Update main.py

Brain tumour type identification/main.py

@@ -15,16 +15,21 @@ def load_brain_tumor_type_model():
 
 	model = Sequential()
 
-	model.add(Conv2D(256, (3, 3), input_shape=(50, 50, 1)))
+	model.add(Conv2D(512, (5, 5), input_shape=(50, 50, 1)))
 	model.add(Activation('relu'))
-	model.add(MaxPooling2D(pool_size=(2,2)))
+	model.add(MaxPooling2D(pool_size=(2, 2)))
 	#The first CNN layer followed by Relu and MaxPooling layers
 
-	model.add(Conv2D(128, (3, 3)))
+	model.add(Conv2D(256, (3, 3)))
 	model.add(Activation('relu'))
-	model.add(MaxPooling2D(pool_size=(2,2)))
+	model.add(MaxPooling2D(pool_size=(2, 2)))
 	#The second convolution layer followed by Relu and MaxPooling layers
 
+	model.add(Conv2D(128, (3, 3)))
+	model.add(Activation('relu'))
+	model.add(MaxPooling2D(pool_size=(2, 2)))
+	#The third convolution layer followed by Relu and MaxPooling layers
+
 	model.add(Flatten())
 	model.add(Dropout(0.5))
 	#Flatten layer to stack the output convolutions from second convolution layer