fixing dataset procesosrs

3 files changed, 617 insertions, 93 deletions

diff --git a/megapixels/notebooks/_local_scratch.ipynb b/megapixels/notebooks/_local_scratch.ipynb
index 167b6ddd..cee17cba 100644
--- a/megapixels/notebooks/_local_scratch.ipynb
+++ b/megapixels/notebooks/_local_scratch.ipynb
@@ -1,161 +1,173 @@
 {
  "cells": [
   {
-   "cell_type": "code",
-   "execution_count": 1,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "import pandas as pd\n",
-    "import cv2 as cv\n",
-    "import numpy as np\n",
-    "%matplotlib inline\n",
-    "import matplotlib.pyplot as plt"
+    "# Scratch pad"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
-    "import sys\n",
     "from glob import glob\n",
     "from os.path import join\n",
     "from pathlib import Path\n",
+    "import random\n",
+    "\n",
+    "import pandas as pd\n",
+    "import cv2 as cv\n",
+    "import numpy as np\n",
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "import sys\n",
     "sys.path.append('/work/megapixels_dev/megapixels')\n",
     "from app.models.bbox import BBox\n",
-    "#from app.utils import im_utils\n",
-    "import random"
+    "from app.utils import im_utils, file_utils"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
-    "dir_ims = '/data_store_ssd/apps/megapixels/datasets/umd_faces/faces/'"
+    "a= [1]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0\n"
-     ]
+     "data": {
+      "text/plain": [
+       "1"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
-    "fp_ims = glob(join(dir_ims, '*.png'))\n",
-    "print(len(fp_ims))"
+    "a[-1]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Help on function choice in module random:\n",
-      "\n",
-      "choice(self, seq)\n",
-      "    Choose a random element from a non-empty sequence.\n",
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "help(random.sample)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 33,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[1, 8, 0, 6, 3] True\n"
-     ]
-    }
-   ],
-   "source": [
-    "a = list(range(0,10))\n",
-    "b = random.sample(a, 5)\n",
-    "print(b, len(set(b))==5)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from random import randint\n",
-    "imu"
+    "fp_filepath = '/data_store_ssd/datasets/people/lfw/metadata/filepath.csv'\n",
+    "df_filepath = pd.read_csv(fp_filepath)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 48,
    "metadata": {},
    "outputs": [],
    "source": [
-    "import face_alignment\n",
-    "from skimage import io\n",
-    "\n",
-    "fa = face_alignment.FaceAlignment(face_alignment.LandmarksType._3D, flip_input=False,  device='cuda')"
+    "image_index = 12467"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 55,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "fp_im = np.random.choice(fp_ims)\n",
-    "im = io.imread(fp_im)\n",
-    "preds = fa.get_landmarks(im)\n",
-    "print(preds[0])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "12474\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "index                   12851\n",
+       "ext                       jpg\n",
+       "fn        Vladimir_Putin_0029\n",
+       "subdir         Vladimir_Putin\n",
+       "Name: 12474, dtype: object"
+      ]
+     },
+     "execution_count": 55,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "import json"
+    "image_index += 1\n",
+    "print(image_index)\n",
+    "df_filepath.iloc[image_index]"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [],
    "source": [
-    "print(len(preds[0]))\n"
+    "import imutils"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 57,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Help on function build_montages in module imutils.convenience:\n",
+      "\n",
+      "build_montages(image_list, image_shape, montage_shape)\n",
+      "    ---------------------------------------------------------------------------------------------\n",
+      "    author: Kyle Hounslow\n",
+      "    ---------------------------------------------------------------------------------------------\n",
+      "    Converts a list of single images into a list of 'montage' images of specified rows and columns.\n",
+      "    A new montage image is started once rows and columns of montage image is filled.\n",
+      "    Empty space of incomplete montage images are filled with black pixels\n",
+      "    ---------------------------------------------------------------------------------------------\n",
+      "    :param image_list: python list of input images\n",
+      "    :param image_shape: tuple, size each image will be resized to for display (width, height)\n",
+      "    :param montage_shape: tuple, shape of image montage (width, height)\n",
+      "    :return: list of montage images in numpy array format\n",
+      "    ---------------------------------------------------------------------------------------------\n",
+      "    \n",
+      "    example usage:\n",
+      "    \n",
+      "    # load single image\n",
+      "    img = cv2.imread('lena.jpg')\n",
+      "    # duplicate image 25 times\n",
+      "    num_imgs = 25\n",
+      "    img_list = []\n",
+      "    for i in xrange(num_imgs):\n",
+      "        img_list.append(img)\n",
+      "    # convert image list into a montage of 256x256 images tiled in a 5x5 montage\n",
+      "    montages = make_montages_of_images(img_list, (256, 256), (5, 5))\n",
+      "    # iterate through montages and display\n",
+      "    for montage in montages:\n",
+      "        cv2.imshow('montage image', montage)\n",
+      "        cv2.waitKey(0)\n",
+      "    \n",
+      "    ----------------------------------------------------------------------------------------------\n",
+      "\n"
+     ]
+    }
+   ],
    "source": [
-    "with open('test.json', 'w') as fp:\n",
-    "  json.dump(preds[0].tolist(), fp)"
+    "help(imutils.build_montages)"
    ]
   },
   {
@@ -182,7 +194,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.5"
+   "version": "3.6.6"
   }
  },
  "nbformat": 4,
diff --git a/megapixels/notebooks/datasets/lfw/lfw_make_identity_csv.ipynb b/megapixels/notebooks/datasets/lfw/lfw_make_identity_csv.ipynb
new file mode 100644
index 00000000..039614f0
--- /dev/null
+++ b/megapixels/notebooks/datasets/lfw/lfw_make_identity_csv.ipynb
@@ -0,0 +1,510 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Add identity ID to index"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from os.path import join\n",
+    "from pathlib import Path\n",
+    "import difflib\n",
+    "\n",
+    "from tqdm import tqdm_notebook as tqdm\n",
+    "import pandas as pd\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# names\n",
+    "DATA_STORE = '/data_store_ssd/'\n",
+    "dir_dataset = 'datasets/people/lfw/metadata'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# split records into index and uuids\n",
+    "fp_identity_in = join(DATA_STORE, dir_dataset, 'identities_old.csv')\n",
+    "fp_identity_out = join(DATA_STORE, dir_dataset, 'identity_lookup.csv')\n",
+    "\n",
+    "df_identity = pd.read_csv(fp_identity_in).set_index('index')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>name</th>\n",
+       "      <th>name_orig</th>\n",
+       "      <th>description</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>images</th>\n",
+       "      <th>image_index</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>index</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>A. J. Cook</td>\n",
+       "      <td>AJ Cook</td>\n",
+       "      <td>Canadian actress</td>\n",
+       "      <td>f</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>AJ Lamas</td>\n",
+       "      <td>AJ Lamas</td>\n",
+       "      <td>American actor</td>\n",
+       "      <td>m</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Aaron Eckhart</td>\n",
+       "      <td>Aaron Eckhart</td>\n",
+       "      <td>American actor</td>\n",
+       "      <td>m</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Aaron Guiel</td>\n",
+       "      <td>Aaron Guiel</td>\n",
+       "      <td>Professional baseball player</td>\n",
+       "      <td>m</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Aaron Patterson</td>\n",
+       "      <td>Aaron Patterson</td>\n",
+       "      <td>Author</td>\n",
+       "      <td>m</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  name        name_orig                   description gender  \\\n",
+       "index                                                                          \n",
+       "0           A. J. Cook          AJ Cook              Canadian actress      f   \n",
+       "1             AJ Lamas         AJ Lamas                American actor      m   \n",
+       "2        Aaron Eckhart    Aaron Eckhart                American actor      m   \n",
+       "3          Aaron Guiel      Aaron Guiel  Professional baseball player      m   \n",
+       "4      Aaron Patterson  Aaron Patterson                        Author      m   \n",
+       "\n",
+       "       images  image_index  \n",
+       "index                       \n",
+       "0           1            0  \n",
+       "1           1            1  \n",
+       "2           1            2  \n",
+       "3           1            3  \n",
+       "4           1            4  "
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_identity.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>name</th>\n",
+       "      <th>name_orig</th>\n",
+       "      <th>description</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>images</th>\n",
+       "      <th>image_index</th>\n",
+       "      <th>subdir</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>index</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>A. J. Cook</td>\n",
+       "      <td>AJ Cook</td>\n",
+       "      <td>Canadian actress</td>\n",
+       "      <td>f</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>AJ Lamas</td>\n",
+       "      <td>AJ Lamas</td>\n",
+       "      <td>American actor</td>\n",
+       "      <td>m</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "             name name_orig       description gender  images  image_index  \\\n",
+       "index                                                                       \n",
+       "0      A. J. Cook   AJ Cook  Canadian actress      f       1            0   \n",
+       "1        AJ Lamas  AJ Lamas    American actor      m       1            1   \n",
+       "\n",
+       "      subdir  \n",
+       "index         \n",
+       "0             \n",
+       "1             "
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# associate each file with an identity\n",
+    "df_identity['subdir'] = [''] * len(df_identity)\n",
+    "df_identity.head(2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "ece5c11b90954b25b1f1e28fc2fe6b55",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "HBox(children=(IntProgress(value=0, max=5749), HTML(value='')))"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "for row in tqdm(df_identity.itertuples(), total=len(df_identity)):\n",
+    "  name = row.name_orig\n",
+    "  subdir = name.replace(' ','_')\n",
+    "  df_identity.at[row.Index, 'subdir'] = subdir"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>name</th>\n",
+       "      <th>name_orig</th>\n",
+       "      <th>description</th>\n",
+       "      <th>gender</th>\n",
+       "      <th>images</th>\n",
+       "      <th>image_index</th>\n",
+       "      <th>subdir</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>index</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>A. J. Cook</td>\n",
+       "      <td>AJ Cook</td>\n",
+       "      <td>Canadian actress</td>\n",
+       "      <td>f</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>AJ_Cook</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>AJ Lamas</td>\n",
+       "      <td>AJ Lamas</td>\n",
+       "      <td>American actor</td>\n",
+       "      <td>m</td>\n",
+       "      <td>1</td>\n",
+       "      <td>1</td>\n",
+       "      <td>AJ_Lamas</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Aaron Eckhart</td>\n",
+       "      <td>Aaron Eckhart</td>\n",
+       "      <td>American actor</td>\n",
+       "      <td>m</td>\n",
+       "      <td>1</td>\n",
+       "      <td>2</td>\n",
+       "      <td>Aaron_Eckhart</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Aaron Guiel</td>\n",
+       "      <td>Aaron Guiel</td>\n",
+       "      <td>Professional baseball player</td>\n",
+       "      <td>m</td>\n",
+       "      <td>1</td>\n",
+       "      <td>3</td>\n",
+       "      <td>Aaron_Guiel</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Aaron Patterson</td>\n",
+       "      <td>Aaron Patterson</td>\n",
+       "      <td>Author</td>\n",
+       "      <td>m</td>\n",
+       "      <td>1</td>\n",
+       "      <td>4</td>\n",
+       "      <td>Aaron_Patterson</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  name        name_orig                   description gender  \\\n",
+       "index                                                                          \n",
+       "0           A. J. Cook          AJ Cook              Canadian actress      f   \n",
+       "1             AJ Lamas         AJ Lamas                American actor      m   \n",
+       "2        Aaron Eckhart    Aaron Eckhart                American actor      m   \n",
+       "3          Aaron Guiel      Aaron Guiel  Professional baseball player      m   \n",
+       "4      Aaron Patterson  Aaron Patterson                        Author      m   \n",
+       "\n",
+       "       images  image_index           subdir  \n",
+       "index                                        \n",
+       "0           1            0          AJ_Cook  \n",
+       "1           1            1         AJ_Lamas  \n",
+       "2           1            2    Aaron_Eckhart  \n",
+       "3           1            3      Aaron_Guiel  \n",
+       "4           1            4  Aaron_Patterson  "
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df_identity.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df_identity.to_csv(fp_identity_out)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 138,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# make a clean index separate from files"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 145,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'AJ Lamas'"
+      ]
+     },
+     "execution_count": 145,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#df_identies = pd.read_csv('identities.csv')\n",
+    "df_identities.iloc[1]['name']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 149,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1 2 3 4\n"
+     ]
+    }
+   ],
+   "source": [
+    "a = [1,2,3,4]\n",
+    "\n",
+    "print(*a)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:megapixels]",
+   "language": "python",
+   "name": "conda-env-megapixels-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/megapixels/notebooks/examples/face_recognition_demo.ipynb b/megapixels/notebooks/examples/face_recognition_demo.ipynb
index 68c5f3b6..804c63b6 100644
--- a/megapixels/notebooks/examples/face_recognition_demo.ipynb
+++ b/megapixels/notebooks/examples/face_recognition_demo.ipynb
@@ -402,7 +402,9 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "import imutils"
+   ]
   },
   {
    "cell_type": "code",