Update app.py

app.py

@@ -16,8 +16,6 @@ import tempfile
 import base64
 import plotly.graph_objects as go
 from plotly.subplots import make_subplots
-import matplotlib.pyplot as plt
-from matplotlib import cm
 
 # Load the emotion prediction model
 def load_emotion_model(model_path):
@@ -191,18 +189,21 @@ def generate_image(emotion_prediction, transcribed_text):
 # Function to create a visualization with both the equirectangular image and a 3D sphere
 def create_texture_and_sphere_preview(image):
     try:
+        # Convert PIL image to numpy array for display
+        img_array = np.array(image)
+        
         # Create a subplot with the equirectangular image and a 3D sphere
         fig = make_subplots(
             rows=1, cols=2,
             subplot_titles=("Equirectangular Texture", "3D Sphere Preview"),
-            specs=[[{"type": "image"}, {"type": "scatter3d"}]]
+            specs=[[{"type": "image"}, {"type": "scatter3d"}]],
+            horizontal_spacing=0.1
         )
         
-        # Add the equirectangular image
-        img_array = np.array(image)
+        # Add the equirectangular image to the first subplot
         fig.add_trace(go.Image(z=img_array), row=1, col=1)
         
-        # Create a 3D sphere with a representative color pattern
+        # Create a 3D sphere for the second subplot
         # Since we can't directly apply the texture, we'll create a colored sphere
         u = np.linspace(0, 2 * np.pi, 50)
         v = np.linspace(0, np.pi, 25)
@@ -230,6 +231,10 @@ def create_texture_and_sphere_preview(image):
             showlegend=False
         )
         
+        # Update axes for the image subplot
+        fig.update_xaxes(visible=False, row=1, col=1)
+        fig.update_yaxes(visible=False, row=1, col=1)
+        
         # Update 3D scene settings
         fig.update_scenes(
             aspectmode='data',
@@ -242,78 +247,6 @@ def create_texture_and_sphere_preview(image):
         print("Error creating texture and sphere preview:", e)
         return go.Figure()
 
-# Function to create a detailed explanation figure
-def create_detailed_preview(image):
-    try:
-        # Create a more detailed visualization
-        fig = make_subplots(
-            rows=2, cols=2,
-            subplot_titles=(
-                "Equirectangular Texture", 
-                "3D Sphere Preview", 
-                "Texture Mapping Diagram",
-                "How It Works"
-            ),
-            specs=[
-                [{"type": "image"}, {"type": "scatter3d"}],
-                [{"type": "xy"}, {"type": "xy"}]
-            ]
-        )
-        
-        # Add the equirectangular image
-        img_array = np.array(image)
-        fig.add_trace(go.Image(z=img_array), row=1, col=1)
-        
-        # Create a 3D sphere
-        u = np.linspace(0, 2 * np.pi, 30)
-        v = np.linspace(0, np.pi, 15)
-        u, v = np.meshgrid(u, v)
-        
-        x = np.sin(v) * np.cos(u)
-        y = np.sin(v) * np.sin(u)
-        z = np.cos(v)
-        
-        fig.add_trace(go.Surface(
-            x=x, y=y, z=z,
-            surfacecolor=z,
-            colorscale='Viridis',
-            showscale=False,
-            opacity=0.8
-        ), row=1, col=2)
-        
-        # Add a diagram showing how equirectangular mapping works
-        x_diagram = [0, 1, 1, 0, 0]
-        y_diagram = [0, 0, 1, 1, 0]
-        fig.add_trace(go.Scatter(x=x_diagram, y=y_diagram, fill="toself"), row=2, col=1)
-        
-        # Add text explanation
-        fig.add_annotation(
-            x=0.5, y=0.5,
-            xref="x domain", yref="y domain",
-            text="Equirectangular images wrap around spheres to create 360° environments",
-            showarrow=False,
-            row=2, col=2
-        )
-        
-        # Update layout
-        fig.update_layout(
-            height=600,
-            title_text="360° Environment Creation Process",
-            showlegend=False
-        )
-        
-        # Update axes for diagram
-        fig.update_xaxes(visible=False, row=2, col=1)
-        fig.update_yaxes(visible=False, row=2, col=1)
-        fig.update_xaxes(visible=False, row=2, col=2)
-        fig.update_yaxes(visible=False, row=2, col=2)
-        
-        return fig
-        
-    except Exception as e:
-        print("Error creating detailed preview:", e)
-        return go.Figure()
-
 # Function to get predictions
 def get_predictions(audio_input):
     emotion_prediction = predict_emotion_from_audio(audio_input)