Update app.py

app.py

@@ -41,19 +41,29 @@ def get_model():
 # -----------------------
 def predict(img):
     model = get_model()
+    
+    # Save original size
+    orig_size = img.size  # (width, height)
+    
+    # Resize image for model
     img_gray = img.convert("L").resize((224, 224))
     x = np.expand_dims(np.expand_dims(np.array(img_gray)/255.0, -1), 0)
     
+    # Predict mask
     pred = model.predict(x)[0]
-    
-    tumor_present = pred.max() > 0.5
+    tumor_present = pred.max() > 0.7
     
     if tumor_present:
-        mask = (pred > 0.5).astype(np.uint8) * 255
-        mask_img = Image.fromarray(mask.squeeze()).convert("L")  # single channel for mask
+        mask = (pred > 0.7).astype(np.uint8) * 255
+        mask_img = Image.fromarray(mask.squeeze()).convert("L")
+        
+        # Resize mask back to original image size
+        mask_img = mask_img.resize(orig_size)
+        
+        # Create red overlay
+        red_overlay = Image.new("RGB", orig_size, (255, 0, 0))
         overlay = img.convert("RGB")
-        red_overlay = Image.new("RGB", mask_img.size, (255,0,0))
-        overlay.paste(red_overlay, (0,0), mask_img)
+        overlay.paste(red_overlay, (0, 0), mask_img)
         return "Tumor Detected", overlay
     else:
         return "No Tumor Detected", None