Update deep dream example for Keras 3.

keras-team · Nov 9, 2023 · fe285a4 · fe285a4
1 parent a7787f6
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Showing 5 changed files with 90 additions and 101 deletions.
diff --git a/examples/generative/deep_dream.py b/examples/generative/deep_dream.py
@@ -38,8 +38,8 @@
 
 import numpy as np
 import tensorflow as tf
-from tensorflow import keras
-from tensorflow.keras.applications import inception_v3
+import keras
+from keras.applications import inception_v3
 
 base_image_path = keras.utils.get_file("sky.jpg", "https://i.imgur.com/aGBdQyK.jpg")
 result_prefix = "sky_dream"

diff --git a/examples/generative/img/deep_dream/deep_dream_17_0.png b/examples/generative/img/deep_dream/deep_dream_17_0.png
diff --git a/...rative/img/deep_dream/deep_dream_5_0.jpeg → ...erative/img/deep_dream/deep_dream_5_0.jpg b/...rative/img/deep_dream/deep_dream_5_0.jpeg → ...erative/img/deep_dream/deep_dream_5_0.jpg
diff --git a/examples/generative/ipynb/deep_dream.ipynb b/examples/generative/ipynb/deep_dream.ipynb
@@ -42,7 +42,7 @@
     "- Stop when we are back to the original size.\n",
     "To obtain the detail lost during upscaling, we simply\n",
     "take the original image, shrink it down, upscale it,\n",
-    "and compare the result to the (resized) original image.\n"
+    "and compare the result to the (resized) original image."
    ]
   },
   {
@@ -51,7 +51,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Setup\n"
+    "## Setup"
    ]
   },
   {
@@ -64,8 +64,8 @@
    "source": [
     "import numpy as np\n",
     "import tensorflow as tf\n",
-    "from tensorflow import keras\n",
-    "from tensorflow.keras.applications import inception_v3\n",
+    "import keras\n",
+    "from keras.applications import inception_v3\n",
     "\n",
     "base_image_path = keras.utils.get_file(\"sky.jpg\", \"https://i.imgur.com/aGBdQyK.jpg\")\n",
     "result_prefix = \"sky_dream\"\n",
@@ -87,7 +87,7 @@
     "num_octave = 3  # Number of scales at which to run gradient ascent\n",
     "octave_scale = 1.4  # Size ratio between scales\n",
     "iterations = 20  # Number of ascent steps per scale\n",
-    "max_loss = 15.0\n"
+    "max_loss = 15.0"
    ]
   },
   {
@@ -96,7 +96,7 @@
     "colab_type": "text"
    },
    "source": [
-    "This is our base image:\n"
+    "This is our base image:"
    ]
   },
   {
@@ -109,7 +109,7 @@
    "source": [
     "from IPython.display import Image, display\n",
     "\n",
-    "display(Image(base_image_path))\n"
+    "display(Image(base_image_path))"
    ]
   },
   {
@@ -118,7 +118,7 @@
     "colab_type": "text"
    },
    "source": [
-    "Let's set up some image preprocessing/deprocessing utilities:\n"
+    "Let's set up some image preprocessing/deprocessing utilities:"
    ]
   },
   {
@@ -150,7 +150,7 @@
     "    # Convert to uint8 and clip to the valid range [0, 255]\n",
     "    x = np.clip(x, 0, 255).astype(\"uint8\")\n",
     "    return x\n",
-    "\n"
+    ""
    ]
   },
   {
@@ -162,7 +162,7 @@
     "## Compute the Deep Dream loss\n",
     "\n",
     "First, build a feature extraction model to retrieve the activations of our target layers\n",
-    "given an input image.\n"
+    "given an input image."
    ]
   },
   {
@@ -186,7 +186,7 @@
     "\n",
     "# Set up a model that returns the activation values for every target layer\n",
     "# (as a dict)\n",
-    "feature_extractor = keras.Model(inputs=model.inputs, outputs=outputs_dict)\n"
+    "feature_extractor = keras.Model(inputs=model.inputs, outputs=outputs_dict)"
    ]
   },
   {
@@ -195,7 +195,7 @@
     "colab_type": "text"
    },
    "source": [
-    "The actual loss computation is very simple:\n"
+    "The actual loss computation is very simple:"
    ]
   },
   {
@@ -218,7 +218,7 @@
     "        scaling = tf.reduce_prod(tf.cast(tf.shape(activation), \"float32\"))\n",
     "        loss += coeff * tf.reduce_sum(tf.square(activation[:, 2:-2, 2:-2, :])) / scaling\n",
     "    return loss\n",
-    "\n"
+    ""
    ]
   },
   {
@@ -227,7 +227,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Set up the gradient ascent loop for one octave\n"
+    "## Set up the gradient ascent loop for one octave"
    ]
   },
   {
@@ -259,7 +259,7 @@
     "            break\n",
     "        print(\"... Loss value at step %d: %.2f\" % (i, loss))\n",
     "    return img\n",
-    "\n"
+    ""
    ]
   },
   {
@@ -268,7 +268,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Run the training loop, iterating over different octaves\n"
+    "## Run the training loop, iterating over different octaves"
    ]
   },
   {
@@ -284,7 +284,7 @@
     "\n",
     "successive_shapes = [original_shape]\n",
     "for i in range(1, num_octave):\n",
-    "    shape = tuple([int(dim / (octave_scale ** i)) for dim in original_shape])\n",
+    "    shape = tuple([int(dim / (octave_scale**i)) for dim in original_shape])\n",
     "    successive_shapes.append(shape)\n",
     "successive_shapes = successive_shapes[::-1]\n",
     "shrunk_original_img = tf.image.resize(original_img, successive_shapes[0])\n",
@@ -303,7 +303,7 @@
     "    img += lost_detail\n",
     "    shrunk_original_img = tf.image.resize(original_img, shape)\n",
     "\n",
-    "keras.utils.save_img(result_prefix + \".png\", deprocess_image(img.numpy()))\n"
+    "keras.utils.save_img(result_prefix + \".png\", deprocess_image(img.numpy()))"
    ]
   },
   {
@@ -314,7 +314,7 @@
    "source": [
     "Display the result.\n",
     "\n",
-    "You can use the trained model hosted on [Hugging Face Hub](https://huggingface.co/keras-io/deep-dream) ",
+    "You can use the trained model hosted on [Hugging Face Hub](https://huggingface.co/keras-io/deep-dream)\n",
     "and try the demo on [Hugging Face Spaces](https://huggingface.co/spaces/keras-io/deep-dream)."
    ]
   },
@@ -326,7 +326,7 @@
    },
    "outputs": [],
    "source": [
-    "display(Image(result_prefix + \".png\"))\n"
+    "display(Image(result_prefix + \".png\"))"
    ]
   }
  ],