Update app.py

app.py

@@ -4,8 +4,8 @@ from PIL import Image
 import numpy as np
 import cv2
 
-# Load the YOLOv8 model (you can adjust the model path if needed)
-model = YOLO('yolov8n.pt')  # Ensure this path points to the correct YOLO model file
+# Load the YOLOv8 model (ensure this path is correct)
+model = YOLO('yolov8n.pt')
 
 def identify_disease(image):
     # Convert the image to RGB if it's not
@@ -14,9 +14,18 @@ def identify_disease(image):
     
     # Perform inference
     results = model(image)
+    predictions = results[0]
+    
+    # Check if there are any detections
+    if len(predictions.boxes) == 0:
+        # No detections, return the image with a message
+        annotated_image = np.array(image)
+        cv2.putText(annotated_image, "No disease detected", (10, 30), 
+                    cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
+        annotated_image = Image.fromarray(annotated_image)
+        return annotated_image, [{"Disease": "None", "Confidence": "N/A"}]
     
     # Extract predictions
-    predictions = results[0]
     boxes = predictions.boxes
     labels = boxes.cls.cpu().numpy()
     scores = boxes.conf.cpu().numpy()