add feature in video process

app.py

@@ -134,7 +134,7 @@ if file_name is not None:
         frame_interval = frame_rate  # Process one frame per second
 
         frame_emotions = []
-
+        frame_emotions_refined = []
         for frame_idx in range(0, frame_count, frame_interval):
             video.set(cv2.CAP_PROP_POS_FRAMES, frame_idx)
             ret, frame = video.read()
@@ -160,8 +160,14 @@ if file_name is not None:
                 output = pipe_emotions(face)
                 frame_emotion.append(output[0]['label'])
             frame_emotions.append(frame_emotion)
+            
+            frame_emotion_refined = []
+            for face in persons_image_list:
+                output = pipe_emotions_refined(face)
+                frame_emotion_refined.append(output[0]['label'])
+            frame_emotions_refined.append(frame_emotion_refined)
 
-        # Plot emotions over frames
+        # Plot number of persons detected over frames
         fig, ax = plt.subplots(figsize=(10, 5))
         ax.plot(range(len(frame_emotions)), [len(emotions) for emotions in frame_emotions], label='Number of Persons Detected')
         ax.set_xlabel('Frame')
@@ -171,5 +177,17 @@ if file_name is not None:
 
         st.pyplot(fig)
 
+        # Plot emotions over frames, using the same frame index
+        fig, ax = plt.subplots(figsize=(10, 5))
+        for emotion in frame_emotions_refined[0]:
+            ax.bar(range(len(frame_emotions_refined)), [emotion_counts[emotion] for emotion_counts in frame_emotions_refined], label=emotion)
+        ax.set_xlabel('Frame')
+        ax.set_ylabel('Emotion Count')
+        ax.set_title('Emotion Distribution Over Frames')
+        ax.legend()
+
+        st.pyplot(fig)
+
+
     else:
         st.error("Unsupported file type. Please upload an image or a video.")