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jhj0517
commited on
Commit
·
3fde2e0
1
Parent(s):
4e82fb6
added NLLB translation
Browse files- app.py +28 -1
- modules/nllb_inference.py +1 -1
- outputs/translations/outputs for translation are saved here.txt +0 -0
- ui/htmls.py +55 -0
app.py
CHANGED
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@@ -1,7 +1,8 @@
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import gradio as gr
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from modules.whisper_Inference import WhisperInference
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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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@@ -21,6 +22,7 @@ def on_change_models(model_size):
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whisper_inf = WhisperInference()
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block = gr.Blocks(css=CSS).queue(api_open=False)
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with block:
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@@ -100,4 +102,29 @@ with block:
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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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block.launch()
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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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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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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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modules/nllb_inference.py
CHANGED
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@@ -68,7 +68,7 @@ class NLLBInference:
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write_file(subtitle, f"{output_path}.srt")
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elif
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parsed_dicts = parse_vtt(file_path=file_path)
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total_progress = len(parsed_dicts)
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for index, dic in enumerate(parsed_dicts):
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write_file(subtitle, f"{output_path}.srt")
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elif file_ext == ".vtt":
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parsed_dicts = parse_vtt(file_path=file_path)
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total_progress = len(parsed_dicts)
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for index, dic in enumerate(parsed_dicts):
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outputs/translations/outputs for translation are saved here.txt
ADDED
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File without changes
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ui/htmls.py
CHANGED
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@@ -39,4 +39,59 @@ CSS = """
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MARKDOWN = """
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### [Whisper Web-UI](https://github.com/jhj0517/Whsiper-WebUI)
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"""
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MARKDOWN = """
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### [Whisper Web-UI](https://github.com/jhj0517/Whsiper-WebUI)
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"""
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NLLB_VRAM_TABLE = """
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<style>
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table {
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border-collapse: collapse;
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width: 100%;
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}
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th, td {
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border: 1px solid #dddddd;
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text-align: left;
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padding: 8px;
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}
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th {
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background-color: #f2f2f2;
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}
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</style>
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</head>
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<body>
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<details>
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<summary>VRAM usage for each model</summary>
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<table>
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<thead>
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<tr>
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<th>Model name</th>
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<th>Required VRAM</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td>nllb-200-3.3B</td>
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<td>~16GB</td>
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</tr>
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<tr>
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<td>nllb-200-1.3B</td>
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<td>~8GB</td>
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</tr>
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<tr>
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<td>nllb-200-distilled-600M</td>
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<td>~4GB</td>
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</tr>
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</tbody>
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</table>
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<p><strong>Note:</strong> Be mindful of your VRAM! The table above provides an approximate VRAM usage for each model.</p>
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</details>
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</body>
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</html>
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"""
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