Update app.py

app.py

@@ -3,8 +3,6 @@ import numpy as np
 import cv2
 import tempfile
 import os
-from io import BytesIO
-from matplotlib import pyplot as plt
 
 # Load model files
 prototxt_path = "colorization_deploy_v2.prototxt"
@@ -49,7 +47,7 @@ if uploaded_video is not None:
     # Initialize progress bar and frame counter
     frame_count = 0
     progress_bar = st.progress(0)
-    stframe = st.empty()  # Placeholder for showing frames in Streamlit
+    progress_text = st.empty()  # Placeholder for frame count text
 
     # Process each frame
     while True:
@@ -58,7 +56,7 @@ if uploaded_video is not None:
             break
 
         frame_count += 1
-        st.write(f"Processing frame {frame_count} of {total_frames}")
+        progress_text.text(f"Processing frame {frame_count} of {total_frames}")
 
         # Convert frame to LAB color space and preprocess
         normalized = frame.astype("float32") / 255.0
@@ -78,9 +76,8 @@ if uploaded_video is not None:
         colorized = cv2.cvtColor(colorized, cv2.COLOR_LAB2BGR)
         colorized = (255 * colorized).astype("uint8")
 
-        # Update the progress bar and display the current frame in Streamlit
+        # Update the progress line and frame count display
         progress_bar.progress(frame_count / total_frames)
-        stframe.image(colorized, channels="BGR", caption=f"Colorized Frame {frame_count}")
 
         # Write colorized frame to output
         out.write(colorized)