colab demo update (#6616)

research/deeplab/deeplab_demo.ipynb

@@ -7,9 +7,36 @@
         "id": "KFPcBuVFw61h"
       },
       "source": [
-        "# DeepLab Demo\n",
+        "# Overview\n",
         "\n",
-        "This demo will demostrate the steps to run deeplab semantic segmentation model on sample input images."
+        "This demo will demostrate the steps to use the DeepLab model to perform semantic segmentation on a sample input image. Expected outputs are semantic labels overlayed on the sample image.\n",
+        "\n",
+        "### What is DeepLab\n",
+        "Models used in this colab perform semantic segmentation. Semantic segmentation models focus on assigning semantic labels (e.g. sky, person, car) to multiple objects and stuff in a single image."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "colab_type": "text",
+        "id": "t3ozFsEEP-u_"
+      },
+      "source": [
+        "# Instructions\n",
+        "\u003ch3\u003e\u003ca href=\"https://cloud.google.com/tpu/\"\u003e\u003cimg valign=\"middle\" src=\"https://raw.githubusercontent.com/GoogleCloudPlatform/tensorflow-without-a-phd/master/tensorflow-rl-pong/images/tpu-hexagon.png\" width=\"50\"\u003e\u003c/a\u003e  \u0026nbsp;\u0026nbsp;Use a free TPU device\u003c/h3\u003e\n",
+        "\n",
+        "   1. On the main menu, click Runtime and select **Change runtime type**. Set \"TPU\" as the hardware accelerator.\n",
+        "   1. Click Runtime again and select **Runtime \u003e Run All** (Watch out: the \"Colab-only auth for this notebook and the TPU\" cell requires user input). You can also run the cells manually with Shift-ENTER."
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "colab_type": "text",
+        "id": "7cRiapZ1P3wy"
+      },
+      "source": [
+        "## Import Libraries"
       ]
     },
     {
@@ -17,19 +44,12 @@
       "execution_count": 0,
       "metadata": {
         "cellView": "code",
-        "colab": {
-          "autoexec": {
-            "startup": false,
-            "wait_interval": 0
-          }
-        },
+        "colab": {},
         "colab_type": "code",
         "id": "kAbdmRmvq0Je"
       },
       "outputs": [],
       "source": [
-        "#@title Imports\n",
-        "\n",
         "import os\n",
         "from io import BytesIO\n",
         "import tarfile\n",
@@ -44,25 +64,32 @@
         "import tensorflow as tf"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "colab_type": "text",
+        "id": "p47cYGGOQE1W"
+      },
+      "source": [
+        "## Import helper methods\n",
+        "These methods will help us perform the following tasks:\n",
+        "* Load the latest version of the pretrained DeepLab model\n",
+        "* Load the colormap from the PASCAL VOC dataset\n",
+        "* Adds colors to various labels (For example, \"pink\" for people, \"green\" for bicycle and more)\n",
+        "* Visualize an image, and add an overlay of colors on various regions."
+      ]
+    },
     {
       "cell_type": "code",
       "execution_count": 0,
       "metadata": {
         "cellView": "code",
-        "colab": {
-          "autoexec": {
-            "startup": false,
-            "wait_interval": 0
-          }
-        },
+        "colab": {},
         "colab_type": "code",
         "id": "vN0kU6NJ1Ye5"
       },
       "outputs": [],
       "source": [
-        "#@title Helper methods\n",
-        "\n",
-        "\n",
         "class DeepLabModel(object):\n",
         "  \"\"\"Class to load deeplab model and run inference.\"\"\"\n",
         "\n",
@@ -202,23 +229,27 @@
         "FULL_COLOR_MAP = label_to_color_image(FULL_LABEL_MAP)"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "colab_type": "text",
+        "id": "nGcZzNkASG9A"
+      },
+      "source": [
+        "## Select a pretrained model\n",
+        "We have trained the DeepLab model using various backbone networks that you can choose form."
+      ]
+    },
     {
       "cell_type": "code",
       "execution_count": 0,
       "metadata": {
-        "colab": {
-          "autoexec": {
-            "startup": false,
-            "wait_interval": 0
-          }
-        },
+        "colab": {},
         "colab_type": "code",
         "id": "c4oXKmnjw6i_"
       },
       "outputs": [],
       "source": [
-        "#@title Select and download models {display-mode: \"form\"}\n",
-        "\n",
         "MODEL_NAME = 'mobilenetv2_coco_voctrainaug'  # @param ['mobilenetv2_coco_voctrainaug', 'mobilenetv2_coco_voctrainval', 'xception_coco_voctrainaug', 'xception_coco_voctrainval']\n",
         "\n",
         "_DOWNLOAD_URL_PREFIX = 'http://download.tensorflow.org/models/'\n",
@@ -269,18 +300,13 @@
       "cell_type": "code",
       "execution_count": 0,
       "metadata": {
-        "colab": {
-          "autoexec": {
-            "startup": false,
-            "wait_interval": 0
-          }
-        },
+        "cellView": "form",
+        "colab": {},
         "colab_type": "code",
         "id": "edGukUHXyymr"
       },
       "outputs": [],
       "source": [
-        "#@title Run on sample images {display-mode: \"form\"}\n",
         "\n",
         "SAMPLE_IMAGE = 'image1'  # @param ['image1', 'image2', 'image3']\n",
         "IMAGE_URL = ''  #@param {type:\"string\"}\n",
@@ -310,32 +336,27 @@
       ]
     },
     {
-      "cell_type": "code",
-      "execution_count": 0,
+      "cell_type": "markdown",
       "metadata": {
-        "colab": {
-          "autoexec": {
-            "startup": false,
-            "wait_interval": 0
-          }
-        },
-        "colab_type": "code",
-        "id": "7XrFNGsxzSIB"
+        "colab_type": "text",
+        "id": "aUbVoHScTJYe"
       },
-      "outputs": [],
       "source": [
-        ""
+        "## What's next\n",
+        "\n",
+        "* Learn about [Cloud TPUs](https://cloud.google.com/tpu/docs) that Google designed and optimized specifically to speed up and scale up ML workloads for training and inference and to enable ML engineers and researchers to iterate more quickly.\n",
+        "* Explore the range of [Cloud TPU tutorials and Colabs](https://cloud.google.com/tpu/docs/tutorials) to find other examples that can be used when implementing your ML project.\n",
+        "* [Here's](https://cloud.google.com/tpu/docs/tutorials/deeplab) a direct link to the DeepLab tutorial.\n"
       ]
     }
   ],
   "metadata": {
     "colab": {
       "collapsed_sections": [],
-      "default_view": {},
       "name": "DeepLab Demo.ipynb",
       "provenance": [],
-      "version": "0.3.2",
-      "views": {}
+      "toc_visible": true,
+      "version": "0.3.2"
     },
     "kernelspec": {
       "display_name": "Python 2",
@@ -345,4 +366,3 @@
   "nbformat": 4,
   "nbformat_minor": 0
 }
-