Update app.py

app.py

@@ -1,7 +1,40 @@
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+import cv2
+# Load the video file
+cap = cv2.VideoCapture('video_file.mp4')
+# Check if the video has audio
+if cap.get(cv2.CAP_PROP_AUDIO_STATUS):
+   # Read the video frames
+   while True:
+       ret, frame = cap.read()
+       # Convert the frame to grayscale and apply thresholding
+       gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+       _, thresh = cv2.threshold(gray, 100, 255, cv2.THRESH_BINARY)
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+       # Display the resulting image
+       imshow("Thresholded Image", thresh)
+       # Check if the user presses the 'q' key
+       if cv2.waitKey(1) & 0xFF == ord('q'):
+           # Break out of the loop
+           break
+else:
+   print("No Audio Found")
+
+# Release the video capture
+cap.release()
+
+# Load the audio file
+audio, sr = librosa.load('audio_file.wav')
+
+# Generate a new audio file with the same duration as the video
+new_audio = np.zeros((len(frame), sr))
+for i in range(len(frame)):
+   # Calculate the time stamp for each pixel in the frame
+   t = (i * framerate) + start_time
+   
+   # Add the corresponding value from the audio signal to the new audio array
+   new_audio[i] = audio[int(t)]
+
+# Save the new audio file
+librosa.save('output_file.wav', new_audio, sr)