Update utils.py

utils.py

@@ -1,4 +1,10 @@
-# Brain Tumor Detection Model
+import torch
+import torch.nn as nn
+
+# ================================
+# 🧠 MODEL CLASSES
+# ================================
+
 class BrainTumorModel(nn.Module):
     def __init__(self):
         super(BrainTumorModel, self).__init__()
@@ -10,15 +16,14 @@ class BrainTumorModel(nn.Module):
             nn.ReLU(),
             nn.MaxPool2d(2),
             nn.Flatten(),
-            nn.Linear(32 * 56 * 56, 128),  # Adjust if image size is different
+            nn.Linear(32 * 56 * 56, 128),
             nn.ReLU(),
-            nn.Linear(128, 4)  # 4 classes
+            nn.Linear(128, 4)  # 4 tumor classes
         )
 
     def forward(self, x):
         return self.model(x)
 
-# Glioma Stage Detection Model
 class GliomaStageModel(nn.Module):
     def __init__(self):
         super(GliomaStageModel, self).__init__()
@@ -39,35 +44,14 @@ class GliomaStageModel(nn.Module):
         return self.model(x)
 
 # ================================
-# 👤 USER INPUT FUNCTION
-# ================================
-
-def get_user_test_data():
-    print("Enter the following details for prediction:")
-
-    gender_input = input("Gender (M/F): ").strip().lower()
-    gender = 0 if gender_input == 'm' else 1  # Male = 0, Female = 1
-
-    age = float(input("Age at Diagnosis: "))
-
-    idh1 = int(input("IDH1 Mutation? (1 for Yes, 0 for No): "))
-    tp53 = int(input("TP53 Mutation? (1 for Yes, 0 for No): "))
-    atrx = int(input("ATRX Mutation? (1 for Yes, 0 for No): "))
-    pten = int(input("PTEN Mutation? (1 for Yes, 0 for No): "))
-    egfr = int(input("EGFR Mutation? (1 for Yes, 0 for No): "))
-    cic = int(input("CIC Mutation? (1 for Yes, 0 for No): "))
-    pik3ca = int(input("PIK3CA Mutation? (1 for Yes, 0 for No): "))
-
-    return [gender, age, idh1, tp53, atrx, pten, egfr, cic, pik3ca]
-
-# ================================
-# 🩺 TUMOR PRECAUTIONS
+# 💡 PRECAUTIONS
 # ================================
 
 def get_precautions_from_gemini(tumor_type):
     precaution_db = {
         "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."
+        "notumor": "Stay healthy and get annual MRI scans if symptoms appear.",
+        "glioma": "Maintain a healthy lifestyle and follow up with neuro-oncologist."
     }
-    return precaution_db.get(tumor_type.lower(), "No specific precautions found.")
+    return precaution_db.get(tumor_type.lower(), "No specific precautions found.")