Update app.py

app.py

@@ -8,7 +8,10 @@ import numpy as np
 model = load_model('race_prediction_model.h5')
 
 # Define the categories based on your model's output
-categories = ['Black', 'White', 'Indian', 'Southeast Asian', 'Latino Hispanic', 'East Asian', 'Middle Eastern']  # Update with actual categories
+categories = [
+    'Black', 'Indian', 'Southeast Asian', 
+    'East Asian', 'White', 'Middle Eastern', 'Latino_Hispanic'
+]  # Replace with your actual categories
 
 # Define the function to classify images
 def classify_image(img):
@@ -18,7 +21,6 @@ def classify_image(img):
     img_array /= 255.0
 
     predictions = model.predict(img_array)
-    predicted_class = categories[np.argmax(predictions)]
     return {category: float(pred) for category, pred in zip(categories, predictions[0])}
 
 # Define the Gradio components
@@ -26,34 +28,15 @@ image = gr.Image(type='pil', label='Upload an Image')
 label = gr.Label(label="Predictions")
 examples = ['example1.jpeg', 'example2.jpeg', 'example3.jpeg']  # Replace with your example images
 
-# Define a theme selector
-theme_selector = gr.Dropdown(choices=['default', 'dark', 'huggingface', 'compact'], label="Choose Theme", default='default')
-
-# Function to create and launch the Gradio interface
-def create_interface(theme):
-    return gr.Interface(
-        fn=classify_image, 
-        inputs=image, 
-        outputs=label, 
-        title="Face to Race", 
-        description="Upload an image to classify it based on the trained model.",
-        examples=examples,
-        theme=theme
-    )
-
-# Create the initial interface
-intf = create_interface('default')
-
-# Define a callback to update the theme
-def update_theme(theme):
-    global intf
-    intf.close()  # Close the current interface
-    intf = create_interface(theme)  # Create a new interface with the selected theme
-    intf.launch(share=True, inline=False)  # Launch the new interface
-
-# Launch the initial interface
-intf.launch(share=True, inline=False)
-
-# Add a separate interface for theme selection
-theme_intf = gr.Interface(fn=update_theme, inputs=theme_selector, outputs=None, live=True)
-theme_intf.launch(share=True, inline=False)
+# Define the Gradio interface
+intf = gr.Interface(
+    fn=classify_image, 
+    inputs=image, 
+    outputs=label, 
+    title="Face to Race", 
+    description="Upload an image to classify it based on the trained model.",
+    examples=examples
+)
+
+# Launch the interface
+intf.launch(share=True, inline=False)