Update app.py

app.py

@@ -328,6 +328,7 @@ async def predict_tomato(file: UploadFile = File(...)):
             "message": "Please upload a clear image of a PLANT leaf."
         })
 
+        # --- SMART BACKGROUND REMOVAL ---
         # --- SMART BACKGROUND REMOVAL ---
         image_array = np.array(image).astype(np.float32)
 
@@ -335,23 +336,27 @@ async def predict_tomato(file: UploadFile = File(...)):
         G = image_array[:, :, 1]
         B = image_array[:, :, 2]
 
-        # Brightness: pixel must be very bright overall
+        # Brightness: must be very bright (tightened from 200 → 220)
         brightness = (R + G + B) / 3.0
-        is_bright = brightness > 200
+        is_bright = brightness > 220
 
-        # Saturation: true background has no color — R, G, B are all similar
-        # A green leaf pixel will have G much higher than R and B
+        # Saturation: tightened from 30 → 15 to avoid removing leaf tissue
         channel_range = (
             np.maximum(np.maximum(R, G), B) -
             np.minimum(np.minimum(R, G), B)
         )
-        is_unsaturated = channel_range < 30  # low color variation = background
+        is_unsaturated = channel_range < 15
+
+        # Extra guard: true background has no dominant green channel
+        # Leaf pixels always have G notably higher than R and B
+        is_not_green = (G - R) < 15
 
-        # Only replace pixels that are BOTH bright AND colorless
-        background_mask = is_bright & is_unsaturated
+        # All three must be true to be considered background
+        background_mask = is_bright & is_unsaturated & is_not_green
         image_array[background_mask] = [0, 0, 0]
 
         image = Image.fromarray(image_array.astype(np.uint8))
+
         
         # 1. Standard Resize
         image = image.resize((224, 224))