Update app.py

app.py

@@ -1,4 +1,18 @@
 import gradio as gr
+
+model = Sequential([
+  layers.experimental.preprocessing.Rescaling(1./255, input_shape=(img_height, img_width, 3)),
+  layers.Conv2D(16, 3, padding='same', activation='relu'),
+  layers.MaxPooling2D(),
+  layers.Conv2D(32, 3, padding='same', activation='relu'),
+  layers.MaxPooling2D(),
+  layers.Conv2D(64, 3, padding='same', activation='relu'),
+  layers.MaxPooling2D(),
+  layers.Flatten(),
+  layers.Dense(128, activation='relu'),
+  layers.Dense(num_classes,activation='softmax')
+])
+
 def predict_image(img):
   img_2d=img.reshape(-1,180,180,3)
   prediction=model.predict(img_2d)[0]