Update app.py

app.py

@@ -1,7 +1,7 @@
 """
 File: app.py
 Author: Dr. Gordon Wright
-Description: Description: Main application file for Facial_Expression_Recognition.
+Description: Main application file for Facial_Expression_Recognition.
              The file defines the Gradio interface, sets up the main blocks,
              and includes event handlers for various components.
 License: MIT License
@@ -14,7 +14,6 @@ from app.description import DESCRIPTION_STATIC, DESCRIPTION_DYNAMIC
 from app.authors import AUTHORS
 from app.app_utils import preprocess_image_and_predict, preprocess_video_and_predict
 
-
 def clear_static_info():
     return (
         gr.Image(value=None, type="pil"),
@@ -33,35 +32,36 @@ def clear_dynamic_info():
     )
 
 with gr.Blocks(css="app.css") as demo:
+    # Header with Observatory logo
+    with gr.Row(elem_classes="header-container"):
+        with gr.Column():
+            gr.Image("images/LMLOBS.png", show_label=False, container=False, elem_classes="header-logo")
+    
+    gr.Markdown("# Facial Expression Recognition")
+    gr.Markdown("### LittleMonkeyLab | Goldsmiths Observatory")
+    
     with gr.Tab("Static Faces"):
         gr.Markdown(value=DESCRIPTION_STATIC)
         with gr.Row():
             with gr.Column(scale=2, elem_classes="dl1"):
                 input_image = gr.Image(label="Original image", type="pil")
                 with gr.Row():
-                    clear_btn = gr.Button(
-                        value="Clear", interactive=True, scale=1, elem_classes="clear"
-                    )
-                    submit = gr.Button(
-                        value="Submit", interactive=True, scale=1, elem_classes="submit"
-                    )
+                    clear_btn = gr.Button(value="Clear", interactive=True, scale=1, elem_classes="clear")
+                    submit = gr.Button(value="Submit", interactive=True, scale=1, elem_classes="submit")
             with gr.Column(scale=1, elem_classes="dl4"):
                 with gr.Row():
                     output_image = gr.Image(label="Face", scale=1, elem_classes="dl5")
                     output_heatmap = gr.Image(label="Heatmap", scale=1, elem_classes="dl2")
                 output_label = gr.Label(num_top_classes=3, scale=1, elem_classes="dl3")
-        gr.Examples(
-            [
-                "images/Anger.png",
-                "images/contempt.png",
-                "images/Disgust.png",
-                "images/Happy.png",
-                "images/Fear.png",
-                "images/Sad.png",
-                "images/Surprise.png",
-            ],
-            [input_image],
-        )
+        gr.Examples([
+            "images/Anger.png",
+            "images/contempt.png",
+            "images/Disgust.png",
+            "images/Happy.png",
+            "images/Fear.png",
+            "images/Sad.png",
+            "images/Surprise.png",
+        ], [input_image])
     
     with gr.Tab("Dynamic Faces"):
         gr.Markdown(value=DESCRIPTION_DYNAMIC)
@@ -69,28 +69,25 @@ with gr.Blocks(css="app.css") as demo:
             with gr.Column(scale=2):
                 input_video = gr.Video(elem_classes="video1")
                 with gr.Row():
-                    clear_btn_dynamic = gr.Button(
-                        value="Clear", interactive=True, scale=1
-                    )
-                    submit_dynamic = gr.Button(
-                        value="Submit", interactive=True, scale=1, elem_classes="submit"
-                    )
+                    clear_btn_dynamic = gr.Button(value="Clear", interactive=True, scale=1)
+                    submit_dynamic = gr.Button(value="Submit", interactive=True, scale=1, elem_classes="submit")
             with gr.Column(scale=2, elem_classes="dl4"):
                 with gr.Row():
                     output_video = gr.Video(label="Original video", scale=1, elem_classes="video2")
                     output_face = gr.Video(label="Pre-processed video", scale=1, elem_classes="video3")
                     output_heatmaps = gr.Video(label="Heatmaps", scale=1, elem_classes="video4")
                 output_statistics = gr.Plot(label="Statistics of emotions", elem_classes="stat")
-        gr.Examples(
-            ["videos/BillClinton.mp4"
-            ],
-            [input_video],
-        )
-
+        gr.Examples(["videos/BillClinton.mp4"], [input_video])
     
     with gr.Tab("References"):
         gr.Markdown(value=AUTHORS)
-
+    
+    # Footer with branding
+    with gr.Row(elem_classes="center-content"):
+        with gr.Column():
+            gr.Image("images/LMLLOGO.png", show_label=False, container=False, elem_classes="footer-logo")
+            gr.Markdown("© LittleMonkeyLab | Goldsmiths Observatory", elem_classes="footer-text")
+    
     submit.click(
         fn=preprocess_image_and_predict,
         inputs=[input_image],
@@ -103,7 +100,7 @@ with gr.Blocks(css="app.css") as demo:
         outputs=[input_image, output_image, output_heatmap, output_label],
         queue=True,
     )
-
+    
     submit_dynamic.click(
         fn=preprocess_video_and_predict,
         inputs=input_video,