younes21000 commited on
Commit
96c70ac
·
verified ·
1 Parent(s): 9d76491

Update app.py

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Files changed (1) hide show
  1. app.py +8 -8
app.py CHANGED
@@ -1,4 +1,3 @@
1
- import gradio as gr
2
  import whisper
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  import os
4
  from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
@@ -36,8 +35,7 @@ def load_translation_model(target_language):
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  "hi": "hi", # Hindi
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  "ja": "ja", # Japanese
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  "ko": "ko", # Korean
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- "ru": "ru" # Russian
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-
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  }
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  target_lang_code = lang_codes.get(target_language)
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  if not target_lang_code:
@@ -68,7 +66,7 @@ def format_timestamp(seconds):
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  seconds = seconds % 60
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  return f"{hours:02}:{minutes:02}:{seconds:02},{milliseconds:03}"
70
 
71
- # Write subtitles in SRT format
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  def write_srt(transcription, output_file, tokenizer=None, translation_model=None):
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  with open(output_file, "w") as f:
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  for i, segment in enumerate(transcription['segments']):
@@ -113,9 +111,11 @@ def write_word(transcription, output_file, tokenizer=None, translation_model=Non
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114
  # Helper function to write PDF documents
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  def write_pdf(transcription, output_file, tokenizer=None, translation_model=None):
 
116
  c = canvas.Canvas(output_file, pagesize=A4)
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  app_dir = os.path.dirname(os.path.abspath(__file__))
118
 
 
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  nazanin_font_path = os.path.join(app_dir, 'B-NAZANIN.TTF')
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  arial_font_path = os.path.join(app_dir, 'Arial.ttf')
121
 
@@ -184,10 +184,10 @@ def write_ppt(transcription, output_file, tokenizer=None, translation_model=None
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  # Transcribing video and generating output
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  def transcribe_video(video_file, language, target_language, model_name, output_format):
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- actual_model_name = whisper_models[model_name]
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- model = whisper.load_model(actual_model_name)
189
 
190
- if video_file is not None:
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  video_file_path = video_file.name
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  else:
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  raise ValueError("No video file provided. Please upload a video file.")
@@ -250,4 +250,4 @@ iface = gr.Interface(
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  )
251
 
252
  # Run the interface
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- iface.launch(share=True)
 
 
1
  import whisper
2
  import os
3
  from transformers import M2M100ForConditionalGeneration, M2M100Tokenizer
 
35
  "hi": "hi", # Hindi
36
  "ja": "ja", # Japanese
37
  "ko": "ko", # Korean
38
+ "ru": "ru", # Russian
 
39
  }
40
  target_lang_code = lang_codes.get(target_language)
41
  if not target_lang_code:
 
66
  seconds = seconds % 60
67
  return f"{hours:02}:{minutes:02}:{seconds:02},{milliseconds:03}"
68
 
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+ # Corrected write_srt function
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  def write_srt(transcription, output_file, tokenizer=None, translation_model=None):
71
  with open(output_file, "w") as f:
72
  for i, segment in enumerate(transcription['segments']):
 
111
 
112
  # Helper function to write PDF documents
113
  def write_pdf(transcription, output_file, tokenizer=None, translation_model=None):
114
+ # Create PDF with A4 page size
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  c = canvas.Canvas(output_file, pagesize=A4)
116
  app_dir = os.path.dirname(os.path.abspath(__file__))
117
 
118
+ # Register fonts
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  nazanin_font_path = os.path.join(app_dir, 'B-NAZANIN.TTF')
120
  arial_font_path = os.path.join(app_dir, 'Arial.ttf')
121
 
 
184
 
185
  # Transcribing video and generating output
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  def transcribe_video(video_file, language, target_language, model_name, output_format):
187
+ actual_model_name = whisper_models[model_name] # Map user selection to model name
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+ model = whisper.load_model(actual_model_name) # Load the selected model
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190
+ if video_file is not None: # Ensure the video_file is not None
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  video_file_path = video_file.name
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  else:
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  raise ValueError("No video file provided. Please upload a video file.")
 
250
  )
251
 
252
  # Run the interface
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+ iface.launch(share=True)