pip install imageio

Author: atqy

prep_data/image_data_guide/builtin_preprocess_and_train.ipynb

@@ -39,6 +39,15 @@
     "In this section, you will use a dataset manifest to download animal images from the COCO dataset for all ten animal classes. You will then download frog images from the CIFAR dataset and add them to your COCO animal images. In order to simulate coming to SageMaker with your own dataset, we will keep the data in an unstructured form until the next notebook where you will learn the best practices for structuring an image dataset."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install imageio"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,

prep_data/image_data_guide/pytorch_preprocess_and_train.ipynb

@@ -8,7 +8,7 @@
     "\n",
     "**Notes**: \n",
     "* This notebook should be used with the conda_pytorch_latest_p36 kernel\n",
-    "* You can also explore image preprocessing with TensorFlow and PyTorch by running [Download, Structure, and Preprocess Image Data for TensorFlow Models](tensorflow_preprocess_and_train.ipynb) and [Download, Structure, and Preprocess Image Data for SageMaker Built-In Algorithms](builtin_preprocess_and_train.ipynb), respectively.\n",
+    "* You can also explore image preprocessing with TensorFlow and SageMaker Built-in Algorithms by running [Download, Structure, and Preprocess Image Data for TensorFlow Models](tensorflow_preprocess_and_train.ipynb) and [Download, Structure, and Preprocess Image Data for SageMaker Built-In Algorithms](builtin_preprocess_and_train.ipynb), respectively.\n",
     "\n"
    ]
   },

prep_data/image_data_guide/tensorflow_preprocess_and_train.ipynb

@@ -8,7 +8,7 @@
     "\n",
     "**Notes**: \n",
     "* This notebook should be used with the conda_pytorch_latest_p36 kernel\n",
-    "* You can also explore image preprocessing with TensorFlow and PyTorch by running [Download, Structure, and Preprocess Image Data for PyTorch Models](pytorch_preprocess_and_train.ipynb) and [Download, Structure, and Preprocess Image Data for SageMaker Built-In Algorithms](builtin_preprocess_and_train.ipynb), respectively.\n"
+    "* You can also explore image preprocessing with PyTorch and SageMaker Built-in Algorithms by running [Download, Structure, and Preprocess Image Data for PyTorch Models](pytorch_preprocess_and_train.ipynb) and [Download, Structure, and Preprocess Image Data for SageMaker Built-In Algorithms](builtin_preprocess_and_train.ipynb), respectively.\n"
    ]
   },
   {
@@ -39,6 +39,15 @@
     "In this section, you will use a dataset manifest to download animal images from the COCO dataset for all ten animal classes. You will then download frog images from the CIFAR dataset and add them to your COCO animal images. In order to simulate coming to SageMaker with your own dataset, we will keep the data in an unstructured form until the next notebook where you will learn the best practices for structuring an image dataset."
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "! pip install imageio"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,