Fix quickstart code (keras-team#987)

* Fix quickstart code

* Fix quickstart to actually run

templates/keras_cv/index.md

@@ -31,21 +31,36 @@ Create a preprocessing pipeline:
 
 ```python
 import keras_cv
+import tensorflow as tf
 from tensorflow import keras
-
-preprocessing_model = keras.Sequential([
-    keras_cv.layers.RandAugment(value_range=(0, 255))
+import tensorflow_datasets as tfds
+
+preprocessing_layers = [
+    keras_cv.layers.RandomResizedCrop(
+      target_size=(224, 224),
+      crop_area_factor=(0.8, 1.0),
+      aspect_ratio_factor=(3/4, 4/3)
+    ),
+    keras_cv.layers.RandomFlip(),
+    keras_cv.layers.RandAugment(value_range=(0, 255)),
     keras_cv.layers.CutMix(),
     keras_cv.layers.MixUp()
-], name="preprocessing_model")
+]
+
+def augment_data(images, labels):
+  labels = tf.one_hot(labels, 3)
+  inputs = {"images": images, "labels": labels}
+  for layer in preprocessing_layers:
+    inputs = layer(inputs)
+  return inputs['images'], inputs['labels']
 ```
 
 Augment a `tf.data.Dataset`:
 
 ```python
-dataset = dataset.map(lambda images, labels: {"images": images, "labels": labels})
-dataset = dataset.map(preprocessing_model)
-dataset = dataset.map(lambda inputs: (inputs["images"], inputs["labels"]))
+dataset = tfds.load('rock_paper_scissors', as_supervised=True, split='train')
+dataset = dataset.batch(64)
+dataset = dataset.map(augment_data)
 ```
 
 Create a model:
@@ -54,9 +69,13 @@ Create a model:
 densenet = keras_cv.models.DenseNet121(
   include_rescaling=True,
   include_top=True,
-  num_classes=102
+  num_classes=3
+)
+densenet.compile(
+  loss='categorical_crossentropy',
+  optimizer='adam',
+  metrics=['accuracy']
 )
-densenet.compile(optimizer='adam', metrics=['accuracy'])
 ```
 
 Train your model: