Update app.py

app.py

@@ -14,7 +14,6 @@ import umap
 import pandas as pd
 import matplotlib
 import matplotlib.pyplot as plt
-from matplotlib.ticker import MaxNLocator
 from moviepy.editor import VideoFileClip
 from PIL import Image
 import gradio as gr
@@ -22,7 +21,6 @@ import tempfile
 import shutil
 
 
-
 # Suppress TensorFlow warnings
 os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
 import tensorflow as tf
@@ -119,7 +117,7 @@ def extract_frames(video_path, output_folder, desired_fps, progress_callback=Non
 
         # Report progress
         if progress_callback:
-            progress = min(100, (frame_count / total_frames_to_extract) * 100)  # Ensure it doesn't exceed 100%
+            progress = min(100, (frame_count / total_frames_to_extract) * 100)
             progress_callback(progress, f"Extracting frame")
 
         if frame_count >= total_frames_to_extract:
@@ -485,9 +483,6 @@ def process_video(video_path, num_anomalies, num_components, desired_fps, batch_
         except Exception as e:
             return f"Error generating plots: {str(e)}", None, None, None, None, None, None, None, None, None
 
-        # Get a random face sample
-        face_sample = get_random_face_sample(organized_faces_folder, largest_cluster, output_folder)
-
         progress(1.0, "Preparing results")
         results = f"Top {num_anomalies} anomalies (All Features):\n"
         results += "\n".join([f"{score:.4f} at {timecode}" for score, timecode in
@@ -501,17 +496,19 @@ def process_video(video_path, num_anomalies, num_components, desired_fps, batch_
             results += f"\n\nTop {num_anomalies} {emotion.capitalize()} Scores:\n"
             results += "\n".join([f"{df[emotion].iloc[i]:.4f} at {df['Timecode'].iloc[i]}" for i in top_indices])
 
+        # Get a random face sample
+        face_sample = get_random_face_sample(organized_faces_folder, largest_cluster, output_folder)
+
         return (
-            results,  # Text results to a Textbox
-            face_sample,  # Random face sample image
+            results,
             anomaly_plot_all,
             anomaly_plot_comp,
-            *emotion_plots
+            *emotion_plots,
+            face_sample
         )
 
-    # Gradio interface
-
 
+# Gradio interface
 iface = gr.Interface(
     fn=process_video,
     inputs=[