Update app.py

app.py

@@ -19,6 +19,11 @@ if not os.path.exists(save_dir):
     print("📁 Folder created:", save_dir)
 os.makedirs(save_dir, exist_ok=True)
 
+
+# Placeholder image for invalid uploads
+invalid_img = Image.new("RGB", (224, 224), color=(200, 200, 200))
+
+
 # Load model
 model = models.resnet50(weights=None)
 model.fc = torch.nn.Linear(model.fc.in_features, 2)
@@ -38,13 +43,26 @@ transform = transforms.Compose([
                          [0.229, 0.224, 0.225])
 ])
 
-# Predict and save
+def looks_like_fundus(image):
+    """
+    Basic heuristic to check if an image is likely a retinal fundus scan.
+    Fundus images tend to have a bright circular region (retina)
+    with a darker background.
+    """
+    img = np.array(image.convert("L").resize((224, 224)))
+    thresh = img > 40  # bright region
+    white_ratio = np.sum(thresh) / img.size
+
+    # Fundus images usually occupy ~40–75% of the area
+    return 0.40 < white_ratio < 0.75
+
 def predict_retinopathy(image):
-    # Validate image
-     if not looks_like_fundus(image):
+    # Validate image first
+    if not looks_like_fundus(image):
         return (
             invalid_img,
-            "❌ Invalid image detected.\n\nPlease upload a *retinal fundus scan* for accurate Diabetic Retinopathy assessment."
+            "⚠️ The uploaded image does not appear to be a retinal fundus scan.\n\n"
+            "Please upload a valid ophthalmic retinal image for Diabetic Retinopathy assessment."
         )
 
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")