Update app.py

app.py

@@ -118,33 +118,37 @@ def process_image(image, transform_type):
                     (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 
                     0.7, (255, 255, 255), 2)
         
-        # Create analysis plots
-        plt.style.use('seaborn')
+        # Create analysis plots with default style
+        plt.style.use('default')
         fig, axes = plt.subplots(2, 2, figsize=(15, 12))
         fig.suptitle('Blood Cell Analysis Results', fontsize=16, y=0.95)
         
         df = pd.DataFrame(features)
         if not df.empty:
             # Distribution plots
-            df['area'].hist(ax=axes[0,0], bins=20, color='skyblue', edgecolor='black')
+            axes[0,0].hist(df['area'], bins=20, color='skyblue', edgecolor='black')
             axes[0,0].set_title('Cell Size Distribution')
             axes[0,0].set_xlabel('Area (pixels)')
             axes[0,0].set_ylabel('Count')
+            axes[0,0].grid(True, alpha=0.3)
             
-            df['circularity'].hist(ax=axes[0,1], bins=20, color='lightgreen', edgecolor='black')
+            axes[0,1].hist(df['circularity'], bins=20, color='lightgreen', edgecolor='black')
             axes[0,1].set_title('Circularity Distribution')
             axes[0,1].set_xlabel('Circularity')
             axes[0,1].set_ylabel('Count')
+            axes[0,1].grid(True, alpha=0.3)
             
             # Scatter plot
             axes[1,0].scatter(df['area'], df['circularity'], alpha=0.6, c='purple')
             axes[1,0].set_title('Area vs Circularity')
             axes[1,0].set_xlabel('Area')
             axes[1,0].set_ylabel('Circularity')
+            axes[1,0].grid(True, alpha=0.3)
             
             # Box plot
             df.boxplot(column=['area', 'circularity'], ax=axes[1,1])
             axes[1,1].set_title('Feature Distributions')
+            axes[1,1].grid(True, alpha=0.3)
         else:
             for ax in axes.flat:
                 ax.text(0.5, 0.5, 'No cells detected', ha='center', va='center')
@@ -163,6 +167,8 @@ def process_image(image, transform_type):
     
     except Exception as e:
         print(f"Error processing image: {str(e)}")
+        import traceback
+        traceback.print_exc()  # This will print the full error trace
         return None, None, None, None