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|
| import logging |
| import os |
| from pathlib import Path |
|
|
| import gradio as gr |
|
|
| from decode import decode |
| from model import get_pretrained_model, get_vad, language_to_models |
|
|
| title = "# Next-gen Kaldi: Generate subtitles for videos" |
|
|
| description = """ |
| This space shows how to generate subtitles/captions with Next-gen Kaldi. |
| |
| It is running on CPU within a docker container provided by Hugging Face. |
| |
| Please find test video files at |
| <https://huggingface.co/csukuangfj/vad/tree/main> |
| |
| See more information by visiting the following links: |
| |
| - <https://github.com/k2-fsa/sherpa-onnx> |
| - <https://github.com/k2-fsa/icefall> |
| - <https://github.com/k2-fsa/k2> |
| - <https://github.com/lhotse-speech/lhotse> |
| |
| If you want to deploy it locally, please see |
| <https://k2-fsa.github.io/sherpa/> |
| """ |
|
|
| |
| |
| css = """ |
| .result {display:flex;flex-direction:column} |
| .result_item {padding:15px;margin-bottom:8px;border-radius:15px;width:100%} |
| .result_item_success {background-color:mediumaquamarine;color:white;align-self:start} |
| .result_item_error {background-color:#ff7070;color:white;align-self:start} |
| """ |
|
|
|
|
| def update_model_dropdown(language: str): |
| if language in language_to_models: |
| choices = language_to_models[language] |
| return gr.Dropdown.update(choices=choices, value=choices[0]) |
|
|
| raise ValueError(f"Unsupported language: {language}") |
|
|
|
|
| def build_html_output(s: str, style: str = "result_item_success"): |
| return f""" |
| <div class='result'> |
| <div class='result_item {style}'> |
| {s} |
| </div> |
| </div> |
| """ |
|
|
|
|
| def show_file_info(in_filename: str): |
| logging.info(f"Input file: {in_filename}") |
| _ = os.system(f"ffprobe -hide_banner -i '{in_filename}'") |
|
|
|
|
| def process_uploaded_video_file( |
| language: str, |
| repo_id: str, |
| in_filename: str, |
| ): |
| if in_filename is None or in_filename == "": |
| return "", build_html_output( |
| "Please first upload a file and then click " |
| 'the button "submit for recognition"', |
| "result_item_error", |
| ) |
|
|
| logging.info(f"Processing uploaded file: {in_filename}") |
|
|
| ans = process(language, repo_id, in_filename) |
| return (in_filename, ans[0]), ans[0], ans[1], ans[2] |
|
|
|
|
| def process_uploaded_audio_file( |
| language: str, |
| repo_id: str, |
| in_filename: str, |
| ): |
| if in_filename is None or in_filename == "": |
| return "", build_html_output( |
| "Please first upload a file and then click " |
| 'the button "submit for recognition"', |
| "result_item_error", |
| ) |
|
|
| logging.info(f"Processing uploaded file: {in_filename}") |
|
|
| return process(language, repo_id, in_filename) |
|
|
|
|
| def process(language: str, repo_id: str, in_filename: str): |
| recognizer = get_pretrained_model(repo_id) |
| vad = get_vad() |
|
|
| result = decode(recognizer, vad, in_filename) |
| logging.info(result) |
|
|
| srt_filename = Path(in_filename).with_suffix(".srt") |
| with open(srt_filename, "w", encoding="utf-8") as f: |
| f.write(result) |
|
|
| show_file_info(in_filename) |
| logging.info("Done") |
|
|
| return ( |
| srt_filename, |
| build_html_output("Done! Please download the SRT file", "result_item_success"), |
| result, |
| ) |
|
|
|
|
| demo = gr.Blocks(css=css) |
|
|
|
|
| with demo: |
| gr.Markdown(title) |
| language_choices = list(language_to_models.keys()) |
|
|
| language_radio = gr.Radio( |
| label="Language", |
| choices=language_choices, |
| value=language_choices[0], |
| ) |
|
|
| model_dropdown = gr.Dropdown( |
| choices=language_to_models[language_choices[0]], |
| label="Select a model", |
| value=language_to_models[language_choices[0]][0], |
| ) |
|
|
| language_radio.change( |
| update_model_dropdown, |
| inputs=language_radio, |
| outputs=model_dropdown, |
| ) |
|
|
| with gr.Tabs(): |
| with gr.TabItem("Upload video from disk"): |
| uploaded_video_file = gr.Video( |
| source="upload", |
| interactive=True, |
| label="Upload from disk", |
| show_share_button=True, |
| ) |
| upload_video_button = gr.Button("Submit for recognition") |
|
|
| output_video = gr.Video(label="Output") |
| output_srt_file_video = gr.File( |
| label="Generated subtitles", show_label=True |
| ) |
|
|
| output_info_video = gr.HTML(label="Info") |
| output_textbox_video = gr.Textbox( |
| label="Recognized speech from uploaded video file" |
| ) |
|
|
| with gr.TabItem("Upload audio from disk"): |
| uploaded_audio_file = gr.Audio( |
| source="upload", |
| type="filepath", |
| optional=False, |
| label="Upload audio from disk", |
| ) |
| upload_audio_button = gr.Button("Submit for recognition") |
|
|
| output_srt_file_audio = gr.File( |
| label="Generated subtitles", show_label=True |
| ) |
|
|
| output_info_audio = gr.HTML(label="Info") |
| output_textbox_audio = gr.Textbox( |
| label="Recognized speech from uploaded audio file" |
| ) |
|
|
| upload_video_button.click( |
| process_uploaded_video_file, |
| inputs=[ |
| language_radio, |
| model_dropdown, |
| uploaded_video_file, |
| ], |
| outputs=[ |
| output_video, |
| output_srt_file_video, |
| output_info_video, |
| output_textbox_video, |
| ], |
| ) |
|
|
| upload_audio_button.click( |
| process_uploaded_audio_file, |
| inputs=[ |
| language_radio, |
| model_dropdown, |
| uploaded_audio_file, |
| ], |
| outputs=[ |
| output_srt_file_audio, |
| output_info_audio, |
| output_textbox_audio, |
| ], |
| ) |
|
|
| gr.Markdown(description) |
|
|
| if __name__ == "__main__": |
| formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s" |
|
|
| logging.basicConfig(format=formatter, level=logging.INFO) |
|
|
| demo.launch() |
|
|
