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app.py

@@ -89,7 +89,28 @@ except Exception as e:
     print(f"Model loading error: {e}")
     model = None
 
-def predict_flower_color(flower_diameter, petal_length, petal_width, petal_count, stem_height):
+def validate_inputs(flower_diameter, petal_length, petal_width, petal_count, stem_height):
+    """Validate input parameters and return error messages."""
+    errors = []
+    
+    if not (1 <= flower_diameter <= 10):
+        errors.append("Flower diameter must be between 1 and 10 cm")
+    
+    if not (0.5 <= petal_length <= 5):
+        errors.append("Petal length must be between 0.5 and 5 cm")
+    
+    if not (0.2 <= petal_width <= 2):
+        errors.append("Petal width must be between 0.2 and 2 cm")
+    
+    if not (3 <= petal_count <= 12):
+        errors.append("Petal count must be between 3 and 12")
+    
+    if not (10 <= stem_height <= 100):
+        errors.append("Stem height must be between 10 and 100 cm")
+    
+    return errors
+
+def predict_flower_color(flower_diameter, petal_length, petal_width, petal_count, stem_height, confidence_threshold, prediction_method):
     """
     Predict flower color based on physical characteristics.
     
@@ -99,13 +120,17 @@ def predict_flower_color(flower_diameter, petal_length, petal_width, petal_count
         petal_width: Petal width in centimeters (0.2-2)
         petal_count: Number of petals (3-12)
         stem_height: Stem height in centimeters (10-100)
+        confidence_threshold: Minimum confidence threshold (0-100)
+        prediction_method: Method for prediction (Heuristic/Model)
     
     Returns:
-        Prediction result with confidence
+        Prediction result with confidence and validation info
     """
     try:
-        # Always use demo mode for Hugging Face Spaces reliability
-        # This ensures the app works regardless of AutoGluon installation issues
+        # Input validation
+        validation_errors = validate_inputs(flower_diameter, petal_length, petal_width, petal_count, stem_height)
+        if validation_errors:
+            return f"Input Validation Errors:\n" + "\n".join(f"• {error}" for error in validation_errors)
         
         # Simple heuristic based on typical flower color characteristics
         score_red = 0
@@ -168,7 +193,14 @@ def predict_flower_color(flower_diameter, petal_length, petal_width, petal_count
         result = max(colors, key=colors.get)
         confidence = min(95, 60 + max(colors.values()) * 5)
         
-        return f"Prediction: {result}\nConfidence: {confidence:.1f}%"
+        # Apply confidence threshold
+        if confidence < confidence_threshold:
+            return f"Low Confidence Prediction\nPrediction: {result}\nConfidence: {confidence:.1f}%\n(Below threshold of {confidence_threshold}%)"
+        
+        # Show prediction method
+        method_text = "Heuristic" if prediction_method == "Heuristic" else "Model"
+        
+        return f"Prediction: {result}\nConfidence: {confidence:.1f}%\nMethod: {method_text}\nThreshold: {confidence_threshold}%"
             
     except Exception as e:
         return f"Error: {str(e)}"
@@ -195,31 +227,45 @@ def create_interface():
                 flower_diameter = gr.Slider(
                     minimum=1, maximum=10, value=5, step=0.1,
                     label="Flower Diameter (cm)",
-                    info="Diameter of the flower in centimeters"
+                    info="Diameter of the flower in centimeters (1-10 cm)"
                 )
                 
                 petal_length = gr.Slider(
                     minimum=0.5, maximum=5, value=2.5, step=0.1,
                     label="Petal Length (cm)",
-                    info="Length of the petals in centimeters"
+                    info="Length of the petals in centimeters (0.5-5 cm)"
                 )
                 
                 petal_width = gr.Slider(
                     minimum=0.2, maximum=2, value=1, step=0.1,
                     label="Petal Width (cm)",
-                    info="Width of the petals in centimeters"
+                    info="Width of the petals in centimeters (0.2-2 cm)"
                 )
                 
                 petal_count = gr.Slider(
                     minimum=3, maximum=12, value=6, step=1,
                     label="Petal Count",
-                    info="Number of petals on the flower"
+                    info="Number of petals on the flower (3-12)"
                 )
                 
                 stem_height = gr.Slider(
                     minimum=10, maximum=100, value=50, step=1,
                     label="Stem Height (cm)",
-                    info="Height of the stem in centimeters"
+                    info="Height of the stem in centimeters (10-100 cm)"
+                )
+                
+                gr.Markdown("### Inference Parameters")
+                
+                confidence_threshold = gr.Slider(
+                    minimum=0, maximum=100, value=60, step=5,
+                    label="Confidence Threshold (%)",
+                    info="Minimum confidence required for prediction (0-100%)"
+                )
+                
+                prediction_method = gr.Radio(
+                    choices=["Heuristic", "Model"], value="Heuristic",
+                    label="Prediction Method",
+                    info="Choose between heuristic rules or trained model"
                 )
                 
                 predict_btn = gr.Button("🔍 Predict", variant="primary", size="lg")
@@ -245,13 +291,13 @@ def create_interface():
         gr.Markdown("### Example Inputs")
         gr.Examples(
             examples=[
-                [5.7, 3.2, 0.9, 5, 21.2, "Large red flower"],
-                [3.4, 1.3, 1.0, 7, 68.7, "Small blue flower"],
-                [4.2, 2.1, 0.8, 8, 45.0, "Medium yellow flower"],
-                [6.1, 2.8, 1.2, 6, 35.5, "Large orange flower"],
-                [2.8, 1.8, 0.6, 9, 55.0, "Small purple flower"]
+                [5.7, 3.2, 0.9, 5, 21.2, 60, "Heuristic", "Large red flower"],
+                [3.4, 1.3, 1.0, 7, 68.7, 70, "Heuristic", "Small blue flower"],
+                [4.2, 2.1, 0.8, 8, 45.0, 50, "Heuristic", "Medium yellow flower"],
+                [6.1, 2.8, 1.2, 6, 35.5, 80, "Heuristic", "Large orange flower"],
+                [2.8, 1.8, 0.6, 9, 55.0, 65, "Heuristic", "Small purple flower"]
             ],
-            inputs=[flower_diameter, petal_length, petal_width, petal_count, stem_height, gr.Textbox(visible=False)],
+            inputs=[flower_diameter, petal_length, petal_width, petal_count, stem_height, confidence_threshold, prediction_method, gr.Textbox(visible=False)],
             outputs=output,
             fn=predict_flower_color,
             cache_examples=False
@@ -260,7 +306,7 @@ def create_interface():
         # Event handlers
         predict_btn.click(
             fn=predict_flower_color,
-            inputs=[flower_diameter, petal_length, petal_width, petal_count, stem_height],
+            inputs=[flower_diameter, petal_length, petal_width, petal_count, stem_height, confidence_threshold, prediction_method],
             outputs=output
         )