Update app.py

app.py

@@ -107,7 +107,7 @@ data_augmentation = keras.Sequential(
 model = Sequential([
     data_augmentation,
     normalization_layer,
-    layers.Conv2D(32, 3, padding='same', activation='relu'),
+    layers.Conv2D(32, 3, padding='same', activation='relu', input_shape=(img_height, img_width, 3)),
     layers.MaxPooling2D(),
     layers.Conv2D(64, 3, padding='same', activation='relu'),
     layers.MaxPooling2D(),
@@ -126,6 +126,9 @@ model = Sequential([
     layers.Dense(num_classes, activation='softmax')
 ])
 
+# Ensure the input shape is correctly passed
+model.build((None, img_height, img_width, 3))
+
 model.compile(optimizer=keras.optimizers.Adam(learning_rate=0.001),
               loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=False),
               metrics=['accuracy'])