Update app.py

app.py

@@ -35,4 +35,37 @@ validation_set = tf.keras.utils.image_dataset_from_directory(
     interpolation="bilinear",
     follow_links=False,
     crop_to_aspect_ratio=False
-)
+)
+
+model = tf.keras.models.Sequential()
+
+model.add(tf.keras.layers.Conv2D(filters=32,kernel_size=3,padding='same',activation='relu',input_shape=[64,64,3]))
+model.add(tf.keras.layers.Conv2D(filters=32,kernel_size=3,activation='relu'))
+model.add(tf.keras.layers.MaxPool2D(pool_size=2,strides=2))
+
+
+model.add(tf.keras.layers.Dropout(0.25))
+
+
+model.add(tf.keras.layers.Conv2D(filters=64,kernel_size=3,padding='same',activation='relu'))
+model.add(tf.keras.layers.Conv2D(filters=64,kernel_size=3,activation='relu'))
+model.add(tf.keras.layers.MaxPool2D(pool_size=2,strides=2))
+
+
+model.add(tf.keras.layers.Dropout(0.25))
+
+
+model.add(tf.keras.layers.Flatten())
+
+
+model.add(tf.keras.layers.Dense(units=512,activation='relu'))
+
+
+model.add(tf.keras.layers.Dense(units=256,activation='relu'))
+
+
+model.add(tf.keras.layers.Dropout(0.5)) #To avoid overfitting
+
+
+#Output Layer
+model.add(tf.keras.layers.Dense(units=36,activation='softmax'))