Update model.py

model.py

@@ -43,7 +43,7 @@ def bone_net(img):
 def brain_net(img):
     lt = ['pituitary', 'notumor', 'meningioma', 'glioma']
     img = cv2.resize(img,(224,224))
-    model = tf.keras.models.load_model("Models/model_brain_tumur.h5",compile=False)
+    model = tf.keras.models.load_model("Models/brain.h5",compile=False)
     result = model.predict(np.array([img]))
     ans = np.argmax(result)
     return lt[ans]
@@ -59,7 +59,7 @@ def chest_net(img):
 def Eye_net(img):
     lt = ['glaucoma', 'normal', 'diabetic_retinopathy', 'cataract']
     img = cv2.resize(img,(224,224))
-    model = tf.keras.models.load_model("Models/Eye_diseases.h5",compile=False)
+    model = tf.keras.models.load_model("Models/eye.h5",compile=False)
     result = model.predict(np.array([img]))
     ans = np.argmax(result)
     return lt[ans]
@@ -67,7 +67,7 @@ def Eye_net(img):
 def kidney_net(img):
     lt = ['Cyst', 'Tumor', 'Stone', 'Normal']
     img = cv2.resize(img,(224,224))
-    model = tf.keras.models.load_model("Models/kidney_stone.h5",compile=False)
+    model = tf.keras.models.load_model("Models/kidney.h5",compile=False)
     result = model.predict(np.array([img]))
     ans = np.argmax(result)
     return lt[ans]