Update app.py

app.py

@@ -67,19 +67,25 @@ def generate_gemini_response(disease_list, user_context="", conversation_history
         return f"Error connecting to Gemini API: {str(e)}"
 
 # Performing inference using YOLO
-def inference(image):
-    """Detect crop diseases in the given image."""
-    results = yolo_model(image, conf=0.4)
+def inference(image, conf_threshold=0.5):
+    """Detect crop diseases in the given image with confidence filtering."""
+    results = yolo_model(image, conf=0.4)  # Adjusted confidence threshold for detection
     infer = np.zeros(image.shape, dtype=np.uint8)
     detected_classes = []
     class_names = {}
+    confidence_scores = []
 
     for r in results:
         infer = r.plot()
         class_names = r.names
-        detected_classes = r.boxes.cls.tolist()
+        for i, cls in enumerate(r.boxes.cls.tolist()):
+            confidence = r.boxes.conf[i].item()  # Get confidence score
+            if confidence >= conf_threshold:  # Only consider high-confidence detections
+                detected_classes.append(cls)
+                confidence_scores.append(confidence)
+
+    return infer, detected_classes, class_names, confidence_scores
 
-    return infer, detected_classes, class_names
 
 # Converting text to chosen language speech
 def text_to_speech(text, language="en"):
@@ -171,8 +177,18 @@ if uploaded_file:
     st.image(processed_image, caption="🔍 Detected Diseases", use_column_width=True)
 
     if detected_classes:
-        detected_disease_names = [class_names[cls] for cls in detected_classes]
-        st.write(f"✅ **Detected Diseases:** {', '.join(detected_disease_names)}")
+    # Convert detected class indexes to names
+        detected_disease_names = [
+            f"{class_names[cls]} ({confidence_scores[i]:.2f})"
+            for i, cls in enumerate(detected_classes)
+    ]
+
+    # Show only the most confident detections
+    if detected_disease_names:
+        st.write(f"✅ **High Confidence Diseases Detected:** {', '.join(detected_disease_names)}")
+    else:
+        st.write("✅ No high-confidence diseases detected.")
+
 
         # AI-generated diagnosis from Gemini
         st.subheader("📋 AI Diagnosis")