02

02_production.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -263,25 +263,67 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "To download images, you should sign up at Microsoft for *Bing Image Search*. You will be given a key, which you can either paste over `os.environ('AZURE_SEARCH_KEY')` below, or you can set in your terminal as:\n",
+    "As at the time of writing, Bing Image Search is the best option we know of for finding and downloading images. It's free for up to 1000 queries per month, and each query can download up to 150 images. However, something better might have come along between when we wrote this and when you're reading the book, so be sure to check out [book.fast.ai](https://book.fast.ai) where we'll let you know our current recommendation."
-    "\n",
-    "    export AZURE_SEARCH_KEY=your_key_here"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "key = os.environ['AZURE_SEARCH_KEY']"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "As at the time of writing, Bing Image Search is the best option we know of for finding and downloading images. It's free for up to 1000 queries per month, and each query can download up to 150 images. However, something better might have come along between when we wrote this and when you're reading the book, so be sure to check out [book.fast.ai](https://book.fast.ai) where we'll let you know our current recommendation."
+    "> important: Services that can be used for creating datasets come and go all the time, and their features, interfaces, and pricing change regularly too. In this section, we'll show how to use one particular provider, *Bing Image Search*, using the service they have as this book as written. We'll be providing more options and more up to date information on the [book website](https://book.fast.ai), so be sure to have a look there now to get the most current information on how to download images from the web to create a dataset for deep learning."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To download images with Bing Image Search, you should sign up at Microsoft for *Bing Image Search*. You will be given a key, which you can either paste here, replacing \"XXX\":"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "key = 'XXX'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "...or, if you're comfortable at the command line, you can set it in your terminal with:\n",
+    "\n",
+    "    export AZURE_SEARCH_KEY=your_key_here\n",
+    "\n",
+    "and then restart jupyter notebooks, and finally execute in this notebook:\n",
+    "\n",
+    "```python\n",
+    "key = os.environ['AZURE_SEARCH_KEY']\n",
+    "```\n",
+    "\n",
+    "Once you've set `key`, you can use `search_images_bing`. This function is provided by the small `utils` class included in the book. Remember, if you're not sure where a symbol is defined, you can just type it in your notebook to find out (or prefix with `?` to get help, including the name of the file where it's defined, or with `??` to get its source code):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<function utils.search_images_bing(key, term, min_sz=128)>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "search_images_bing"
    ]
   },
   {
@@ -462,6 +504,22 @@
     "failed"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To remove the failed images, we can use `unlink` on each. Note that, like most fastai functions that return a collection, `verify_images` returns an object of type `L`, which includes the `map` method. This calls the passed function on each element of the collection."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "failed.map(Path.unlink);"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -507,22 +565,6 @@
     "### End sidebar"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "To remove the failed images, we can use `unlink` on each. Note that, like most fastai functions that return a collection, `verify_images` returns an object of type `L`, which includes the `map` method. This calls the passed function on each element of the collection."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "failed.map(Path.unlink);"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -699,7 +741,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "scrolled": true
+   },
    "outputs": [
     {
      "data": {