Update app.py

app.py

@@ -2,8 +2,25 @@ from transformers import pipeline
 from gtts import gTTS
 import subprocess
 import streamlit as st
+import os
 
-# Step 1: Extract Text from Audio using Hugging Face Transformers
+# Step 1: Extract audio from the video
+def extract_audio_from_video(video_path, audio_path="extracted_audio.mp3"):
+    # Use FFmpeg to extract audio from the video file
+    ffmpeg_command = [
+        "ffmpeg", 
+        "-i", video_path,  # Input video
+        "-vn",             # Disable video processing
+        "-acodec", "libmp3lame",  # Set audio codec to mp3
+        "-ar", "44100",     # Set audio sample rate
+        "-ac", "2",         # Set number of audio channels
+        audio_path
+    ]
+    subprocess.run(ffmpeg_command)
+    print(f"Audio extracted to {audio_path}")
+    return audio_path
+
+# Step 2: Extract text from the audio using Hugging Face Transformers (Whisper)
 def extract_text_from_audio(audio_path):
     # Load the ASR pipeline from Hugging Face with a Whisper-like model
     transcriber = pipeline("automatic-speech-recognition", model="openai/whisper-base")
@@ -18,7 +35,7 @@ def extract_text_from_audio(audio_path):
     
     return text
 
-# Step 2: Generate Voice-Over using gTTS
+# Step 3: Generate voice-over using gTTS
 def generate_voice_over(text, output_audio_path="voice_over.mp3"):
     # Generate audio with gTTS
     tts = gTTS(text=text, lang="en")
@@ -26,7 +43,7 @@ def generate_voice_over(text, output_audio_path="voice_over.mp3"):
     print(f"Voice-over saved as {output_audio_path}")
     return output_audio_path
 
-# Step 3: Combine Voice-Over with Original Video using FFmpeg
+# Step 4: Combine voice-over with original video using FFmpeg
 def add_voice_over_to_video(video_path, audio_path, output_video_path="output_video_with_voice.mp4"):
     # Use FFmpeg to combine video with new audio
     ffmpeg_command = [
@@ -36,29 +53,33 @@ def add_voice_over_to_video(video_path, audio_path, output_video_path="output_vi
         "-c:v", "copy",
         "-map", "0:v:0",
         "-map", "1:a:0",
-        "-shortest",
+        "-shortest",  # Ensure the video ends when the audio ends
         output_video_path
     ]
     subprocess.run(ffmpeg_command)
     print(f"Final video with voice-over saved as {output_video_path}")
 
-# Step 4: Run the complete process
+# Step 5: Run the complete process
 def main(video_path):
-    # Step 1: Extract text from video/audio
-    text = extract_text_from_audio(video_path)
+    # Step 1: Extract audio from the video
+    audio_path = extract_audio_from_video(video_path)
+    
+    # Step 2: Extract text from the audio
+    text = extract_text_from_audio(audio_path)
     print("Extracted Text:", text)
     
-    # Step 2: Generate voice-over from extracted text
-    audio_path = generate_voice_over(text)
+    # Step 3: Generate voice-over from extracted text
+    voice_over_path = generate_voice_over(text)
     
-    # Step 3: Add voice-over to the video
-    add_voice_over_to_video(video_path, audio_path)
+    # Step 4: Add voice-over to the video
+    add_voice_over_to_video(video_path, voice_over_path)
 
 # Streamlit interface to upload video file
 uploaded_file = st.file_uploader("Upload a video file", type=["mp4"])
 if uploaded_file is not None:
+    # Save the uploaded file as input_video.mp4
     with open("input_video.mp4", "wb") as f:
         f.write(uploaded_file.getbuffer())
     
-    # Call the main function after video is uploaded
+    # Call the main function after the video is uploaded
     main("input_video.mp4")