Update app.py

app.py

@@ -1,17 +1,8 @@
-# Install dependencies if not already done in your environment
-# pip install transformers torch gtts ffmpeg-python
-
 from transformers import pipeline
 from gtts import gTTS
 import subprocess
 import streamlit as st
 
-uploaded_file = st.file_uploader("Upload a video file", type=["mp4"])
-if uploaded_file is not None:
-    with open("input_video.mp4", "wb") as f:
-        f.write(uploaded_file.getbuffer())
-    main("input_video.mp4")
-
 # Step 1: Extract Text from Audio using Hugging Face Transformers
 def extract_text_from_audio(audio_path):
     # Load the ASR pipeline from Hugging Face with a Whisper-like model
@@ -51,7 +42,7 @@ def add_voice_over_to_video(video_path, audio_path, output_video_path="output_vi
     subprocess.run(ffmpeg_command)
     print(f"Final video with voice-over saved as {output_video_path}")
 
-# Run the complete process
+# Step 4: Run the complete process
 def main(video_path):
     # Step 1: Extract text from video/audio
     text = extract_text_from_audio(video_path)
@@ -63,5 +54,11 @@ def main(video_path):
     # Step 3: Add voice-over to the video
     add_voice_over_to_video(video_path, audio_path)
 
-# Provide the path to your input video file
-main("input_video.mp4")
+# Streamlit interface to upload video file
+uploaded_file = st.file_uploader("Upload a video file", type=["mp4"])
+if uploaded_file is not None:
+    with open("input_video.mp4", "wb") as f:
+        f.write(uploaded_file.getbuffer())
+    
+    # Call the main function after video is uploaded
+    main("input_video.mp4")