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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Find Knowledge Graph Names"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "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",
+ "import time\n",
+ "from datetime import datetime\n",
+ "\n",
+ "import requests\n",
+ "\n",
+ "import json\n",
+ "import urllib\n",
+ "from multiprocessing.pool import ThreadPool\n",
+ "import threading\n",
+ "from urllib.request import urlopen\n",
+ "import urllib.request\n",
+ "\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\n",
+ "import sys\n",
+ "sys.path.append('/work/megapixels_dev/megapixels/')\n",
+ "from app.utils import file_utils, im_utils"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Load Metadata"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "dir_msceleb = '/data_store_hdd/datasets/people/msceleb/media/original/'\n",
+ "kg_ids_msceleb = [x.replace('m.', '/m/') for x in os.listdir(dir_msceleb)]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "api_key = open('/work/megapixels_dev/3rdparty/knowledge-graph-api/.api_key').read()\n",
+ "url_kg_api = 'https://kgsearch.googleapis.com/v1/entities:search'"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def get_kg_from_kg_obj(obj):\n",
+ " # TODO detect 503 service unavailable\n",
+ " timeout_error_msg = b'HTTP Error 503: Service Unavailable'\n",
+ " url_error_msg = b'HTTP Error 400: Bad Request'\n",
+ " global api_key, url_kg_api\n",
+ " kg_id = obj['kg_id']\n",
+ " params = {\n",
+ " 'ids': kg_id,\n",
+ " 'limit': 1,\n",
+ " 'indent': True,\n",
+ " 'key': api_key,\n",
+ " }\n",
+ " url = f'{url_kg_api}?{urllib.parse.urlencode(params)}'\n",
+ " result = {'kg_id': kg_id, 'score': 0.0, 'description': '', 'url':'', 'accessed': False} # default\n",
+ " try:\n",
+ " json_response = urllib.request.urlopen(url).read()\n",
+ " except Exception as e:\n",
+ " result['error'] = str(e)\n",
+ " else:\n",
+ " try:\n",
+ " response = json.loads(json_response)\n",
+ " items = response.get('itemListElement', [])\n",
+ " result['accessed'] = True\n",
+ " if items:\n",
+ " item = items[0]\n",
+ " item_result = item.get('result', [])\n",
+ " result['description'] = item_result.get('description', '')\n",
+ " det_desc = item_result.get('detailedDescription', '')\n",
+ " if det_desc:\n",
+ " result['description_extended'] = det_desc.get('articleBody','')\n",
+ " result['description_license'] = det_desc.get('license','')\n",
+ " result['description_url'] = det_desc.get('url','')\n",
+ " else:\n",
+ " result['description_extended'] = ''\n",
+ " result['description_license'] = ''\n",
+ " result['description_url'] = ''\n",
+ " result_img = item_result.get('image', '')\n",
+ " if result_img:\n",
+ " result['image_url'] = result_img.get('contentUrl', '')\n",
+ " result['name'] = item_result.get('name', '')\n",
+ " result['score'] = item.get('resultScore', 0.0)\n",
+ " result['url'] = item_result.get('url', '')\n",
+ " except Exception as e:\n",
+ " result['error'] = str(e)\n",
+ " return result"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "unmapped_persons = [{'kg_id': x} for x in kg_ids_msceleb]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "2d0733764379489aa82ed20f20edbb9b",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "HBox(children=(IntProgress(value=0, max=93418), HTML(value='')))"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "data": {
+ "application/vnd.jupyter.widget-view+json": {
+ "model_id": "f38b47614c5b4894b7e026b6a46a5057",
+ "version_major": 2,
+ "version_minor": 0
+ },
+ "text/plain": [
+ "HBox(children=(IntProgress(value=0, max=93418), HTML(value='')))"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "opt_threads = 10\n",
+ "pbar = tqdm(total=len(unmapped_persons))\n",
+ "\n",
+ "# define thread mapping function\n",
+ "def pool_map_persons(obj):\n",
+ " global pbar\n",
+ " pbar.update(1)\n",
+ " kg_obj = get_kg_from_kg_obj(obj)\n",
+ " return kg_obj\n",
+ "\n",
+ "# convert to thread pool\n",
+ "mapped_persons = []\n",
+ "pool = ThreadPool(opt_threads)\n",
+ "\n",
+ "# start threading\n",
+ "with tqdm(total=len(unmapped_persons)) as pbar:\n",
+ " mapped_persons = pool.map(pool_map_persons, unmapped_persons)\n",
+ "\n",
+ "# close tqdm\n",
+ "pbar.close()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "```\n",
+ "{'@id': 'kg:/m/01008l96',\n",
+ " 'name': 'Mohamed Guessous',\n",
+ " '@type': ['Thing', 'Person'],\n",
+ " 'description': 'Moroccan sociologist',\n",
+ " 'image': {'contentUrl': 'http://t2.gstatic.com/images?q=tbn:ANd9GcTAHGBU-4ZzSqcMbDPnSHZA10u0L9Hnppdvt_AnFdQzOYnS0aHM',\n",
+ " 'url': 'https://en.wikipedia.org/wiki/Mohamed_Guessous'},\n",
+ " 'detailedDescription': {'articleBody': 'Mohamed Guessous was a Moroccan sociologist. He was also an active politician in the Socialist Union of Popular Forces.',\n",
+ " 'url': 'https://en.wikipedia.org/wiki/Mohamed_Guessous',\n",
+ " 'license': 'https://en.wikipedia.org/wiki/Wikipedia:Text_of_Creative_Commons_Attribution-ShareAlike_3.0_Unported_License'},\n",
+ " 'score': 11.046742}\n",
+ " ```"
+ ]
+ },
+ {
+ "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
+}