| # Input mode selection | |
| input_mode = gr.Dropdown(choices=["Upload Video/Audio File", "Link Video/Audio"], value="Upload Video/Audio File", label="Input Mode") | |
| # Input components | |
| input_file = gr.File(label="Upload Audio/Video", file_types=[f".{ext}" for ext in ALLOWED_FILE_EXTENSIONS], visible=True) | |
| link_input_info = gr.Markdown("Using yt-dlp to download Youtube Video Links + other platform's ones. Check [all supported sites](https://github.com/yt-dlp/yt-dlp/blob/master/supportedsites.md)!", visible=False) | |
| link_input = gr.Textbox(label="Enter Video/Audio Link", visible=False) | |
| # Model and options | |
| model_choice_subtitles = gr.Dropdown(choices=["whisper-large-v3", "distil-whisper-large-v3-en"], value="whisper-large-v3", label="Audio Speech Recogition (ASR) Model") | |
| transcribe_prompt_subtitles = gr.Textbox(label="Prompt (Optional)", info="Specify any context or spelling corrections.") | |
| with gr.Row(): | |
| language_subtitles = gr.Dropdown(choices=[(lang, code) for lang, code in LANGUAGE_CODES.items()], value="en", label="Language") | |
| auto_detect_language_subtitles = gr.Checkbox(label="Auto Detect Language") | |
| # Generate button | |
| transcribe_button_subtitles = gr.Button("Generate Subtitles") | |
| # Output and settings | |
| include_video_option = gr.Checkbox(label="Include Video with Subtitles") | |
| gr.Markdown("The SubText Rip (SRT) File, contains the subtitles, you can upload this to any video editing app for adding the subs to your video and also modify/stilyze them") | |
| srt_output = gr.File(label="SRT Output File") | |
| show_subtitle_settings = gr.Checkbox(label="Show Subtitle Video Settings", visible=False) | |
| with gr.Row(visible=False) as subtitle_video_settings: | |
| with gr.Column(): | |
| font_selection = gr.Radio(["Arial", "Custom Font File"], value="Arial", label="Font Selection", info="Select what font to use") | |
| font_file = gr.File(label="Upload Font File (TTF or OTF)", file_types=[".ttf", ".otf"], visible=False) | |
| font_color = gr.ColorPicker(label="Font Color", value="#FFFFFF") | |
| font_size = gr.Slider(label="Font Size (in pixels)", minimum=10, maximum=60, value=24, step=1) | |
| outline_thickness = gr.Slider(label="Outline Thickness", minimum=0, maximum=5, value=1, step=1) | |
| outline_color = gr.ColorPicker(label="Outline Color", value="#000000") | |
| video_output = gr.Video(label="Output Video with Subtitles", visible=False) | |
| # Event bindings | |
| # input mode | |
| def toggle_input(mode): | |
| if mode == "Upload Video/Audio File": | |
| return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False) | |
| else: | |
| return gr.update(visible=False), gr.update(visible=True), gr.update(visible=True) | |
| input_mode.change(fn=toggle_input, inputs=[input_mode], outputs=[input_file, link_input_info, link_input]) | |
| # show video output | |
| include_video_option.change(lambda include_video: gr.update(visible=include_video), inputs=[include_video_option], outputs=[video_output]) | |
| # show video output subs settings checkbox | |
| include_video_option.change(lambda include_video: gr.update(visible=include_video), inputs=[include_video_option], outputs=[show_subtitle_settings]) | |
| # show video output subs settings | |
| show_subtitle_settings.change(lambda show: gr.update(visible=show), inputs=[show_subtitle_settings], outputs=[subtitle_video_settings]) | |
| # uncheck show subtitle settings checkbox if include video is unchecked (to make the output subs settings not visible) | |
| show_subtitle_settings.change(lambda show, include_video: gr.update(visible=show and include_video), inputs=[show_subtitle_settings, include_video_option], outputs=[show_subtitle_settings]) | |
| # show custom font file selection | |
| font_selection.change(lambda font_selection: gr.update(visible=font_selection == "Custom Font File"), inputs=[font_selection], outputs=[font_file]) | |
| # Update language dropdown based on model selection | |
| def update_language_options(model): | |
| if model == "distil-whisper-large-v3-en": | |
| return gr.update(choices=[("English", "en")], value="en", interactive=False) | |
| else: | |
| return gr.update(choices=[(lang, code) for lang, code in LANGUAGE_CODES.items()], value="en", interactive=True) | |
| model_choice_subtitles.change(fn=update_language_options, inputs=[model_choice_subtitles], outputs=[language_subtitles]) | |
| # Modified generate subtitles event | |
| transcribe_button_subtitles.click( | |
| fn=generate_subtitles, | |
| inputs=[ | |
| input_mode, | |
| input_file, | |
| link_input, | |
| transcribe_prompt_subtitles, | |
| language_subtitles, | |
| auto_detect_language_subtitles, | |
| model_choice_subtitles, | |
| include_video_option, | |
| font_selection, | |
| font_file, | |
| font_color, | |
| font_size, | |
| outline_thickness, | |
| outline_color, | |
| ], | |
| outputs=[srt_output, video_output], | |
| ) | |
| interface.launch(share=True) | |