131 lines
6.9 KiB
Python
131 lines
6.9 KiB
Python
import gradio as gr
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from modules.whisper_Inference import WhisperInference
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from modules.nllb_inference import NLLBInference
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import os
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from ui.htmls import *
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from modules.youtube_manager import get_ytmetas
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def open_fodler(folder_path):
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if os.path.exists(folder_path):
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os.system(f"start {folder_path}")
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else:
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print(f"The folder {folder_path} does not exist.")
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def on_change_models(model_size):
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translatable_model = ["large", "large-v1", "large-v2"]
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if model_size not in translatable_model:
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return gr.Checkbox.update(visible=False, value=False, interactive=False)
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else:
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return gr.Checkbox.update(visible=True, value=False, label="Translate to English?", interactive=True)
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whisper_inf = WhisperInference()
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nllb_inf = NLLBInference()
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block = gr.Blocks(css=CSS).queue(api_open=False)
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with block:
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with gr.Row():
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with gr.Column():
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gr.Markdown(MARKDOWN, elem_id="md_project")
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with gr.Tabs():
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with gr.TabItem("File"): # tab1
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with gr.Row():
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input_file = gr.Files(type="file", label="Upload File here")
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with gr.Row():
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dd_model = gr.Dropdown(choices=whisper_inf.available_models, value="large-v2", label="Model")
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dd_lang = gr.Dropdown(choices=["Automatic Detection"] + whisper_inf.available_langs,
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value="Automatic Detection", label="Language")
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dd_subformat = gr.Dropdown(["SRT", "WebVTT"], value="SRT", label="Subtitle Format")
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with gr.Row():
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cb_translate = gr.Checkbox(value=False, label="Translate to English?", interactive=True)
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with gr.Row():
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btn_run = gr.Button("GENERATE SUBTITLE FILE", variant="primary")
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with gr.Row():
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tb_indicator = gr.Textbox(label="Output")
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btn_openfolder = gr.Button('📂').style(full_width=False)
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btn_run.click(fn=whisper_inf.transcribe_file,
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inputs=[input_file, dd_model, dd_lang, dd_subformat, cb_translate], outputs=[tb_indicator])
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btn_openfolder.click(fn=lambda: open_fodler("outputs"), inputs=None, outputs=None)
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dd_model.change(fn=on_change_models, inputs=[dd_model], outputs=[cb_translate])
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with gr.TabItem("Youtube"): # tab2
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with gr.Row():
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tb_youtubelink = gr.Textbox(label="Youtube Link")
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with gr.Row().style(equal_height=True):
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with gr.Column():
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img_thumbnail = gr.Image(label="Youtube Thumbnail")
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with gr.Column():
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tb_title = gr.Label(label="Youtube Title")
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tb_description = gr.Textbox(label="Youtube Description", max_lines=15)
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with gr.Row():
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dd_model = gr.Dropdown(choices=whisper_inf.available_models, value="large-v2", label="Model")
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dd_lang = gr.Dropdown(choices=["Automatic Detection"] + whisper_inf.available_langs,
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value="Automatic Detection", label="Language")
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dd_subformat = gr.Dropdown(choices=["SRT", "WebVTT"], value="SRT", label="Subtitle Format")
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with gr.Row():
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cb_translate = gr.Checkbox(value=False, label="Translate to English?", interactive=True)
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with gr.Row():
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btn_run = gr.Button("GENERATE SUBTITLE FILE", variant="primary")
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with gr.Row():
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tb_indicator = gr.Textbox(label="Output")
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btn_openfolder = gr.Button('📂').style(full_width=False)
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btn_run.click(fn=whisper_inf.transcribe_youtube,
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inputs=[tb_youtubelink, dd_model, dd_lang, dd_subformat, cb_translate],
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outputs=[tb_indicator])
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tb_youtubelink.change(get_ytmetas, inputs=[tb_youtubelink],
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outputs=[img_thumbnail, tb_title, tb_description])
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btn_openfolder.click(fn=lambda: open_fodler("outputs"), inputs=None, outputs=None)
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dd_model.change(fn=on_change_models, inputs=[dd_model], outputs=[cb_translate])
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with gr.TabItem("Mic"): # tab3
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with gr.Row():
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mic_input = gr.Microphone(label="Record with Mic", type="filepath", interactive=True)
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with gr.Row():
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dd_model = gr.Dropdown(choices=whisper_inf.available_models, value="large-v2", label="Model")
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dd_lang = gr.Dropdown(choices=["Automatic Detection"] + whisper_inf.available_langs,
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value="Automatic Detection", label="Language")
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dd_subformat = gr.Dropdown(["SRT", "WebVTT"], value="SRT", label="Subtitle Format")
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with gr.Row():
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cb_translate = gr.Checkbox(value=False, label="Translate to English?", interactive=True)
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with gr.Row():
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btn_run = gr.Button("GENERATE SUBTITLE FILE", variant="primary")
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with gr.Row():
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tb_indicator = gr.Textbox(label="Output")
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btn_openfolder = gr.Button('📂').style(full_width=False)
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btn_run.click(fn=whisper_inf.transcribe_mic,
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inputs=[mic_input, dd_model, dd_lang, dd_subformat, cb_translate], outputs=[tb_indicator])
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btn_openfolder.click(fn=lambda: open_fodler("outputs"), inputs=None, outputs=None)
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dd_model.change(fn=on_change_models, inputs=[dd_model], outputs=[cb_translate])
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with gr.TabItem("T2T Translation"): # tab 4
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with gr.Row():
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file_subs = gr.Files(type="file", label="Upload Subtitle Files to translate here",
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file_types=['.vtt', '.srt'])
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with gr.TabItem("NLLB"): # sub tab1
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with gr.Row():
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dd_nllb_model = gr.Dropdown(label="Model", value=nllb_inf.default_model_size,
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choices=nllb_inf.available_models)
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dd_nllb_sourcelang = gr.Dropdown(label="Source Language", choices=nllb_inf.available_source_langs)
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dd_nllb_targetlang = gr.Dropdown(label="Target Language", choices=nllb_inf.available_target_langs)
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with gr.Row():
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btn_run = gr.Button("TRANSLATE SUBTITLE FILE", variant="primary")
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with gr.Row():
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tb_indicator = gr.Textbox(label="Output")
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btn_openfolder = gr.Button('📂').style(full_width=False)
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with gr.Column():
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md_vram_table = gr.HTML(NLLB_VRAM_TABLE, elem_id="md_nllb_vram_table")
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btn_run.click(fn=nllb_inf.translate_file,
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inputs=[file_subs, dd_nllb_model, dd_nllb_sourcelang, dd_nllb_targetlang],
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outputs=[tb_indicator])
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btn_openfolder.click(fn=lambda: open_fodler("outputs\\translations"), inputs=None, outputs=None)
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block.launch()
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