Update app.py

app.py

@@ -482,22 +482,11 @@ def process_hdf5_file(uploaded_file, percentage):
         sys.stdout = sys.__stdout__  # Reset print statements
 
 ######################## Define the Gradio interface ###############################
-detect_theme_js = """
-<script>
-    function detectTheme() {
-        const isDarkMode = window.matchMedia && window.matchMedia('(prefers-color-scheme: dark)').matches;
-        return isDarkMode ? 'dark' : 'light';
-    }
-
-    window.onload = function() {
-        const theme = detectTheme();
-        const themeTextbox = document.getElementById('theme_output');
-        if (themeTextbox) {
-            themeTextbox.value = theme; 
-            themeTextbox.dispatchEvent(new Event('input'));  // Fire an input event to notify Gradio of the change
-        }
-    };
-</script>
+js_code = """
+() => {
+  const isDarkMode = window.matchMedia && window.matchMedia('(prefers-color-scheme: dark)').matches;
+  return isDarkMode ? 'dark' : 'light';
+}
 """
 
 with gr.Blocks(css="""
@@ -556,8 +545,6 @@ with gr.Blocks(css="""
         <a target="_blank" href="https://huggingface.co/wi-lab/lwm">https://huggingface.co/wi-lab/lwm</a>
     </div>
     """)
-
-    theme_output = gr.Textbox(label="Theme", value="light", visible=False)
     
     # Tab for Beam Prediction Task
     with gr.Tab("Beam Prediction Task"):
@@ -590,6 +577,12 @@ with gr.Blocks(css="""
             raw_img_bp = gr.Image(label="Raw Channels", type="pil", width=300, height=500)
             embeddings_img_bp = gr.Image(label="Embeddings", type="pil", width=300, height=500)
 
+        # Use the theme detection from JavaScript
+        theme_output = gr.Textbox(label="Theme", visible=False)
+    
+        # Run the JS code to detect the theme and set it to theme_output
+        theme_output.change(fn=None, inputs=[], outputs=[theme_output], _js=js_code)
+    
         # Update the confusion matrices whenever sliders change
         data_percentage_slider.change(fn=beam_prediction_task, inputs=[data_percentage_slider, task_complexity_dropdown, theme_output], outputs=[raw_img_bp, embeddings_img_bp])
         task_complexity_dropdown.change(fn=beam_prediction_task, inputs=[data_percentage_slider, task_complexity_dropdown, theme_output], outputs=[raw_img_bp, embeddings_img_bp])
@@ -614,7 +607,7 @@ with gr.Blocks(css="""
                 <li><b>📂 Dataset</b>: Use the default dataset (a combination of six scenarios from the DeepMIMO dataset) or upload your own dataset in <b>h5py</b> format.</li>
                 <li><b>💡 Custom Dataset Requirements:</b>
                   <ul>
-                    <li>🛠️ <b>channels</b> array: Shape (N,32,32)</li>
+                    <li>🛢 <b>channels</b> array: Shape (N,32,32)</li>
                     <li>🏷️ <b>labels</b> array: Binary LoS/NLoS values (1/0)</li>
                   </ul>
                 </li>