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jhj0517 commited on
Commit
43820de
·
1 Parent(s): 379621f

added NLLB translation

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Files changed (4) hide show
  1. app.py +28 -1
  2. modules/nllb_inference.py +1 -1
  3. outputs/translations/outputs for translation are saved here.txt +0 -0
  4. ui/htmls.py +55 -0
app.py CHANGED
@@ -1,7 +1,8 @@
1
  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 CSS, MARKDOWN
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  from modules.youtube_manager import get_ytmetas
6
 
7
 
@@ -21,6 +22,7 @@ def on_change_models(model_size):
21
 
22
 
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  whisper_inf = WhisperInference()
 
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  block = gr.Blocks(css=CSS).queue(api_open=False)
25
 
26
  with block:
@@ -100,4 +102,29 @@ with block:
100
  btn_openfolder.click(fn=lambda: open_fodler("outputs"), inputs=None, outputs=None)
101
  dd_model.change(fn=on_change_models, inputs=[dd_model], outputs=[cb_translate])
102
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
103
  block.launch()
 
1
  import gradio as gr
2
  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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8
 
 
22
 
23
 
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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)
27
 
28
  with block:
 
102
  btn_openfolder.click(fn=lambda: open_fodler("outputs"), inputs=None, outputs=None)
103
  dd_model.change(fn=on_change_models, inputs=[dd_model], outputs=[cb_translate])
104
 
105
+ 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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+
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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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+
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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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+
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+
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  block.launch()
modules/nllb_inference.py CHANGED
@@ -68,7 +68,7 @@ class NLLBInference:
68
 
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  write_file(subtitle, f"{output_path}.srt")
70
 
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- elif file_path == ".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):
 
68
 
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  write_file(subtitle, f"{output_path}.srt")
70
 
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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):
outputs/translations/outputs for translation are saved here.txt ADDED
File without changes
ui/htmls.py CHANGED
@@ -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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+
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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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+
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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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+
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+ </body>
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+ </html>
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  """