Update utils.py

utils.py

@@ -6,18 +6,18 @@ import torch.nn as nn
 
 class BrainTumorModel(nn.Module):
     def __init__(self):
-        super(BrainTumorModel, self).__init__()
+        super().__init__()
         self.model = nn.Sequential(
-            nn.Conv2d(3, 16, kernel_size=3, stride=1, padding=1),
+            nn.Conv2d(3, 16, 3, padding=1),
             nn.ReLU(),
             nn.MaxPool2d(2),
-            nn.Conv2d(16, 32, kernel_size=3, stride=1, padding=1),
+            nn.Conv2d(16, 32, 3, padding=1),
             nn.ReLU(),
             nn.MaxPool2d(2),
             nn.Flatten(),
             nn.Linear(32 * 56 * 56, 128),
             nn.ReLU(),
-            nn.Linear(128, 4)  # 4 tumor classes
+            nn.Linear(128, 4)
         )
 
     def forward(self, x):
@@ -25,18 +25,18 @@ class BrainTumorModel(nn.Module):
 
 class GliomaStageModel(nn.Module):
     def __init__(self):
-        super(GliomaStageModel, self).__init__()
+        super().__init__()
         self.model = nn.Sequential(
-            nn.Conv2d(3, 16, kernel_size=3, stride=1, padding=1),
+            nn.Conv2d(3, 16, 3, padding=1),
             nn.ReLU(),
             nn.MaxPool2d(2),
-            nn.Conv2d(16, 32, kernel_size=3, stride=1, padding=1),
+            nn.Conv2d(16, 32, 3, padding=1),
             nn.ReLU(),
             nn.MaxPool2d(2),
             nn.Flatten(),
             nn.Linear(32 * 56 * 56, 128),
             nn.ReLU(),
-            nn.Linear(128, 4)  # 4 glioma stages
+            nn.Linear(128, 4)
         )
 
     def forward(self, x):
@@ -44,7 +44,7 @@ class GliomaStageModel(nn.Module):
 
 def get_precautions_from_gemini(tumor_type: str) -> str:
     db = {
-        "meningioma": "Avoid radiation exposure and get regular check-ups.",
+        "meningioma": "Avoid radiation exposure and get regular check‑ups.",
         "pituitary":   "Monitor hormonal levels and follow medication strictly.",
         "notumor":     "Stay healthy and get annual MRI scans if symptoms appear."
     }