Update app.py

app.py

@@ -405,9 +405,12 @@ if recipe_submit and uploaded_image:
     with col1:
         predictions = classifyImage(input_image)
         print("Predictions: ", predictions)
+
+        # graph variables
         fpredictions = ""
         class_names = []
         confidences = []
+        MIN_CONFIDENCE = 0.05 
     
         # Show the top predictions with percentages
         st.write("Top Predictions:")
@@ -417,7 +420,8 @@ if recipe_submit and uploaded_image:
             class_name = class_name.title()
             st.markdown(f"*{class_name}*: {confidence:.2f}%")
             class_names.append(class_name)
-            confidences.append(confidence)
+            confidences.append(confidence if confidence > MIN_CONFIDENCE else MIN_CONFIDENCE) # minimum length of the bar (5%), 
+
         print(fpredictions)
 
         #reversing them so graph displays highest predictions at the top
@@ -432,7 +436,6 @@ if recipe_submit and uploaded_image:
         bars = ax.barh(class_names, confidences, color=cmap(norm(confidences)))
 
         fig.patch.set_alpha(0.2)  # Transparent background
-        fig.patch.set_boxstyle("round,pad=0.1,rounding_size=15") # rounded edges
         
         # Add labels inside the bars, aligned to the right
         for bar in bars: