Update app.py

app.py

@@ -78,8 +78,9 @@ def process_frame(frame, selected_model):
             ax.set_title('Top 5 Emotions')
             ax.invert_yaxis()  # Invert y-axis to have the highest probability at the top
             
-            # Adjust x-axis labels
-            ax.set_xticklabels(ax.get_xticks(), rotation=0, ha='center')
+            # Adjust x-axis labels to show only 3 decimal places
+            ax.set_xticks(ax.get_xticks())
+            ax.set_xticklabels([f'{x:.3f}' for x in ax.get_xticks()], rotation=0, ha='center')
             
             # Ensure all labels are fully visible
             plt.tight_layout()
@@ -126,15 +127,15 @@ with gr.Blocks() as app:
                 model_dropdown_video = gr.Dropdown(choices=["ViT-B/32", "ViT-B/16", "ViT-L/14"], label="Model", value="ViT-B/16")
                 gr.Markdown("Upload a video to detect faces and recognize emotions.")
                 video_input = gr.Video()
-                frame_slider = gr.Slider(minimum=0, maximum=100, step=1, label="Frame Index", value=0)
                 output_frame = gr.Image(label="Processed Frame")
+                frame_slider = gr.Slider(minimum=0, maximum=100, step=1, label="Frame Index", value=0)
                 output_graph = gr.Image(label="Results Graph")
 
                 def update_slider_and_process(video):
                     cap = cv2.VideoCapture(video)
                     total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
                     cap.release()
-                    processed_frame, graph = process_video(video, "ViT-L/14", 0)
+                    processed_frame, graph = process_video(video, "ViT-B/16", 0)
                     return gr.update(maximum=total_frames-1), processed_frame, graph
 
                 def update_frame(video, model, frame_idx):