Update app.py

app.py

@@ -331,16 +331,23 @@ def plot_emotion(df, emotion, num_anomalies, color):
     plt.tight_layout()
     return fig
 
-def get_random_face_sample(organized_faces_folder, largest_cluster):
+import base64
+
+def get_random_face_sample(organized_faces_folder, largest_cluster, output_folder):
     person_folder = os.path.join(organized_faces_folder, f"person_{largest_cluster}")
     face_files = [f for f in os.listdir(person_folder) if f.endswith('.jpg')]
     if face_files:
         random_face = np.random.choice(face_files)
         face_path = os.path.join(person_folder, random_face)
-        return face_path
+        output_path = os.path.join(output_folder, "random_face_sample.jpg")
+        shutil.copy(face_path, output_path)
+        return output_path
     return None
 
 def process_video(video_path, num_anomalies, num_components, desired_fps, batch_size, progress=gr.Progress()):
+    output_folder = "output"
+    os.makedirs(output_folder, exist_ok=True)
+    
     with tempfile.TemporaryDirectory() as temp_dir:
         aligned_faces_folder = os.path.join(temp_dir, 'aligned_faces')
         organized_faces_folder = os.path.join(temp_dir, 'organized_faces')
@@ -396,8 +403,8 @@ def process_video(video_path, num_anomalies, num_components, desired_fps, batch_
             return f"Error generating plots: {str(e)}", None, None, None, None, None, None
 
         # Get a random face sample
-        face_sample = get_random_face_sample(organized_faces_folder, largest_cluster)
-
+        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 
@@ -425,7 +432,7 @@ iface = gr.Interface(
     ],
     outputs=[
         gr.Textbox(label="Anomaly Detection Results"),
-        gr.Image(label="Random Face Sample of Most Frequent Person"),
+        gr.Image(type="filepath", label="Random Face Sample of Most Frequent Person"),
         gr.Plot(label="Anomaly Scores (All Features)"),
         gr.Plot(label="Anomaly Scores (Components Only)"),
         gr.Plot(label="Fear Scores"),