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authoradamhrv <adam@ahprojects.com>2019-01-28 18:11:36 +0100
committeradamhrv <adam@ahprojects.com>2019-01-28 18:11:36 +0100
commitdd2c36288aa1e8af14588f9258f6785879b8638c (patch)
tree543564ff7cc9b83ae1ecbc5b0d89bca9a6c17742 /megapixels/notebooks/datasets/imdb_wiki/imdb_wiki_kg.ipynb
parentb0b06be0defe97ef19cf4d0f3328db40d299e110 (diff)
add utils for analyzing identities
Diffstat (limited to 'megapixels/notebooks/datasets/imdb_wiki/imdb_wiki_kg.ipynb')
-rw-r--r--megapixels/notebooks/datasets/imdb_wiki/imdb_wiki_kg.ipynb468
1 files changed, 0 insertions, 468 deletions
diff --git a/megapixels/notebooks/datasets/imdb_wiki/imdb_wiki_kg.ipynb b/megapixels/notebooks/datasets/imdb_wiki/imdb_wiki_kg.ipynb
deleted file mode 100644
index b9a77fda..00000000
--- a/megapixels/notebooks/datasets/imdb_wiki/imdb_wiki_kg.ipynb
+++ /dev/null
@@ -1,468 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "# IMDB-WIKI Knowledge Graph"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 110,
- "metadata": {},
- "outputs": [],
- "source": [
- "import os\n",
- "import os.path as osp\n",
- "from os.path import join\n",
- "from glob import glob\n",
- "import random\n",
- "import math\n",
- "from datetime import datetime\n",
- "import requests\n",
- "import json\n",
- "import urllib\n",
- "\n",
- "import cv2 as cv\n",
- "import pandas as pd\n",
- "from scipy.io import loadmat\n",
- "import numpy as np\n",
- "%matplotlib inline\n",
- "import matplotlib.pyplot as plt\n",
- "\n",
- "from tqdm import tqdm_notebook as tqdm\n",
- "%reload_ext autoreload\n",
- "%autoreload 2"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Load Metadata"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "metadata": {},
- "outputs": [],
- "source": [
- "fp_meta = '/data_store_hdd/datasets/people/imdb_wiki/metadata/imdb_wiki.csv'"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "metadata": {},
- "outputs": [],
- "source": [
- "df_meta = pd.read_csv(fp_meta).set_index('index')"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "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>celeb_id</th>\n",
- " <th>dob</th>\n",
- " <th>filepath</th>\n",
- " <th>gender</th>\n",
- " <th>name</th>\n",
- " <th>x1</th>\n",
- " <th>x2</th>\n",
- " <th>y1</th>\n",
- " <th>y2</th>\n",
- " <th>year_photo</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",
- " <th></th>\n",
- " <th></th>\n",
- " <th></th>\n",
- " </tr>\n",
- " </thead>\n",
- " <tbody>\n",
- " <tr>\n",
- " <th>0</th>\n",
- " <td>6488</td>\n",
- " <td>1900-5-11</td>\n",
- " <td>01/nm0000001_rm124825600_1899-5-10_1968.jpg</td>\n",
- " <td>m</td>\n",
- " <td>Fred Astaire</td>\n",
- " <td>1072.926000</td>\n",
- " <td>1214.784000</td>\n",
- " <td>161.838000</td>\n",
- " <td>303.696000</td>\n",
- " <td>1968</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>1</th>\n",
- " <td>6488</td>\n",
- " <td>1900-5-11</td>\n",
- " <td>01/nm0000001_rm3343756032_1899-5-10_1970.jpg</td>\n",
- " <td>m</td>\n",
- " <td>Fred Astaire</td>\n",
- " <td>477.184000</td>\n",
- " <td>622.592000</td>\n",
- " <td>100.352000</td>\n",
- " <td>245.760000</td>\n",
- " <td>1970</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>2</th>\n",
- " <td>6488</td>\n",
- " <td>1900-5-11</td>\n",
- " <td>01/nm0000001_rm577153792_1899-5-10_1968.jpg</td>\n",
- " <td>m</td>\n",
- " <td>Fred Astaire</td>\n",
- " <td>114.969643</td>\n",
- " <td>451.686572</td>\n",
- " <td>114.969643</td>\n",
- " <td>451.686572</td>\n",
- " <td>1968</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>3</th>\n",
- " <td>6488</td>\n",
- " <td>1900-5-11</td>\n",
- " <td>01/nm0000001_rm946909184_1899-5-10_1968.jpg</td>\n",
- " <td>m</td>\n",
- " <td>Fred Astaire</td>\n",
- " <td>622.885506</td>\n",
- " <td>844.339008</td>\n",
- " <td>424.217504</td>\n",
- " <td>645.671006</td>\n",
- " <td>1968</td>\n",
- " </tr>\n",
- " <tr>\n",
- " <th>4</th>\n",
- " <td>6488</td>\n",
- " <td>1900-5-11</td>\n",
- " <td>01/nm0000001_rm980463616_1899-5-10_1968.jpg</td>\n",
- " <td>m</td>\n",
- " <td>Fred Astaire</td>\n",
- " <td>1013.859002</td>\n",
- " <td>1201.586128</td>\n",
- " <td>233.882042</td>\n",
- " <td>421.609168</td>\n",
- " <td>1968</td>\n",
- " </tr>\n",
- " </tbody>\n",
- "</table>\n",
- "</div>"
- ],
- "text/plain": [
- " celeb_id dob filepath \\\n",
- "index \n",
- "0 6488 1900-5-11 01/nm0000001_rm124825600_1899-5-10_1968.jpg \n",
- "1 6488 1900-5-11 01/nm0000001_rm3343756032_1899-5-10_1970.jpg \n",
- "2 6488 1900-5-11 01/nm0000001_rm577153792_1899-5-10_1968.jpg \n",
- "3 6488 1900-5-11 01/nm0000001_rm946909184_1899-5-10_1968.jpg \n",
- "4 6488 1900-5-11 01/nm0000001_rm980463616_1899-5-10_1968.jpg \n",
- "\n",
- " gender name x1 x2 y1 y2 \\\n",
- "index \n",
- "0 m Fred Astaire 1072.926000 1214.784000 161.838000 303.696000 \n",
- "1 m Fred Astaire 477.184000 622.592000 100.352000 245.760000 \n",
- "2 m Fred Astaire 114.969643 451.686572 114.969643 451.686572 \n",
- "3 m Fred Astaire 622.885506 844.339008 424.217504 645.671006 \n",
- "4 m Fred Astaire 1013.859002 1201.586128 233.882042 421.609168 \n",
- "\n",
- " year_photo \n",
- "index \n",
- "0 1968 \n",
- "1 1970 \n",
- "2 1968 \n",
- "3 1968 \n",
- "4 1968 "
- ]
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "df_meta.head()"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "metadata": {},
- "outputs": [],
- "source": [
- "ids"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [],
- "source": [
- "api_key = open('/work/megapixels_dev/3rdparty/knowledge-graph-api/.api_key').read()\n",
- "\n",
- "def get_knowledge(q, api_key):\n",
- " service_url = 'https://kgsearch.googleapis.com/v1/entities:search'\n",
- " params = {\n",
- " 'query': q,\n",
- " 'limit': 5,\n",
- " 'indent': True,\n",
- " 'key': api_key,\n",
- " }\n",
- " url = service_url + '?' + urllib.parse.urlencode(params) # TODO: use requests\n",
- " response = json.loads(urllib.request.urlopen(url).read())\n",
- " response = response.get('itemListElement', [])\n",
- " if len(response) > 0:\n",
- " result = response[0].get('result', [])\n",
- " result['score'] = response[0]['resultScore']\n",
- " return result\n",
- " else:\n",
- " return []"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 106,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "General Secretary of the Communist Party of China\n",
- "Xi Jinping\n"
- ]
- },
- {
- "ename": "KeyError",
- "evalue": "'url'",
- "output_type": "error",
- "traceback": [
- "\u001b[0;31m--------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
- "\u001b[0;32m<ipython-input-106-654588fe3a11>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'description'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'name'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'url'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 7\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'score'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
- "\u001b[0;31mKeyError\u001b[0m: 'url'"
- ]
- }
- ],
- "source": [
- "# test\n",
- "q = 'Xi Jinping'\n",
- "r = get_knowledge(q, api_key)\n",
- "print(r['description'])\n",
- "print(r['name'])\n",
- "print(r['url'])\n",
- "print(r['score'])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 107,
- "metadata": {},
- "outputs": [],
- "source": [
- "from pprint import pprint"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 108,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "kg:/m/06ff60\n"
- ]
- }
- ],
- "source": [
- "print(r['@id'])"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 89,
- "metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "{'@id': 'kg:/g/11f4ksbzcm',\n",
- " '@type': ['Thing', 'Event'],\n",
- " 'detailedDescription': {'articleBody': 'On February 14, 2018, a gunman opened '\n",
- " 'fire at Marjory Stoneman Douglas High '\n",
- " 'School in Parkland, Florida, killing '\n",
- " 'seventeen students and staff members '\n",
- " 'and injuring seventeen others. ',\n",
- " 'license': 'https://en.wikipedia.org/wiki/Wikipedia:Text_of_Creative_Commons_Attribution-ShareAlike_3.0_Unported_License',\n",
- " 'url': 'https://en.wikipedia.org/wiki/Stoneman_Douglas_High_School_shooting'},\n",
- " 'image': {'contentUrl': 'http://t1.gstatic.com/images?q=tbn:ANd9GcQmY7VqmGt4zEJU8Rc4EwPWroYd-L0QQ5wkZfiFO-WRqNBC-FPN',\n",
- " 'url': 'https://en.wikipedia.org/wiki/Stoneman_Douglas_High_School_shooting'},\n",
- " 'name': 'Stoneman Douglas High School shooting',\n",
- " 'score': 60.411652}\n"
- ]
- }
- ],
- "source": [
- "pprint(r)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 20,
- "metadata": {},
- "outputs": [],
- "source": [
- "dir_msceleb = '/data_store_hdd/datasets/people/msceleb/media/original/'"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 64,
- "metadata": {},
- "outputs": [],
- "source": [
- "kgs_msceleb = os.listdir(dir_msceleb)\n",
- "kgs_msceleb = ['/' + x.replace('.','/') for x in kgs_msceleb]"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 109,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "True"
- ]
- },
- "execution_count": 109,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "'/m/06ff60' in kgs_msceleb"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 111,
- "metadata": {},
- "outputs": [],
- "source": [
- "def get_kg_by_id(kg_id, api_key):\n",
- " service_url = 'https://kgsearch.googleapis.com/v1/entities:search'\n",
- " params = {\n",
- " 'ids': kg_id,\n",
- " 'limit': 1,\n",
- " 'indent': True,\n",
- " 'key': api_key,\n",
- " }\n",
- " url = service_url + '?' + urllib.parse.urlencode(params) # TODO: use requests\n",
- " try:\n",
- " response = json.loads(urllib.request.urlopen(url).read())\n",
- " response = response.get('itemListElement', [])\n",
- " result = response[0].get('result', [])\n",
- " result['score'] = response[0]['resultScore']\n",
- " return result\n",
- " except Exception as e:\n",
- " return []"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 122,
- "metadata": {},
- "outputs": [],
- "source": [
- "a = get_kg_by_id('/m/0100n5bs', api_key)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 123,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "[]"
- ]
- },
- "execution_count": 123,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "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
-}