Update app.py

app.py

@@ -8,10 +8,15 @@ import librosa.display
 import soundfile as sf
 import gradio as gr
 import tempfile
+import logging
+
+# Setup logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s', handlers=[logging.FileHandler("video_processing.log"), logging.StreamHandler()])
 
 # Function for displaying progress
 def display_progress(percent, message, progress=gr.Progress()):
  progress(percent, desc=message)
+ logging.info(message)
 
 # Function for extracting audio from video
 def extract_audio(video_path, progress):
@@ -19,13 +24,16 @@ def extract_audio(video_path, progress):
  try:
  video = VideoFileClip(video_path)
  if video.audio is None:
- raise ValueError("No audio found in the video")
+ raise ValueError("No audio found in the video. Please upload a video with an audio track.")
  audio_path = "extracted_audio.wav"
  video.audio.write_audiofile(audio_path)
  display_progress(0.2, "Audio extracted", progress)
+ logging.info(f"Audio extracted: {audio_path}")
  return audio_path
  except Exception as e:
- display_progress(0.2, f"Failed to extract audio: {e}", progress)
+ error_message = f"Failed to extract audio: {e}. Please check if the video file is valid and has an audio track."
+ display_progress(0.2, error_message, progress)
+ logging.error(error_message)
  return None
 
 # Function for dividing video into frames
@@ -33,6 +41,8 @@ def extract_frames(video_path, progress):
  display_progress(0.3, "Extracting frames from video", progress)
  try:
  video = cv2.VideoCapture(video_path)
+ if not video.isOpened():
+ raise ValueError("Failed to open video file. Please check if the file is accessible and valid.")
  frames = []
  success, frame = video.read()
  while success:
@@ -40,9 +50,12 @@ def extract_frames(video_path, progress):
  success, frame = video.read()
  video.release()
  display_progress(0.4, "Frames extracted", progress)
+ logging.info(f"Frames extracted: {len(frames)} frames")
  return frames
  except Exception as e:
- display_progress(0.4, f"Failed to extract frames: {e}", progress)
+ error_message = f"Failed to extract frames: {e}. Please check if the video file is valid and accessible."
+ display_progress(0.4, error_message, progress)
+ logging.error(error_message)
  return None
 
 # Convert frame to spectrogram
@@ -50,12 +63,14 @@ def frame_to_spectrogram(frame, sr=22050):
  gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
  S = np.flipud(gray_frame.astype(np.float32) / 255.0 * 100.0)
  y = librosa.griffinlim(S)
+ logging.info("Converted frame to spectrogram")
  return y
 
 # Saving audio
 def save_audio(y, sr=22050):
  audio_path = 'output_frame_audio.wav'
  sf.write(audio_path, y, sr)
+ logging.info(f"Audio saved: {audio_path}")
  return audio_path
 
 # Saving frame spectrogram
@@ -66,6 +81,7 @@ def save_spectrogram_image(S, frame_number, temp_dir):
  image_path = os.path.join(temp_dir, f'spectrogram_frame_{frame_number}.png')
  plt.savefig(image_path)
  plt.close()
+ logging.info(f"Spectrogram image saved: {image_path}")
  return image_path
 
 # Processing all video frames
@@ -79,7 +95,9 @@ def process_video_frames(frames, sr=22050, temp_dir=None, progress=gr.Progress()
  processed_frame = cv2.imread(image_path)
  processed_frames.append(processed_frame)
  display_progress(0.5 + int((i + 1) / total_frames * 0.7), f"Frame processing {i + 1}/{total_frames}", progress)
+ logging.info(f"Processed frame {i + 1}/{total_frames}")
  display_progress(0.8, "All frames processed", progress)
+ logging.info("All frames processed")
  return processed_frames
 
 # Saving video from frames
@@ -89,6 +107,7 @@ def save_video_from_frames(frames, output_path, fps=30):
  for frame in frames:
  video.write(frame)
  video.release()
+ logging.info(f"Video saved: {output_path}")
 
 # Adding audio back to video
 def add_audio_to_video(video_path, audio_path, output_path, progress):
@@ -99,17 +118,33 @@ def add_audio_to_video(video_path, audio_path, output_path, progress):
  final_video = video.set_audio(audio)
  final_video.write_videofile(output_path, codec='libx264', audio_codec='aac')
  display_progress(1, "Video's ready", progress)
+ logging.info(f"Final video saved: {output_path}")
  except Exception as e:
- display_progress(1, f"Failed to add audio to video: {e}", progress)
+ error_message = f"Failed to add audio to video: {e}. Please ensure that the audio and video files are valid."
+ display_progress(1, error_message, progress)
+ logging.error(error_message)
 
 # Gradio interface
 def process_video(video_path, progress=gr.Progress()):
+ try:
+ video = VideoFileClip(video_path)
+ if video.duration > 10:
+ logging.info(f"Video longer than 10 seconds, trimming to 10 seconds: {video_path}")
+ video = video.subclip(0, 10)
+ temp_trimmed_video_path = "trimmed_video.mp4"
+ video.write_videofile(temp_trimmed_video_path, codec='libx264')
+ video_path = temp_trimmed_video_path
+ except Exception as e:
+ error_message = f"Failed to load video: {e}. Please ensure the video file is valid."
+ logging.error(error_message)
+ return error_message
+
  audio_path = extract_audio(video_path, progress)
  if audio_path is None:
- return "Failed to extract audio from video."
+ return "Failed to extract audio from video. Please check the logs for more details."
  frames = extract_frames(video_path, progress)
  if frames is None:
- return "Failed to extract frames from video."
+ return "Failed to extract frames from video. Please check the logs for more details."
 
  # Creating a temporary folder for saving frames
  with tempfile.TemporaryDirectory() as temp_dir:
@@ -139,14 +174,18 @@ with gr.Blocks(title='Video from Spectrogram', theme=gr.themes.Soft(primary_hue=
  generate_button = gr.Button("Generate")
  with gr.Column(variant='panel'):
  video_output = gr.Video(label="VideoSpectrogram")
+ error_output = gr.HTML()
 
  def gradio_video_process_fn(video_input, progress=gr.Progress()):
- return process_video(video_input, progress)
+ result = process_video(video_input, progress)
+ if isinstance(result, str):
+ return "", result # If there is an error, return the error message
+ return result, "" # If no error, return the video path and empty error message
 
  generate_button.click(
  gradio_video_process_fn,
  inputs=[video_input],
- outputs=[video_output]
+ outputs=[video_output, error_output]
  )
 
 iface.launch(share=True)