Artificial-superintelligence commited on
Commit
8eab835
·
verified ·
1 Parent(s): 76e4a7a

Update app.py

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Files changed (1) hide show
  1. app.py +26 -11
app.py CHANGED
@@ -1,16 +1,14 @@
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  import streamlit as st
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  from moviepy.editor import VideoFileClip
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  import whisper
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- from translate import Translator
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  from gtts import gTTS
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  import tempfile
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  import os
 
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  # Initialize Whisper model
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- try:
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- whisper_model = whisper.load_model("base") # Ensure the model is installed from the correct Whisper library
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- except AttributeError:
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- st.error("Whisper model could not be loaded. Ensure that Whisper is installed from GitHub.")
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  # Language options
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  LANGUAGES = {
@@ -46,15 +44,22 @@ if video_file:
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  os.remove(temp_video_path)
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  st.stop()
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- # Transcribe audio using Whisper
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  try:
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- result = whisper_model.transcribe(audio_path)
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- original_text = result["text"]
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- st.write("Original Transcription:", original_text)
 
 
 
 
 
 
 
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  # Translate text to the target language
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- translator = Translator(to_lang=LANGUAGES[target_language])
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- translated_text = translator.translate(original_text)
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  st.write(f"Translated Text ({target_language}):", translated_text)
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  # Convert translated text to speech
@@ -72,3 +77,13 @@ if video_file:
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  os.remove(temp_video_path)
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  os.remove(audio_path)
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  os.remove(audio_output_path)
 
 
 
 
 
 
 
 
 
 
 
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  import streamlit as st
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  from moviepy.editor import VideoFileClip
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  import whisper
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+ from googletrans import Translator
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  from gtts import gTTS
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  import tempfile
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  import os
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+ import numpy as np
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  # Initialize Whisper model
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+ whisper_model = whisper.load_model("base")
 
 
 
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  # Language options
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  LANGUAGES = {
 
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  os.remove(temp_video_path)
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  st.stop()
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+ # Transcribe audio using Whisper in chunks
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  try:
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+ # Load the audio file with Whisper
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+ audio = whisper.load_audio(audio_path)
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+ audio_segments = split_audio(audio, segment_length=30) # Split into 30-second segments
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+
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+ original_text = ""
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+ for segment in audio_segments:
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+ result = whisper_model.transcribe(segment)
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+ original_text += result["text"] + " " # Concatenate transcriptions
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+
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+ st.write("Original Transcription:", original_text.strip())
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  # Translate text to the target language
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+ translator = Translator()
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+ translated_text = translator.translate(original_text.strip(), dest=LANGUAGES[target_language]).text
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  st.write(f"Translated Text ({target_language}):", translated_text)
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  # Convert translated text to speech
 
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  os.remove(temp_video_path)
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  os.remove(audio_path)
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  os.remove(audio_output_path)
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+
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+ def split_audio(audio, segment_length=30):
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+ """Split audio into segments of specified length in seconds."""
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+ total_length = audio.shape[1] # Total length in seconds
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+ segments = []
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+ for start in range(0, total_length, segment_length):
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+ end = min(start + segment_length, total_length)
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+ segment = audio[:, start:end] # Append the segment
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+ segments.append(segment)
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+ return segments