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gehn11/Vitaliy_Romanyuk_v2

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Text query to image - Integrated project 4
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{
"cells": [
{
"cell_type": "markdown",
"id": "ccda7cfe",
"metadata": {},
"source": [
"<img src=\"http://s3.amazonaws.com/pix.iemoji.com/images/emoji/apple/ios-12/256/waving-hand.png\" align=left width=44, heigth=44>\n",
"<div class=\"alert alert-info\">\n",
"<b> Комментарий ревьюера</b>\n",
"\n",
"\n",
"Привет, Виталий! Давай знакомиться! Меня зовут Дмитрий Махортов, и я буду проверять твой проект. Сразу предлагаю общение на «ты» 🙂, но если тебе это не комфортно, то дай знать, и мы перейдем на «вы». \n",
"\n",
"\n",
"Моя основная цель — не указать на совершенные тобою ошибки, а поделиться своим опытом и помочь тебе погрузиться в увлекательный мир работы с данными и вырасти в крепкого профи. Это отдаленная цель. А ближайшая - сделать твою работу еще лучше )).\n",
" \n",
" \n",
"Все ключевые этапы в работе выполнены, и я вижу что с проектом ты справшяешься. Есть моменты, которые нужно доработать, но я уверен, у тебя все получится.\n",
" \n",
"Расскажу как обычно проходит проверка: \n",
"Бывают моменты, которые требуют пристального внимания. Комментарии по ним выделены <span style='background-color:#F7B3A4'> красным цветом </span> и обозначены значком 🛑. После их доработки проект будет принят. 🙂\n",
" \n",
"<span style='background-color:#B7EBA7'> Зеленым цветом </span> и значком ✅ отмечены удачные и элегантные решения, на которые можно опираться в будущих проектах. Или советы «со звездочкой», которые помогут тебе в будущем.\n",
"\n",
"<span style='background-color:#F9EDA6'>Жёлтым цветом </span> и значком ⚠️ выделено то, что в следующий раз можно сделать по-другому. Ты можешь учесть эти комментарии при выполнении будущих заданий или доработать проект сейчас (однако это не обязательно).\n",
"\n",
"Давай работать над проектом в диалоге: **если ты что-то меняешь в проекте по моим рекомендациям — пиши об этом**. Выбери для своих комментариев какой-то заметный цвет, так мне будет легче отследить изменения. Пожалуйста, **не перемещай, не изменяй и не удаляй мои комментарии**. Всё это поможет выполнить повторную проверку твоего проекта оперативнее. \n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "4196bce0",
"metadata": {},
"source": [
"<div class=\"alert\" style=\"background-color:#ead7f7;color:#8737bf\">\n",
" <font size=\"3\"><b>Комментарий студента</b></font>\n",
" \n",
"И снова привет, Дмитрий!) Огромное спасибо за проверку моей работы! Как и на прошлом проекте - получил от тебя много ценных советов и личного опыта.\n",
" \n",
"Проект дается мне ооооочень тяжело. Сложно мне с нейронками - не хочется просто копировать чужой код - хочется разобраться, как работает, но не во всем получается разобраться. Но стараюсь, как могу) \n",
"Поправил указанные тобой ошибки и недостатки. Надеюсь, что всё правильно сделал)\n",
"\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "e1f51763",
"metadata": {},
"source": [
"# Сборный проект-4\n",
"\n",
"Нам поручено разработать демонстрационную версию поиска изображений по запросу.\n",
"\n",
"Для демонстрационной версии нужно обучить модель, которая получит векторное представление изображения, векторное представление текста, а на выходе выдаст число от 0 до 1 — покажет, насколько текст и картинка подходят друг другу.\n",
"\n",
"## Описание данных\n",
"\n",
"Данные доступны по [ссылке](https://code.s3.yandex.net/datasets/dsplus_integrated_project_4.zip).\n",
"\n",
"В файле `train_dataset.csv` находится информация, необходимая для обучения: имя файла изображения, идентификатор описания и текст описания. Для одной картинки может быть доступно до 5 описаний. Идентификатор описания имеет формат `<имя файла изображения>#<порядковый номер описания>`.\n",
"\n",
"В папке `train_images` содержатся изображения для тренировки модели.\n",
"\n",
"В файле `CrowdAnnotations.tsv` — данные по соответствию изображения и описания, полученные с помощью краудсорсинга. Номера колонок и соответствующий тип данных:\n",
"\n",
"1. Имя файла изображения.\n",
"2. Идентификатор описания.\n",
"3. Доля людей, подтвердивших, что описание соответствует изображению.\n",
"4. Количество человек, подтвердивших, что описание соответствует изображению.\n",
"5. Количество человек, подтвердивших, что описание не соответствует изображению.\n",
"\n",
"В файле `ExpertAnnotations.tsv` содержатся данные по соответствию изображения и описания, полученные в результате опроса экспертов. Номера колонок и соответствующий тип данных:\n",
"\n",
"1. Имя файла изображения.\n",
"2. Идентификатор описания.\n",
"\n",
"3, 4, 5 — оценки трёх экспертов.\n",
"\n",
"Эксперты ставят оценки по шкале от 1 до 4, где 1 — изображение и запрос совершенно не соответствуют друг другу, 2 — запрос содержит элементы описания изображения, но в целом запрос тексту не соответствует, 3 — запрос и текст соответствуют с точностью до некоторых деталей, 4 — запрос и текст соответствуют полностью.\n",
"\n",
"В файле `test_queries.csv` находится информация, необходимая для тестирования: идентификатор запроса, текст запроса и релевантное изображение. Для одной картинки может быть доступно до 5 описаний. Идентификатор описания имеет формат `<имя файла изображения>#<порядковый номер описания>`.\n",
"\n",
"В папке `test_images` содержатся изображения для тестирования модели."
]
},
{
"cell_type": "markdown",
"id": "0139ca68",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" 👍 Да, это хорошая практика - дать описание контекста и проблемы, которую мы решаем. </div>"
]
},
{
"cell_type": "markdown",
"id": "f6e20718",
"metadata": {},
"source": [
"## Знакомство с данными. "
]
},
{
"cell_type": "markdown",
"id": "13d44002",
"metadata": {},
"source": [
"**Импортируем необходимые библиотеки.**"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "06e03d65",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"import os\n",
"import pandas as pd\n",
"import random\n",
"import torch\n",
"import torch.nn as nn\n",
"import torchvision\n",
"from PIL import Image\n",
"from random import randrange\n",
"from sklearn.dummy import DummyRegressor\n",
"from sklearn.feature_extraction.text import TfidfVectorizer\n",
"from sklearn.linear_model import LinearRegression\n",
"from sklearn.metrics import mean_squared_error\n",
"from sklearn.model_selection import GroupShuffleSplit\n",
"from sklearn.preprocessing import StandardScaler\n",
"from torchvision import models\n",
"from torchvision import transforms\n",
"from tqdm import notebook\n",
"from transformers import BertTokenizer, BertModel"
]
},
{
"cell_type": "markdown",
"id": "a5109a73",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
"Отлично, все нужные библиотеки импортированы в начале ноутбука.Это хорошая практика.</div>"
]
},
{
"cell_type": "markdown",
"id": "2f4a5b1c",
"metadata": {},
"source": [
"**Загразим таблицу с информацией для обучения.**"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "ff871b0f",
"metadata": {},
"outputs": [],
"source": [
"path = './to_upload/'"
]
},
{
"cell_type": "markdown",
"id": "49fc63c1",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
"Большое тебе человеческое спасибо за вынос пути к данным в отдельную константу. Это сэкономило мне немало времени при проверке.</div>"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "4a106e03",
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_csv(path+'train_dataset.csv')\n",
"df.columns=['file_name', 'query_id', 'query_text']"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "bcf228bc",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
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" <th></th>\n",
" <th>file_name</th>\n",
" <th>query_id</th>\n",
" <th>query_text</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1056338697_4f7d7ce270.jpg</td>\n",
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" <td>A young child is wearing blue goggles and sitt...</td>\n",
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" <tr>\n",
" <th>1</th>\n",
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" <th>3</th>\n",
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"text/plain": [
" file_name query_id \\\n",
"0 1056338697_4f7d7ce270.jpg 2549968784_39bfbe44f9.jpg#2 \n",
"1 1262583859_653f1469a9.jpg 2549968784_39bfbe44f9.jpg#2 \n",
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"4 2621415349_ef1a7e73be.jpg 2549968784_39bfbe44f9.jpg#2 \n",
"\n",
" query_text \n",
"0 A young child is wearing blue goggles and sitt... \n",
"1 A young child is wearing blue goggles and sitt... \n",
"2 A young child is wearing blue goggles and sitt... \n",
"3 A young child is wearing blue goggles and sitt... \n",
"4 A young child is wearing blue goggles and sitt... "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.head()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "2276f0af",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 5822 entries, 0 to 5821\n",
"Data columns (total 3 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 file_name 5822 non-null object\n",
" 1 query_id 5822 non-null object\n",
" 2 query_text 5822 non-null object\n",
"dtypes: object(3)\n",
"memory usage: 136.6+ KB\n"
]
}
],
"source": [
"df.info()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "58d35a18",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df.duplicated().sum()"
]
},
{
"cell_type": "markdown",
"id": "e75bcbbd",
"metadata": {},
"source": [
"В таблице 5822 строки. Пропусков и дубликатов нет. Проанализируем данные."
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "69cfc4d7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"В датасете 1000 уникальных имен файлов.\n"
]
}
],
"source": [
"print('В датасете', len(df['file_name'].unique()), 'уникальных имен файлов.')"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "a54a2536",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"В датасете 977 уникальных текстов запросов.\n"
]
}
],
"source": [
"print('В датасете', len(df['query_id'].unique()), 'уникальных текстов запросов.')"
]
},
{
"cell_type": "markdown",
"id": "7b0e5ece",
"metadata": {},
"source": [
"Сохраним в переменную *images_df* уникальные имена файлов изображений, а в переменную *queries_df* - уникальные id и тексты запросов."
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "71188090",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1000"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"images_df = pd.DataFrame(df['file_name']).drop_duplicates('file_name').reset_index(drop=True)\n",
"len(images_df['file_name'])"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "5c0f9a4e",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"977"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"queries_df = df[['query_id', 'query_text']].drop_duplicates().reset_index(drop=True)\n",
"len(queries_df)"
]
},
{
"cell_type": "markdown",
"id": "cb5c270f",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" ок, есть первое знакомство с датафреймом </div>"
]
},
{
"cell_type": "markdown",
"id": "9860a8b5",
"metadata": {},
"source": [
"**Загрузим и обработаем данные, полученные с помощью краудсорсинга**"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "bc1e832a",
"metadata": {},
"outputs": [],
"source": [
"train_crowd_target = pd.read_table(path+'CrowdAnnotations.tsv',\n",
" names=['file_name', \n",
" 'query_id', \n",
" 'target_crowd', \n",
" 'num_votes_up', \n",
" 'num_votes_down'])"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "92287250",
"metadata": {
"scrolled": true
},
"outputs": [
{
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"execution_count": 12,
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],
"source": [
"train_crowd_target.head()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "b192ff26",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 47830 entries, 0 to 47829\n",
"Data columns (total 5 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 file_name 47830 non-null object \n",
" 1 query_id 47830 non-null object \n",
" 2 target_crowd 47830 non-null float64\n",
" 3 num_votes_up 47830 non-null int64 \n",
" 4 num_votes_down 47830 non-null int64 \n",
"dtypes: float64(1), int64(2), object(2)\n",
"memory usage: 1.8+ MB\n"
]
}
],
"source": [
"train_crowd_target.info()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "b4b48714",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_crowd_target.duplicated().sum()"
]
},
{
"cell_type": "markdown",
"id": "f5b4ad0d",
"metadata": {},
"source": [
"В датасете 47830 строк. Пропусков и явных дубликатов нет."
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "96097201",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"В таблице 1000 уникальных имен файлов.\n"
]
}
],
"source": [
"print('В таблице', len(train_crowd_target['file_name'].unique()), 'уникальных имен файлов.')"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "3e115b24",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"В таблице 1000 уникальных текстов запросов.\n"
]
}
],
"source": [
"print('В таблице', len(train_crowd_target['query_id'].unique()), 'уникальных текстов запросов.')"
]
},
{
"cell_type": "markdown",
"id": "af5a68a9",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" 👍 </div>"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "85fce577",
"metadata": {},
"outputs": [],
"source": [
"# Округлим значения оценки до 4 знака после запятой."
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "41dd45f9",
"metadata": {},
"outputs": [],
"source": [
"# train_crowd_target['target_crowd'] = train_crowd_target['target_crowd'].round(4)"
]
},
{
"cell_type": "markdown",
"id": "29ed8954",
"metadata": {},
"source": [
"<img src=\"https://upload.wikimedia.org/wikipedia/commons/b/ba/Warning_sign_4.0.png\" align=left width=44, heigth=33>\n",
"<div class=\"alert alert-warning\">\n",
"Если честно, я не вижу в этом большого смысла. Все равно для хранения будет использоваться тот же тип данных, а в качестве мы можем незначительно потерять.\n",
"\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "d64be69c",
"metadata": {},
"source": [
"<div class=\"alert\" style=\"background-color:#ead7f7;color:#8737bf\">\n",
" <font size=\"3\"><b>Комментарий студента</b></font>\n",
" \n",
"Убрал. Изначально ставил, чтобы в *value_counts* значения не задваивались (в нем, например, 0.3333 из краудсорсинга и 0.3333, которые я посчитал, по понятным причинам отображались как разные значения). Потом *value_counts* удалил, а эта строчка осталась. Но вредь так округлять не буду)\n",
"\n",
"</div>"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6ca09c90",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "cbb8fa46",
"metadata": {},
"source": [
"**Загрузим данные с разметкой, полученной с помощью экспертной оценки.**"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "f2bbaab0",
"metadata": {},
"outputs": [],
"source": [
"train_expert_target = pd.read_table(path+'ExpertAnnotations.tsv',\n",
" names=['file_name', \n",
" 'query_id', \n",
" 'eval_1', \n",
" 'eval_2', \n",
" 'eval_3'])"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "3701d915",
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
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" <th></th>\n",
" <th>file_name</th>\n",
" <th>query_id</th>\n",
" <th>eval_1</th>\n",
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" <tr>\n",
" <th>1</th>\n",
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" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
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" <tr>\n",
" <th>2</th>\n",
" <td>1056338697_4f7d7ce270.jpg</td>\n",
" <td>3181701312_70a379ab6e.jpg#2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
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" <tr>\n",
" <th>3</th>\n",
" <td>1056338697_4f7d7ce270.jpg</td>\n",
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" <td>1</td>\n",
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" <td>2</td>\n",
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" <tr>\n",
" <th>4</th>\n",
" <td>1056338697_4f7d7ce270.jpg</td>\n",
" <td>3286822339_5535af6b93.jpg#2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
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" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" file_name query_id eval_1 eval_2 \\\n",
"0 1056338697_4f7d7ce270.jpg 2549968784_39bfbe44f9.jpg#2 1 1 \n",
"1 1056338697_4f7d7ce270.jpg 2718495608_d8533e3ac5.jpg#2 1 1 \n",
"2 1056338697_4f7d7ce270.jpg 3181701312_70a379ab6e.jpg#2 1 1 \n",
"3 1056338697_4f7d7ce270.jpg 3207358897_bfa61fa3c6.jpg#2 1 2 \n",
"4 1056338697_4f7d7ce270.jpg 3286822339_5535af6b93.jpg#2 1 1 \n",
"\n",
" eval_3 \n",
"0 1 \n",
"1 2 \n",
"2 2 \n",
"3 2 \n",
"4 2 "
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_expert_target.head()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "5eb60207",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 5822 entries, 0 to 5821\n",
"Data columns (total 5 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 file_name 5822 non-null object\n",
" 1 query_id 5822 non-null object\n",
" 2 eval_1 5822 non-null int64 \n",
" 3 eval_2 5822 non-null int64 \n",
" 4 eval_3 5822 non-null int64 \n",
"dtypes: int64(3), object(2)\n",
"memory usage: 227.5+ KB\n"
]
}
],
"source": [
"train_expert_target.info()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "4ca40462",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
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" 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>eval_1</th>\n",
" <th>eval_2</th>\n",
" <th>eval_3</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>5822.000000</td>\n",
" <td>5822.000000</td>\n",
" <td>5822.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>1.436620</td>\n",
" <td>1.624356</td>\n",
" <td>1.881999</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>0.787084</td>\n",
" <td>0.856222</td>\n",
" <td>0.904087</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>1.000000</td>\n",
" <td>1.000000</td>\n",
" <td>2.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" <td>2.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>4.000000</td>\n",
" <td>4.000000</td>\n",
" <td>4.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" eval_1 eval_2 eval_3\n",
"count 5822.000000 5822.000000 5822.000000\n",
"mean 1.436620 1.624356 1.881999\n",
"std 0.787084 0.856222 0.904087\n",
"min 1.000000 1.000000 1.000000\n",
"25% 1.000000 1.000000 1.000000\n",
"50% 1.000000 1.000000 2.000000\n",
"75% 2.000000 2.000000 2.000000\n",
"max 4.000000 4.000000 4.000000"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_expert_target.describe()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "120fefac",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"В таблице 1000 уникальных имен файлов.\n"
]
}
],
"source": [
"print('В таблице', len(train_expert_target['file_name'].unique()), 'уникальных имен файлов.')"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "841657a7",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"В таблице 977 уникальных текстов запросов.\n"
]
}
],
"source": [
"print('В таблице', len(train_expert_target['query_id'].unique()), 'уникальных текстов запросов.')"
]
},
{
"cell_type": "markdown",
"id": "cd36d23f",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" 👍 </div>"
]
},
{
"cell_type": "markdown",
"id": "caabfbe9",
"metadata": {},
"source": [
"<img src=\"https://upload.wikimedia.org/wikipedia/commons/b/ba/Warning_sign_4.0.png\" align=left width=44, heigth=33>\n",
"<div class=\"alert alert-warning\">\n",
"На будущее советую четко разделять этапы знакомства с данными и предобработки. Иначе легко запутаться. На первом этапе мы знакомися с данными, получаем инсайты о том, с чем имеем дело. Основной результат этапа - выводы. А на втором уже делаем предобработку,жонглируем колонками и датфреймами. Основной результат этапа - датафрейм признаки/таргет, полученный объединением информации из нескольких источников.\n",
"\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "1e8383f0",
"metadata": {},
"source": [
"<div class=\"alert\" style=\"background-color:#ead7f7;color:#8737bf\">\n",
" <font size=\"3\"><b>Комментарий студента</b></font>\n",
" \n",
"Разделил разделы.\n",
"\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "8c9e44fb",
"metadata": {},
"source": [
"## Предобработка данных."
]
},
{
"cell_type": "markdown",
"id": "18bb424c",
"metadata": {},
"source": [
"Удалим из датасета строки, в которых у всех трех экспертов разделились мнения."
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "03755749",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"126"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_expert_target.loc[(train_expert_target['eval_1'] != train_expert_target['eval_2']) &\n",
" (train_expert_target['eval_2'] != train_expert_target['eval_3']) &\n",
" (train_expert_target['eval_3'] != train_expert_target['eval_1']), 'file_name'].count()"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "c1355f0a",
"metadata": {},
"outputs": [],
"source": [
"train_expert_target = train_expert_target.drop(\n",
" train_expert_target[(train_expert_target['eval_1'] != train_expert_target['eval_2']) &\n",
" (train_expert_target['eval_2'] != train_expert_target['eval_3']) &\n",
" (train_expert_target['eval_3'] != train_expert_target['eval_1'])].index\n",
")"
]
},
{
"cell_type": "markdown",
"id": "046370c6",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" 👍 </div>"
]
},
{
"cell_type": "markdown",
"id": "b61da8fc",
"metadata": {},
"source": [
"По остальным строкам выберем итоговой оценкой ту, за которую проголосовало большинство экспертов. Также приведем оценки экспертов к нашей единой шкале - от 0 до 1. Для этого из оценки экспертов нужно вычесть единицу и разделить на 3."
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "15a0a3b4",
"metadata": {},
"outputs": [],
"source": [
"def most_votes(df):\n",
" \n",
" df['target_experts'] = 0\n",
" \n",
" df.loc[(df['eval_1'] == df['eval_2']) &\n",
" (df['eval_2'] == df['eval_3']), 'target_experts'] = ((df['eval_1'] - 1) / 3).round(4)\n",
" \n",
" df.loc[df['target_experts'] == 0, 'target_experts'] = ((df['eval_2'] - 1) / 3).round(4)\n",
" \n",
" return df"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "aad66012",
"metadata": {},
"outputs": [],
"source": [
"train_expert_target = most_votes(train_expert_target)"
]
},
{
"cell_type": "markdown",
"id": "5ae48f9e",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" 👍 </div>"
]
},
{
"cell_type": "markdown",
"id": "53689752",
"metadata": {},
"source": [
"Проверим, что все посчитано корректно."
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "660399b0",
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
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" }\n",
"\n",
" .dataframe thead th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>file_name</th>\n",
" <th>query_id</th>\n",
" <th>eval_1</th>\n",
" <th>eval_2</th>\n",
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" <th>0</th>\n",
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" <td>1</td>\n",
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" <td>1</td>\n",
" <td>0.0000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
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" <td>2718495608_d8533e3ac5.jpg#2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>0.0000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1056338697_4f7d7ce270.jpg</td>\n",
" <td>3181701312_70a379ab6e.jpg#2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>0.0000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1056338697_4f7d7ce270.jpg</td>\n",
" <td>3207358897_bfa61fa3c6.jpg#2</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>2</td>\n",
" <td>0.3333</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1056338697_4f7d7ce270.jpg</td>\n",
" <td>3286822339_5535af6b93.jpg#2</td>\n",
" <td>1</td>\n",
" <td>1</td>\n",
" <td>2</td>\n",
" <td>0.0000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" file_name query_id eval_1 eval_2 \\\n",
"0 1056338697_4f7d7ce270.jpg 2549968784_39bfbe44f9.jpg#2 1 1 \n",
"1 1056338697_4f7d7ce270.jpg 2718495608_d8533e3ac5.jpg#2 1 1 \n",
"2 1056338697_4f7d7ce270.jpg 3181701312_70a379ab6e.jpg#2 1 1 \n",
"3 1056338697_4f7d7ce270.jpg 3207358897_bfa61fa3c6.jpg#2 1 2 \n",
"4 1056338697_4f7d7ce270.jpg 3286822339_5535af6b93.jpg#2 1 1 \n",
"\n",
" eval_3 target_experts \n",
"0 1 0.0000 \n",
"1 2 0.0000 \n",
"2 2 0.0000 \n",
"3 2 0.3333 \n",
"4 2 0.0000 "
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_expert_target.head()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "abfcfc42",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "bd142c10",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" 👍 </div>"
]
},
{
"cell_type": "markdown",
"id": "3bd33a3e",
"metadata": {},
"source": [
"**Объединим таблицы в один датасет.**\n",
"\n",
"Посчитаем количество пересечений запросов между таблицами с оценками и таблицей с данными."
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "b01976f1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1000"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(set(df['file_name'].unique()).intersection(train_crowd_target['file_name'].unique()))"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "5b4b9c14",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1000"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(set(df['file_name'].unique()).intersection(train_expert_target['file_name'].unique()))"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "0f3a568a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"977"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(set(df['query_id'].unique()).intersection(train_crowd_target['query_id'].unique()))"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "104c422a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"977"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(set(df['query_id'].unique()).intersection(train_expert_target['query_id'].unique()))"
]
},
{
"cell_type": "markdown",
"id": "00605fb5",
"metadata": {},
"source": [
"В таблице, полученной краудсорсингом, больше id уникальных запросов, чем в наших данных. Удалим строки с id запросов, которые нам не известны."
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "2ad65b4a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"23\n"
]
}
],
"source": [
"diff = []\n",
"for query_id in train_crowd_target['query_id'].unique():\n",
" if query_id not in df['query_id'].unique():\n",
" diff.append(query_id)\n",
"\n",
"print(len(diff))"
]
},
{
"cell_type": "markdown",
"id": "cfe2c522",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" 👍 </div>"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "d796a2c4",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"47830\n",
"46721\n"
]
}
],
"source": [
"print(len(train_crowd_target))\n",
"for query_id in diff:\n",
" train_crowd_target = train_crowd_target.drop(\n",
" train_crowd_target[train_crowd_target['query_id'] == query_id].index\n",
" )\n",
"print(len(train_crowd_target))"
]
},
{
"cell_type": "markdown",
"id": "dd20ba65",
"metadata": {},
"source": [
"Проверим, что удаление произведено корректно."
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "fcccf81f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"977"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(set(df['query_id'].unique()).intersection(train_crowd_target['query_id'].unique()))"
]
},
{
"cell_type": "markdown",
"id": "3df5d93c",
"metadata": {},
"source": [
"**Объединим таблицы с оценками.**"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "47dcb64c",
"metadata": {},
"outputs": [],
"source": [
"train_data = train_crowd_target.merge(train_expert_target,\n",
" how='outer', \n",
" on=['file_name', 'query_id']).drop(['eval_1', \n",
" 'eval_2', \n",
" 'eval_3',\n",
" 'num_votes_up',\n",
" 'num_votes_down'], axis=1)"
]
},
{
"cell_type": "markdown",
"id": "7d5a26a8",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
"\n",
"По объединению экспертных и крауд оценок все ОК, но подсвечу возможные альтернативы\n",
" \n",
"-------------- \n",
" \n",
" \n",
"В этом проекте есть несколько возможных стратегий работы с обучающими и краудсорс оценками, вот эти стратегии с плюсами и минусами:\n",
" \n",
"\n",
" - использовать соединение через outer, в этом случае, при корректной обработке пропусков мы можем получить более 50К размеченых пар. К плюсам данного подхода можно отнести большое количество данных. Минус - в основном это будут данные, размеченные краудсорсерами, а там качество раметки ниже.\n",
" - использовать только экспертные оценки. плюс - высокое качество данных (разметка имеет шкалу). Минус - данных меньше. Поясню по поводу качества разметки на примере: если на изображении одна собака, а в описании \"две собаки бегут по берегу\", то эксперты поставять соответствие 0,6-0,7 (переводя в шкалу 0-1), а краудсорсеры поставят 0. Но на экспертных оценках модель хотя-бы научится находить собак, а на краудсор оценках ничему не начится.\n",
"\n",
" - использование соединения через left. Данный подход очевидно проигрывает второму варианту: данных столько же, нужно дополнительно возиться с объединением, но качество разметки снижается.. Но это соответсвует предложениям авторов проекта, поэтому такой подход имеет право на жизнь\n",
"\n",
" - объединение через inner. Тут все плохо - и данных ОЧЕНЬ мало (в два раза меньше, чем использовать только экспертные оценки) и качество у них \"подпорчено\". И навыков по обработке пропусков не получаем.....\n",
"\n",
"\n",
"</div>"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "8ab7c1fe",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"50159"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(train_data)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "375de6f1",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"file_name 0\n",
"query_id 0\n",
"target_crowd 3438\n",
"target_experts 44463\n",
"dtype: int64"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_data.isna().sum()"
]
},
{
"cell_type": "markdown",
"id": "95e57078",
"metadata": {},
"source": [
"**Объединим общую таблицу с оценками с таблицей с текстами запросов.**"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "6c571c2d",
"metadata": {},
"outputs": [],
"source": [
"train_data = train_data.merge(queries_df, \n",
" how='inner', \n",
" on=['query_id'])"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "ce788ff8",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"50159"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(train_data)"
]
},
{
"cell_type": "markdown",
"id": "6fa6c98c",
"metadata": {},
"source": [
"Найдем пропуски."
]
},
{
"cell_type": "code",
"execution_count": 42,
"id": "6ea03758",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"file_name 0\n",
"query_id 0\n",
"target_crowd 3438\n",
"target_experts 44463\n",
"query_text 0\n",
"dtype: int64"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_data.isna().sum()"
]
},
{
"cell_type": "markdown",
"id": "a087dfc8",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" 👍 </div>"
]
},
{
"cell_type": "markdown",
"id": "17f6710d",
"metadata": {},
"source": [
"**Определим итоговые оценки.**"
]
},
{
"cell_type": "markdown",
"id": "1e4dd7ba",
"metadata": {},
"source": [
"В качестве итоговой оценки в строках с пропуском в экспертной оценке возьмем оценку краудсорсинга и наоборот."
]
},
{
"cell_type": "code",
"execution_count": 43,
"id": "162295b9",
"metadata": {},
"outputs": [],
"source": [
"train_data.loc[train_data['target_crowd'].isna(),'total_target'] = train_data['target_experts']\n",
"train_data.loc[train_data['target_experts'].isna(),'total_target'] = train_data['target_crowd']"
]
},
{
"cell_type": "markdown",
"id": "df1e687c",
"metadata": {},
"source": [
"С строках с наличием обеих оценок в качестве итоговой возьмем экспертную оценку."
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "a1e0f7de",
"metadata": {},
"outputs": [],
"source": [
"train_data.loc[train_data['total_target'].isna(),\n",
" 'total_target'] = train_data['target_experts']"
]
},
{
"cell_type": "markdown",
"id": "eb403531",
"metadata": {},
"source": [
"Проверим, что все значения итоговых оценок заполнены."
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "e369b4d7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_data['total_target'].isna().sum()"
]
},
{
"cell_type": "markdown",
"id": "bead0dcc",
"metadata": {},
"source": [
"Удалим лишние столбцы."
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "6cc65146",
"metadata": {},
"outputs": [],
"source": [
"train_data = train_data.drop(['target_experts', 'target_crowd'], axis=1)"
]
},
{
"cell_type": "markdown",
"id": "36f57461",
"metadata": {},
"source": [
"Посмотрим на распределение оценок."
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "7a9c3d4d",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"train_data['total_target'].hist(bins=5)\n",
"plt.title('Распределение оценок соответствия запросов изображениям');"
]
},
{
"cell_type": "markdown",
"id": "63122bce",
"metadata": {},
"source": [
"Количество близких к нулю оценок значительно преобладает над количеством оценок, близких единице."
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "65c518ec",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.061\n"
]
}
],
"source": [
"print((train_data.loc[train_data['total_target'] > 0.5, \n",
" 'total_target'].count() / len(train_data['total_target'])).round(3))"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "4f0c5094",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "74bd2e04",
"metadata": {},
"source": [
"Доля оценок больше 0.5 составляет только 5 % от всей выборки. Скорее всего, будет сложно получить качественную модель с таким дисбалансом в оценках."
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "ce9c2dd8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"Int64Index: 50159 entries, 0 to 50158\n",
"Data columns (total 4 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 file_name 50159 non-null object \n",
" 1 query_id 50159 non-null object \n",
" 2 query_text 50159 non-null object \n",
" 3 total_target 50159 non-null float64\n",
"dtypes: float64(1), object(3)\n",
"memory usage: 2.9+ MB\n"
]
}
],
"source": [
"train_data.info()"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "e43ba365",
"metadata": {
"scrolled": true
},
"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>file_name</th>\n",
" <th>query_id</th>\n",
" <th>query_text</th>\n",
" <th>total_target</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1056338697_4f7d7ce270.jpg</td>\n",
" <td>1056338697_4f7d7ce270.jpg#2</td>\n",
" <td>A woman is signaling is to traffic , as seen f...</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2182488373_df73c7cc09.jpg</td>\n",
" <td>1056338697_4f7d7ce270.jpg#2</td>\n",
" <td>A woman is signaling is to traffic , as seen f...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2594042571_2e4666507e.jpg</td>\n",
" <td>1056338697_4f7d7ce270.jpg#2</td>\n",
" <td>A woman is signaling is to traffic , as seen f...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2843695880_eeea6c67db.jpg</td>\n",
" <td>1056338697_4f7d7ce270.jpg#2</td>\n",
" <td>A woman is signaling is to traffic , as seen f...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2892995070_39f3c9a56e.jpg</td>\n",
" <td>1056338697_4f7d7ce270.jpg#2</td>\n",
" <td>A woman is signaling is to traffic , as seen f...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" file_name query_id \\\n",
"0 1056338697_4f7d7ce270.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"1 2182488373_df73c7cc09.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"2 2594042571_2e4666507e.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"3 2843695880_eeea6c67db.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"4 2892995070_39f3c9a56e.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"\n",
" query_text total_target \n",
"0 A woman is signaling is to traffic , as seen f... 1.0 \n",
"1 A woman is signaling is to traffic , as seen f... 0.0 \n",
"2 A woman is signaling is to traffic , as seen f... 0.0 \n",
"3 A woman is signaling is to traffic , as seen f... 0.0 \n",
"4 A woman is signaling is to traffic , as seen f... 0.0 "
]
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_data.head()"
]
},
{
"cell_type": "markdown",
"id": "ad189282",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
"ОК, есть итоговый датафрейм признаки/таргет. </div>"
]
},
{
"cell_type": "markdown",
"id": "8f0ee3e1",
"metadata": {},
"source": [
"<img src=\"https://upload.wikimedia.org/wikipedia/commons/b/ba/Warning_sign_4.0.png\" align=left width=44, heigth=33>\n",
"<div class=\"alert alert-warning\">\n",
"Но т.к. он является ключевым результатом этапа стоит показать его \"во всей красе\" - как минимум несколько строк и info()\n",
"\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "e6852c38",
"metadata": {},
"source": [
"<div class=\"alert\" style=\"background-color:#ead7f7;color:#8737bf\">\n",
" <font size=\"3\"><b>Комментарий студента</b></font>\n",
" \n",
"Добавил *info* и *head*.\n",
"\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "2f067aca",
"metadata": {},
"source": [
"## Проверка данных\n",
"\n",
"В некоторых странах, где работает наша компания, действуют ограничения по обработке изображений: поисковым сервисам и сервисам, предоставляющим возможность поиска, запрещено без разрешения родителей или законных представителей предоставлять любую информацию, в том числе, но не исключительно тексты, изображения, видео и аудио, содержащие описание, изображение или запись голоса детей. Ребёнком считается любой человек, не достигший 16 лет.\n",
"\n",
"В нашем сервисе строго следуют законам стран, в которых работают. Поэтому при попытке посмотреть изображения, запрещённые законодательством, вместо картинок показывается дисклеймер:\n",
"\n",
"> This image is unavailable in your country in compliance with local laws\n",
">\n",
"\n",
"Однако у нас нет возможности воспользоваться данным функционалом. Поэтому необходимо удалить из обучающей выборки все изображения, которые нарушают данный закон."
]
},
{
"cell_type": "markdown",
"id": "dd1bb3b0",
"metadata": {},
"source": [
"**Удалим из обучающей выборки все запросы, в которых присутствует упоминение детей.**"
]
},
{
"cell_type": "markdown",
"id": "402b53ea",
"metadata": {},
"source": [
"Создадим список слов, присутствие которых в описании к фотографии является маркером присутствия на ней ребенка."
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "f1e856f9",
"metadata": {},
"outputs": [],
"source": [
"stop_words = ['boy', 'girl', 'child', 'children', 'teenage', 'teenager', 'kid', 'baby']"
]
},
{
"cell_type": "markdown",
"id": "8cac2786",
"metadata": {},
"source": [
"Выберем из нашего перечня фотографий те, в описании которых присутствуют данные слов. Сохраним наименования выбранных изображений в переменную *not_allowed_images*."
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "79d8fd51",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: total: 62.5 ms\n",
"Wall time: 57.2 ms\n"
]
}
],
"source": [
"%%time\n",
"not_allowed_images = []\n",
"for i in range(len(queries_df['query_text'])):\n",
" for word in stop_words:\n",
" if (word in queries_df.loc[i, 'query_text'].lower()) and (\n",
" queries_df.loc[i, 'query_id'][:-2] not in not_allowed_images):\n",
" \n",
" not_allowed_images.append(queries_df.loc[i, 'query_id'][:-2])"
]
},
{
"cell_type": "markdown",
"id": "a972b963",
"metadata": {},
"source": [
"Проверим, что наименования изображений сохраняются корректно."
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "dc336c31",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['2549968784_39bfbe44f9.jpg',\n",
" '2718495608_d8533e3ac5.jpg',\n",
" '3545652636_0746537307.jpg',\n",
" '1714316707_8bbaa2a2ba.jpg',\n",
" '2140182410_8e2a06fbda.jpg']"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"not_allowed_images[:5]"
]
},
{
"cell_type": "code",
"execution_count": 54,
"id": "0d9c9492",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"287"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(not_allowed_images)"
]
},
{
"cell_type": "markdown",
"id": "84dde53c",
"metadata": {},
"source": [
"Создадим функцию, которая принимает на вход датасет с наимнованиями файлов изображений в столбце *file_name* и список изображений, которые нужно удалить, и возвращает датасет с удаленными изображениями и обнуленными индексами."
]
},
{
"cell_type": "code",
"execution_count": 55,
"id": "33e7550e",
"metadata": {},
"outputs": [],
"source": [
"def drop_images(df, images_list):\n",
" for image in images_list:\n",
" df = df.drop(df[df['file_name'] == image].index).reset_index(drop=True)\n",
" return df"
]
},
{
"cell_type": "code",
"execution_count": 56,
"id": "4d5011af",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"50159\n",
"36019\n"
]
}
],
"source": [
"print(len(train_data))\n",
"\n",
"train_data = drop_images(train_data, not_allowed_images)\n",
"print(len(train_data))"
]
},
{
"cell_type": "code",
"execution_count": 57,
"id": "15f5b271",
"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>file_name</th>\n",
" <th>query_id</th>\n",
" <th>query_text</th>\n",
" <th>total_target</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1056338697_4f7d7ce270.jpg</td>\n",
" <td>1056338697_4f7d7ce270.jpg#2</td>\n",
" <td>A woman is signaling is to traffic , as seen f...</td>\n",
" <td>1.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2182488373_df73c7cc09.jpg</td>\n",
" <td>1056338697_4f7d7ce270.jpg#2</td>\n",
" <td>A woman is signaling is to traffic , as seen f...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2843695880_eeea6c67db.jpg</td>\n",
" <td>1056338697_4f7d7ce270.jpg#2</td>\n",
" <td>A woman is signaling is to traffic , as seen f...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2892995070_39f3c9a56e.jpg</td>\n",
" <td>1056338697_4f7d7ce270.jpg#2</td>\n",
" <td>A woman is signaling is to traffic , as seen f...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2934359101_cdf57442dc.jpg</td>\n",
" <td>1056338697_4f7d7ce270.jpg#2</td>\n",
" <td>A woman is signaling is to traffic , as seen f...</td>\n",
" <td>0.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" file_name query_id \\\n",
"0 1056338697_4f7d7ce270.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"1 2182488373_df73c7cc09.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"2 2843695880_eeea6c67db.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"3 2892995070_39f3c9a56e.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"4 2934359101_cdf57442dc.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"\n",
" query_text total_target \n",
"0 A woman is signaling is to traffic , as seen f... 1.0 \n",
"1 A woman is signaling is to traffic , as seen f... 0.0 \n",
"2 A woman is signaling is to traffic , as seen f... 0.0 \n",
"3 A woman is signaling is to traffic , as seen f... 0.0 \n",
"4 A woman is signaling is to traffic , as seen f... 0.0 "
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"train_data.head()"
]
},
{
"cell_type": "code",
"execution_count": 58,
"id": "110b0391",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1000\n",
"713\n"
]
}
],
"source": [
"print(len(images_df))\n",
"\n",
"images_df = drop_images(images_df, not_allowed_images)\n",
"print(len(images_df))"
]
},
{
"cell_type": "code",
"execution_count": 59,
"id": "5ebef86e",
"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>file_name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1056338697_4f7d7ce270.jpg</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>1262583859_653f1469a9.jpg</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2621415349_ef1a7e73be.jpg</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>3155451946_c0862c70cb.jpg</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>3222041930_f642f49d28.jpg</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" file_name\n",
"0 1056338697_4f7d7ce270.jpg\n",
"1 1262583859_653f1469a9.jpg\n",
"2 2621415349_ef1a7e73be.jpg\n",
"3 3155451946_c0862c70cb.jpg\n",
"4 3222041930_f642f49d28.jpg"
]
},
"execution_count": 59,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"images_df.head()"
]
},
{
"cell_type": "markdown",
"id": "36b43682",
"metadata": {},
"source": [
"<img src=\"https://upload.wikimedia.org/wikipedia/commons/b/ba/Warning_sign_4.0.png\" align=left width=44, heigth=33>\n",
"<div class=\"alert alert-warning\">\n",
" \n",
"Ты удалил комментарии, в которых были запрещенные слова. Но наша задача убрать изображения, содержащие детей. Есть два способа сделать это:\n",
" \n",
" - Определить список плохих изображений, как изображения удовлетворяющие условиям:\n",
" - Комментарий содержит плохие слова\n",
" - <b>Оценка соответствия комментария и изображения выше порога.</b>\n",
" - Удалить из нашего датасета все пары \"изображение/описание\" с плохими изображениями.\n",
" \n",
" \n",
"И второй, очень красивый способ. Он основан на том, что `query_id` содержит в с себе имя изображения, для которого он был написан (такая пасхалочка от авторов датасета).\n",
" \n",
" - Определить список плохих комментариев\n",
" - У `query_id` плохих комментариев отрезать два последних символа и получим список плохих изображений.\n",
" \n",
" \n",
" \n",
" \n",
" \n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "cb49b224",
"metadata": {},
"source": [
"<div class=\"alert\" style=\"background-color:#ead7f7;color:#8737bf\">\n",
" <font size=\"3\"><b>Комментарий студента</b></font>\n",
" \n",
"Второй вариант действительно хорош!) Я толку дать не мог, зачем в этой таблице айдишники указаны. Вот, оказывается, зачем)\n",
" \n",
"Поправил код - удаляем по комментариям, описывающим фотографии.\n",
"\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "54788528",
"metadata": {},
"source": [
"В окончательном наборе данных осталось около 36 тысяч строк.\n",
"\n",
"Разделим выборку на обучающую и валидационную в пропорции 7:3."
]
},
{
"cell_type": "code",
"execution_count": 60,
"id": "24261ce6",
"metadata": {},
"outputs": [],
"source": [
"gss = GroupShuffleSplit(n_splits=1, train_size=0.7, random_state=10101)"
]
},
{
"cell_type": "code",
"execution_count": 61,
"id": "2de16965",
"metadata": {},
"outputs": [],
"source": [
"train_indices, valid_indices = next(\n",
" gss.split(X=train_data.drop(['total_target'], axis=1), \n",
" y=train_data['total_target'], groups=train_data['file_name'])\n",
")\n",
"\n",
"X_train, X_valid, y_train, y_valid = (\n",
" train_data.drop('total_target', axis=1).loc[train_indices],\n",
" train_data.drop('total_target', axis=1).loc[valid_indices],\n",
" train_data['total_target'].loc[train_indices],\n",
" train_data['total_target'].loc[valid_indices]\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 62,
"id": "421f65ac",
"metadata": {},
"outputs": [],
"source": [
"for df in X_train, X_valid, y_train, y_valid:\n",
" df = df.reset_index(drop=True)"
]
},
{
"cell_type": "markdown",
"id": "bf9fc10e",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
"Отлично, благодаря использованию GroupShuffleSplit ты исключаешь попадание одного изображения в обучающий и валидационный наборы.</div>"
]
},
{
"cell_type": "code",
"execution_count": 63,
"id": "d6b5fae4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"499\n",
"214\n"
]
}
],
"source": [
"print(len(X_train['file_name'].unique()))\n",
"print(len(X_valid['file_name'].unique()))"
]
},
{
"cell_type": "code",
"execution_count": 64,
"id": "6adc4ace",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"25040\n",
"10979\n"
]
}
],
"source": [
"print(len(X_train['file_name']))\n",
"print(len(X_valid['file_name']))"
]
},
{
"cell_type": "markdown",
"id": "e9fc7fd7",
"metadata": {},
"source": [
"В обучаещей выборке 700 уникальных изображений, в валидационной - 300. Разделение прошло корректно."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7481dbb4",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "1f334a64",
"metadata": {},
"source": [
"## Векторизация изображений\n",
"\n",
"Перейдём к векторизации изображений.\n",
"\n",
"Самый примитивный способ — прочесть изображение и превратить полученную матрицу в вектор. Такой способ нам не подходит: длина векторов может быть сильно разной, так как размеры изображений разные. Поэтому обратимся к свёрточным сетям: они позволяют \"выделить\" главные компоненты изображений. Возьмем архитектуру ResNet-18, предварительно натренированную на датасете ImageNet, и исключить из нее полносвязный слой, который отвечает за конечное предсказание."
]
},
{
"cell_type": "markdown",
"id": "bfc65e09",
"metadata": {
"id": "dd04d000"
},
"source": [
"<img src=\"https://upload.wikimedia.org/wikipedia/commons/b/ba/Warning_sign_4.0.png\" align=left width=44, heigth=33>\n",
"<div class=\"alert alert-warning\">\n",
"Хочу обратить твое внимание на тонкий момент, связанный с выбором фреймоворков. Для векторизациии изображений ты использовал pytorch. А нейронку для решения задачи регрессии строишь с помощью Keras.\n",
" \n",
" Поддержка двух DL фреймворков - это будет ад для девопса. Поэтому хорошей практикой является использование одного фреймворка в одном проекте. \n",
" \n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "fe610aeb",
"metadata": {},
"source": [
"<div class=\"alert\" style=\"background-color:#ead7f7;color:#8737bf\">\n",
" <font size=\"3\"><b>Комментарий студента</b></font>\n",
" \n",
"Будем уважать труд девопсов. Заменил на *torch*. Далось мне это, конечно, ценой огромного количества нервов, но зато подразбрался, как с *torch* работать)\n",
"\n",
"</div>"
]
},
{
"cell_type": "code",
"execution_count": 65,
"id": "22ea3ad6",
"metadata": {},
"outputs": [],
"source": [
"# загразим модель\n",
"resnet = models.resnet18(pretrained=True)\n",
"\n",
"# заморозим веса\n",
"for param in resnet.parameters():\n",
" param.requires_grad_(False)\n",
"\n",
"# используем все слои, кроме двух последних\n",
"modules = list(resnet.children())[:-1]\n",
"resnet = nn.Sequential(*modules)\n",
"\n",
"# переводим модель в режим предсказания\n",
"resnet.eval();"
]
},
{
"cell_type": "code",
"execution_count": 66,
"id": "cacb94ae",
"metadata": {},
"outputs": [],
"source": [
"# приведем изображение к нужному формату\n",
"norm = transforms.Normalize(\n",
" mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])\n",
"preprocess = transforms.Compose([\n",
" transforms.Resize(512),\n",
" transforms.CenterCrop(448),\n",
" transforms.ToTensor(),\n",
" norm,\n",
"])"
]
},
{
"cell_type": "markdown",
"id": "bc164fdf",
"metadata": {},
"source": [
"Зададим две функции. \n",
"- Первая функция принимает на вход имя файла изображения и имя папки, где хранится изображение, а на выходе выдает векторное представление данного изображения.\n",
"- Вторая функция принимает датафрейм с именами файлов изображений в столбце *file_name* и имя папки с изображениями, а на выходе выдает тот же датафрейм, но с добаленным столбцом *img_vector*, в котором хранятся векторы изображений, полученные от первой функции."
]
},
{
"cell_type": "code",
"execution_count": 67,
"id": "71307e94",
"metadata": {},
"outputs": [],
"source": [
"def img_to_vect(image_name, img_folder_name):\n",
" \n",
" img = Image.open(path + img_folder_name + '/' + image_name).convert('RGB')\n",
" image_tensor = preprocess(img).unsqueeze(0)\n",
" img_vector = resnet(image_tensor).flatten().numpy()\n",
" \n",
" return img_vector"
]
},
{
"cell_type": "code",
"execution_count": 68,
"id": "95d62bf9",
"metadata": {},
"outputs": [],
"source": [
"def df_img_vectorizer(df, img_folder_name):\n",
" \n",
" df['img_vector'] = df['file_name'].apply(lambda x: img_to_vect(x, img_folder_name))\n",
" \n",
" return df"
]
},
{
"cell_type": "markdown",
"id": "55b969dd",
"metadata": {},
"source": [
"Чтобы сэкономить вычислительные мощности, посчитаем векторы только для уникальных изображений и сохраним их в датафрейм *images_df*, а затем объединим данный датафрейм с нашими обучающей и валидационной таблицей оценок."
]
},
{
"cell_type": "code",
"execution_count": 69,
"id": "62a8e27a",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: total: 6min 37s\n",
"Wall time: 1min 6s\n"
]
}
],
"source": [
"%%time\n",
"images_df = df_img_vectorizer(images_df, 'train_images')"
]
},
{
"cell_type": "code",
"execution_count": 70,
"id": "d5160616",
"metadata": {},
"outputs": [
{
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],
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"images_df.head()"
]
},
{
"cell_type": "code",
"execution_count": 71,
"id": "135003be",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"X_train = X_train.merge(images_df, on='file_name', how='left')"
]
},
{
"cell_type": "code",
"execution_count": 72,
"id": "8eade1a9",
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]
},
"execution_count": 72,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_train.head()"
]
},
{
"cell_type": "code",
"execution_count": 73,
"id": "d6257a04",
"metadata": {},
"outputs": [],
"source": [
"X_valid = X_valid.merge(images_df, on='file_name', how='left')"
]
},
{
"cell_type": "code",
"execution_count": 74,
"id": "bb422332",
"metadata": {},
"outputs": [
{
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]
},
"execution_count": 74,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_valid.head()"
]
},
{
"cell_type": "markdown",
"id": "b7142288",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
"Здесь все ОК, векторизация изображений произведена верно </div>"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a47b8e99",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "ba6764a4",
"metadata": {},
"source": [
"## Векторизация текстов\n",
"\n",
"Векторизуем тексты с помощью BERT. \n",
"\n",
"Зададим функцию, которая примет на вход датафрейм со столбцом *query_text*, а в качестве результата выдаст датафрейм с добавленным столбцом векторных представлений текстов."
]
},
{
"cell_type": "code",
"execution_count": 75,
"id": "506870fd",
"metadata": {},
"outputs": [],
"source": [
"# tfidf = TfidfVectorizer()\n",
"# tfidf.fit(X_train['lem_query_text'].drop_duplicates());"
]
},
{
"cell_type": "code",
"execution_count": 76,
"id": "1b87e296",
"metadata": {},
"outputs": [],
"source": [
"# def text_to_vect(df): \n",
"# text_features_array = tfidf.transform(df['lem_query_text']).toarray() \n",
"# return text_features_array"
]
},
{
"cell_type": "markdown",
"id": "ec6e7734",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" 👍 Обучен векторайзер, есть функция для векторизации набора текстов\n",
"\n",
"-----------\n",
" \n",
"Что касается выбранного подхода. По моим наблюдения используя TfidfVectorizer крайне редко получается обучить толковую модель. Я бы советовал все-таки использовать \"плотные\" вектора полученные с помощью BERT \n",
"\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "910ba717",
"metadata": {},
"source": [
"<div class=\"alert\" style=\"background-color:#ead7f7;color:#8737bf\">\n",
" <font size=\"3\"><b>Комментарий студента</b></font>\n",
" \n",
"Удалил *tfidf*, ниже преобразовал текст *BERT'ом*. Не знаю, насколько правильно использовал его. Конструктивная критика приветствуется)\n",
"\n",
"</div>"
]
},
{
"cell_type": "code",
"execution_count": 77,
"id": "4e04b07a",
"metadata": {},
"outputs": [],
"source": [
"random_seed = 10101\n",
"random.seed(random_seed)\n",
" \n",
"torch.manual_seed(random_seed)\n",
"if torch.cuda.is_available():\n",
" torch.cuda.manual_seed_all(random_seed)"
]
},
{
"cell_type": "code",
"execution_count": 78,
"id": "5fb22bac",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\Users\\V\\anaconda3\\lib\\site-packages\\transformers\\tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884\n",
" warnings.warn(\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `beta` will be renamed internally to `bias`. Please use a different name to suppress this warning.\n",
"A parameter name that contains `gamma` will be renamed internally to `weight`. Please use a different name to suppress this warning.\n"
]
}
],
"source": [
"tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')\n",
"model = BertModel.from_pretrained('bert-base-uncased')"
]
},
{
"cell_type": "code",
"execution_count": 79,
"id": "ce1222c3",
"metadata": {},
"outputs": [],
"source": [
"def get_text_embeddings(df):\n",
" \n",
" tokenized = df['query_text'].apply(lambda x: tokenizer.encode(x, add_special_tokens=True))\n",
"\n",
" max_len = 0\n",
" for i in tokenized.to_numpy():\n",
" if len(i) > max_len:\n",
" max_len = len(i)\n",
" padded = np.array([i + [0]*(max_len - len(i)) for i in tokenized.values])\n",
"\n",
" attention_mask = np.where(padded != 0, 1, 0)\n",
" \n",
" batch_size = 100\n",
" embeddings = []\n",
" \n",
" for i in notebook.tqdm(range((padded.shape[0] - 1) // batch_size + 1)):\n",
" batch = torch.LongTensor(padded[batch_size*i:batch_size*(i+1)]) \n",
" attention_mask_batch = torch.LongTensor(attention_mask[batch_size*i:batch_size*(i+1)])\n",
" \n",
" with torch.no_grad():\n",
" batch_embeddings = model(batch, attention_mask=attention_mask_batch)\n",
" \n",
" embeddings.append(batch_embeddings[0][:,0,:].numpy())\n",
" \n",
" text_features = np.concatenate(embeddings)\n",
" \n",
" df['i'] = df['query_text'].index\n",
" df['text_vector'] = df['i'].apply(lambda x: text_features[x])\n",
" df = df.drop('i', axis=1)\n",
" \n",
" return df"
]
},
{
"cell_type": "markdown",
"id": "b4665aba",
"metadata": {},
"source": [
"Для экономии времени и вычислительных ресурсов посчитаем эмбеддинги только для уникальных текстов запросов (содержатся в столбце *queries_df['query_text']*), а затем передадим полученные значения векторов в датафреймы *X_train* и *X_valid* путем объединения по столбцу *query_id*."
]
},
{
"cell_type": "code",
"execution_count": 80,
"id": "c051db01",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "3be558c0e568402cb712730d47d7a153",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/10 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: total: 2min 17s\n",
"Wall time: 23 s\n"
]
}
],
"source": [
"%%time\n",
"queries_df = get_text_embeddings(queries_df)"
]
},
{
"cell_type": "code",
"execution_count": 81,
"id": "a4ce89f9",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 977 entries, 0 to 976\n",
"Data columns (total 3 columns):\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 query_id 977 non-null object\n",
" 1 query_text 977 non-null object\n",
" 2 text_vector 977 non-null object\n",
"dtypes: object(3)\n",
"memory usage: 23.0+ KB\n"
]
}
],
"source": [
"queries_df.info()"
]
},
{
"cell_type": "code",
"execution_count": 82,
"id": "2101cfa4",
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
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" <th></th>\n",
" <th>query_id</th>\n",
" <th>query_text</th>\n",
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"text/plain": [
" query_id \\\n",
"0 2549968784_39bfbe44f9.jpg#2 \n",
"1 2718495608_d8533e3ac5.jpg#2 \n",
"\n",
" query_text \\\n",
"0 A young child is wearing blue goggles and sitt... \n",
"1 A girl wearing a yellow shirt and sunglasses s... \n",
"\n",
" text_vector \n",
"0 [-0.047876917, 0.05141508, -0.2728134, -0.0722... \n",
"1 [0.3064608, 0.18739623, -0.31747943, -0.147754... "
]
},
"execution_count": 82,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"queries_df.head(2)"
]
},
{
"cell_type": "markdown",
"id": "b178a713",
"metadata": {},
"source": [
"Вектора добавлены корректно. Теперь передадим их в датафреймы *X_train* и *X_valid*."
]
},
{
"cell_type": "code",
"execution_count": 83,
"id": "2ab0d464",
"metadata": {},
"outputs": [],
"source": [
"X_train = X_train.merge(queries_df[['query_id', 'text_vector']],\n",
" on='query_id',\n",
" how='left')"
]
},
{
"cell_type": "code",
"execution_count": 84,
"id": "747c5563",
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
" file_name query_id \\\n",
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"1 2182488373_df73c7cc09.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"\n",
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"0 A woman is signaling is to traffic , as seen f... \n",
"1 A woman is signaling is to traffic , as seen f... \n",
"\n",
" img_vector \\\n",
"0 [0.6463168, 1.7000622, 1.0123887, 0.4651622, 0... \n",
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"\n",
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},
"execution_count": 84,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_train.head(2)"
]
},
{
"cell_type": "code",
"execution_count": 85,
"id": "f5e904b6",
"metadata": {},
"outputs": [],
"source": [
"X_valid = X_valid.merge(queries_df[['query_id', 'text_vector']],\n",
" on='query_id',\n",
" how='left')"
]
},
{
"cell_type": "code",
"execution_count": 86,
"id": "3630b882",
"metadata": {},
"outputs": [
{
"data": {
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" file_name query_id \\\n",
"0 2892995070_39f3c9a56e.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"1 2981702521_2459f2c1c4.jpg 1056338697_4f7d7ce270.jpg#2 \n",
"\n",
" query_text \\\n",
"0 A woman is signaling is to traffic , as seen f... \n",
"1 A woman is signaling is to traffic , as seen f... \n",
"\n",
" img_vector \\\n",
"0 [0.18128534, 0.6973805, 0.510044, 0.16081898, ... \n",
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"\n",
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"0 [0.043843593, 0.10764923, -0.18056223, -0.0312... \n",
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]
},
"execution_count": 86,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"X_valid.head(2)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ae269988",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "c3fbf411",
"metadata": {},
"source": [
"## Объединение векторов\n",
"\n",
"Объедините векторы изображений и векторы текстов с целевой переменной. \n",
"\n",
"Создадим функцию, принимающую на вход датафрейм со столбцами *img_vector* и *text_vector*, и выдающую на выходе массив объединенных векторов изображений и текстов, который можно использовать для обучений моделей."
]
},
{
"cell_type": "code",
"execution_count": 87,
"id": "e022289b",
"metadata": {},
"outputs": [],
"source": [
"def make_features(df):\n",
" \n",
" # массив с векторами признаков изображений\n",
" img_array = np.array(df['img_vector'].values.tolist())\n",
" \n",
" # массив с векторами признаков текста\n",
" text_array = np.array(df['text_vector'].values.tolist())\n",
" \n",
" # объединенный массив с полным набором признаков\n",
" features_array = np.concatenate((text_array, img_array), axis=1)\n",
" \n",
" return features_array"
]
},
{
"cell_type": "markdown",
"id": "f2bb5f40",
"metadata": {},
"source": [
"Масштабируем признаки. "
]
},
{
"cell_type": "code",
"execution_count": 88,
"id": "d6fd5b03",
"metadata": {},
"outputs": [],
"source": [
"scaler = StandardScaler()"
]
},
{
"cell_type": "code",
"execution_count": 89,
"id": "4b8a14b2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(25040, 1280)\n"
]
}
],
"source": [
"features_train = scaler.fit_transform(make_features(X_train))\n",
"print(features_train.shape)"
]
},
{
"cell_type": "code",
"execution_count": 90,
"id": "2a000139",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(10979, 1280)\n"
]
}
],
"source": [
"features_valid = scaler.transform(make_features(X_valid))\n",
"print(features_valid.shape)"
]
},
{
"cell_type": "markdown",
"id": "4c2d95ed",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" Вектора, полученные из текста и изображения объеденены👍 </div>"
]
},
{
"cell_type": "markdown",
"id": "a115a700",
"metadata": {},
"source": [
"<div class=\"alert\" style=\"background-color:#ead7f7;color:#8737bf\">\n",
" <font size=\"3\"><b>Комментарий студента</b></font>\n",
" \n",
"Из-за замены *tf-idf* на *BERT* немного подкорректировал функцию. Также добавил *StandardScaler*.\n",
"\n",
"</div>"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "77350848",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "94c3d62f",
"metadata": {},
"source": [
"## Обучение модели предсказания соответствия\n",
"\n",
"Обучим две модели: линейную регрессию и полносвязную нейронную сеть. В качестве метрики будем использовать среднеквадратическое отклонение *mean_squared_error*."
]
},
{
"cell_type": "markdown",
"id": "85334b25",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" 👍 </div>"
]
},
{
"cell_type": "markdown",
"id": "902cef2e",
"metadata": {},
"source": [
"**Обучим модель линейной регрессии.**"
]
},
{
"cell_type": "code",
"execution_count": 91,
"id": "7e389923",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"lin_reg = LinearRegression()\n",
"lin_reg.fit(features_train, y_train);"
]
},
{
"cell_type": "code",
"execution_count": 92,
"id": "81bf90c5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.08879310344342321\n"
]
}
],
"source": [
"lin_reg_preds = lin_reg.predict(features_valid)\n",
"print(mean_squared_error(y_valid, lin_reg_preds))"
]
},
{
"cell_type": "markdown",
"id": "98a300dd",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" 👍 </div>"
]
},
{
"cell_type": "markdown",
"id": "e7e0741f",
"metadata": {},
"source": [
"**Обучим полносвязную нейронную сеть с 4 слоями.**"
]
},
{
"cell_type": "markdown",
"id": "9f344b2c",
"metadata": {},
"source": [
"Приведем матрицы признаков и векторы целевых переменных к типу тензора, который требуется для корректной работы библиотеки *torch*."
]
},
{
"cell_type": "code",
"execution_count": 93,
"id": "12e02a6e",
"metadata": {},
"outputs": [],
"source": [
"X_train_tensor = torch.tensor(features_train, dtype=torch.float32)\n",
"X_valid_tensor = torch.tensor(features_valid, dtype=torch.float32)\n",
"y_train_tensor = torch.tensor(np.array(y_train), dtype=torch.float32).unsqueeze(1)\n",
"y_valid_tensor = torch.tensor(np.array(y_valid), dtype=torch.float32).unsqueeze(1)"
]
},
{
"cell_type": "code",
"execution_count": 94,
"id": "0840ccda",
"metadata": {},
"outputs": [],
"source": [
"class ModelNN(nn.Module):\n",
" def __init__(self, input_size, \n",
" hidden_size_1, \n",
" hidden_size_2, \n",
" hidden_size_3):\n",
" super(ModelNN, self).__init__()\n",
" \n",
" self.layer1 = nn.Linear(input_size, hidden_size_1)\n",
"# self.dp1 = nn.Dropout(p=0.5)\n",
" self.layer2 = nn.Linear(hidden_size_1, hidden_size_2)\n",
"# self.dp2 = nn.Dropout(p=0.5)\n",
" self.layer3 = nn.Linear(hidden_size_2, hidden_size_3)\n",
" self.layer4 = nn.Linear(hidden_size_3, 1)\n",
" \n",
" \n",
" def forward(self, x):\n",
" x = self.layer1(x)\n",
"# x = self.dp1(x)\n",
" x = torch.relu(x)\n",
" \n",
" x = self.layer2(x)\n",
"# x = self.dp2(x) \n",
" x = torch.relu(x)\n",
" \n",
" x = self.layer3(x)\n",
" x = torch.relu(x)\n",
" \n",
" x = torch.sigmoid(self.layer4(x))\n",
" \n",
" return x"
]
},
{
"cell_type": "code",
"execution_count": 95,
"id": "c0dee2d9",
"metadata": {},
"outputs": [],
"source": [
"torch.manual_seed(10101)\n",
"input_size = X_train_tensor.shape[1]\n",
"hidden_size_1 = 500\n",
"hidden_size_2 = 120\n",
"hidden_size_3 = 20\n",
"num_epochs = 100\n",
"learning_rate = 0.001"
]
},
{
"cell_type": "code",
"execution_count": 96,
"id": "d41965b4",
"metadata": {},
"outputs": [],
"source": [
"def init_weights(layer):\n",
" if type(layer) == nn.Linear: \n",
" nn.init.kaiming_uniform_(layer.weight, mode='fan_in', nonlinearity='relu')"
]
},
{
"cell_type": "code",
"execution_count": 97,
"id": "b8ecd451",
"metadata": {},
"outputs": [],
"source": [
"nn_model = ModelNN(input_size, \n",
" hidden_size_1, \n",
" hidden_size_2, \n",
" hidden_size_3)\n",
"nn_model.apply(init_weights)\n",
"criterion = nn.MSELoss()\n",
"optimizer = torch.optim.Adam(nn_model.parameters(), lr=learning_rate)"
]
},
{
"cell_type": "code",
"execution_count": 98,
"id": "ea2357cc",
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Epoch [10 / 100], Train Loss: 0.0553, Val Loss: 0.0564\n",
"Epoch [20 / 100], Train Loss: 0.0521, Val Loss: 0.0534\n",
"Epoch [30 / 100], Train Loss: 0.0478, Val Loss: 0.0510\n",
"Epoch [40 / 100], Train Loss: 0.0443, Val Loss: 0.0485\n",
"Epoch [50 / 100], Train Loss: 0.0413, Val Loss: 0.0473\n",
"Epoch [60 / 100], Train Loss: 0.0385, Val Loss: 0.0464\n",
"Epoch [70 / 100], Train Loss: 0.0360, Val Loss: 0.0458\n",
"Epoch [80 / 100], Train Loss: 0.0334, Val Loss: 0.0454\n",
"Epoch [90 / 100], Train Loss: 0.0308, Val Loss: 0.0451\n",
"Epoch [100 / 100], Train Loss: 0.0279, Val Loss: 0.0450\n",
"CPU times: total: 2min 57s\n",
"Wall time: 29.5 s\n"
]
}
],
"source": [
"%%time\n",
"for epoch in range(num_epochs):\n",
" # Прямой проход\n",
" nn_model.train()\n",
" outputs = nn_model(X_train_tensor)\n",
" train_loss = criterion(outputs, y_train_tensor)\n",
" \n",
" # Обратный проход\n",
" optimizer.zero_grad()\n",
" train_loss.backward()\n",
" optimizer.step()\n",
" \n",
" # Валидация\n",
" nn_model.eval()\n",
" with torch.no_grad():\n",
" outputs = nn_model(X_valid_tensor)\n",
" val_loss = criterion(outputs, y_valid_tensor)\n",
" \n",
"\n",
" if (epoch + 1) % 10 == 0:\n",
" print(f'Epoch [{epoch + 1} / {num_epochs}], Train Loss: {train_loss.item():.4f}, Val Loss: {val_loss.item():.4f}')"
]
},
{
"cell_type": "code",
"execution_count": 99,
"id": "01d91519",
"metadata": {},
"outputs": [],
"source": [
"nn_preds = nn_model.forward(X_valid_tensor)"
]
},
{
"cell_type": "code",
"execution_count": 100,
"id": "269dcb22",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.045"
]
},
"execution_count": 100,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"round(mean_squared_error(y_valid, nn_preds.detach().numpy()), 4)"
]
},
{
"cell_type": "markdown",
"id": "9d5f43ba",
"metadata": {},
"source": [
"Модель показала метрику MSE = 0.0450."
]
},
{
"cell_type": "code",
"execution_count": 101,
"id": "ab1be694",
"metadata": {},
"outputs": [],
"source": [
"# Возьмем полносвязную нейронную сеть с 4 слоями. \n",
"# Переберем количество нейронов на первых трех слоях, чтобы выбрать лучшую модель. \n",
"# Обучение для каждой конфигурации будем проводить в течение 100 эпох."
]
},
{
"cell_type": "code",
"execution_count": 102,
"id": "94a308b1",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"# %%time\n",
"# best_metric = 1000\n",
"# for i in range(50, 151, 100):\n",
"# for j in range(20, 51, 30):\n",
"# for k in range(5, 11, 5):\n",
" \n",
"# units_4 = [i, j, k, 1]\n",
"# input_dim = train_features.shape[1]\n",
" \n",
"# dense_model = keras.models.Sequential()\n",
"# dense_model.add(keras.layers.Dense(units=units_4[0], input_dim=input_dim, activation='relu'))\n",
"# dense_model.add(Dense(units=units_4[1], input_dim=units_4[0], activation='relu'))\n",
"# dense_model.add(Dense(units=units_4[2], input_dim=units_4[1], activation='relu'))\n",
"# dense_model.add(Dense(units=units_4[3], input_dim=units_4[2], activation='sigmoid'))\n",
"\n",
"# dense_model.compile(loss='mean_squared_error', optimizer='Adam', metrics=['mean_squared_error'])\n",
" \n",
"# dense_model.fit(train_features, y_train, epochs=100,validation_data=(valid_features, y_valid))\n",
" \n",
"# metric = mean_squared_error(y_valid, dense_model.predict(valid_features))\n",
" \n",
"# if metric < best_metric:\n",
"# best_metric = metric\n",
"# best_units = [i, j, k]\n",
"# best_dense_model = dense_model\n",
" "
]
},
{
"cell_type": "markdown",
"id": "cc2cc740",
"metadata": {},
"source": [
"<img src=\"https://upload.wikimedia.org/wikipedia/commons/b/ba/Warning_sign_4.0.png\" align=left width=44, heigth=33>\n",
"<div class=\"alert alert-warning\">\n",
"Так точно делать не стоит. Ты фиксируешь количество эпох и просто перебираешь размеры слоев в автоматическом режиме. При обучении нейронок работает другая логика. Мы исходим из того, что нейронка это универсаьный аппроксиматор, которая может описать любую зависимость. При подборе архитектуры мы ищем баланс между недообучением и переобучением модели. Надеюсь следующие пара комментариев помогут тебе.\n",
"\n",
"И для получения базовой интуиции советую делать подбор \"руками\".\n",
" \n",
" \n",
"\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "f8654603",
"metadata": {
"id": "3nd6gGrvzp1l"
},
"source": [
"<img src=\"https://upload.wikimedia.org/wikipedia/commons/b/ba/Warning_sign_4.0.png\" align=left width=44, heigth=33>\n",
"<div class=\"alert alert-warning\">\n",
"На мой взгляд ты воспринимаешь \"количество эпох\" как гиперпараметр \"спущеный с верху\". Т.е. устанавливаем параметры сети, запускаем обучение и смотрим на результат.\n",
" \n",
"Но в случае с нейронками логика ипользования немного отличается от того, к чему мы привыкли в классических моделях. Здесь лучше работать по другой логике:\n",
" \n",
" - оределилили архитектуру, создали модель\n",
" - начинаем её учить. и учим пока метрика на валидационной выборке улучшается. Наблюдая в динамике метрики на обучающей и валидационной выборках.\n",
" - если вдруг метрика на обучающей выборке перестала снижаться, можно попробовать уменьшить шаг обучения (например в 10 раз) и продолжить обучение модели.\n",
" \n",
"В любом случае полезно обучать модель пока метрика на валидации улучшается. Наша цель - оптимальное состояние модели, при котором модель хорошо находит законмоерности в данных, но еще не переобучилась.\n",
" \n",
"После того, как закончили обучение смотрим на логи, анализируем, чего модели не хватило, меняем архитектуру и запускаем обучение по новой. \n",
" \n",
"\n",
" \n",
"\n",
" \n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "4fbf1a91",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
"\n",
"\n",
"Для осознанной настройки нейронки важно понимать, как менять её архитектуру (усложнять и уменьшать регуляризацию? уменьшать шаг обучения? усиливать регуляризацию?). Для того чтобы принять эти решения мало видеть только конечную цифру, важно понимать, чего модели не хватает чтобы метрика стала лучше.\n",
" \n",
" \n",
"Вот типичные проблемы, которые можно выявить анализируя графики и пути их решения:\n",
"\n",
"<b>Недообучение (Underfitting)</b>\n",
" Признаки: Высокие значения потерь и низкая точность как на обучающей, так и на валидационной выборке. Графики потерь не снижаются (или снижаются недостаточно).\n",
" \n",
" Решения:\n",
" \n",
" - Увеличение сложности модели (добавление слоев, увеличение числа нейронов).\n",
" - Использование более сложных моделей, таких как более глубокие нейронные сети.\n",
" - Увеличение количества эпох обучения.\n",
"\n",
"<b>Переобучение (Overfitting)</b>\n",
" Признаки: Значительное снижение потерь и увеличение точности на обучающей выборке, но высокие потери и низкая точность на валидационной выборке. Графики начинают расходиться после некоторого количества эпох.\n",
" \n",
" Решения:\n",
" - Регуляризация (L1, L2 регуляризация).\n",
" - Dropout (добавление Dropout слоев).\n",
" - Уменьшение сложности модели (уменьшение числа слоев или нейронов).\n",
" - Использование аугментации данных для увеличения разнообразия данных.\n",
" - Раннее завершение обучения (Early Stopping) на основе валидационной ошибки.\n",
"\n",
"<b>Плохой выбор гиперпараметров</b>\n",
" Признаки: Нестабильные графики потерь и точности (большие колебания).\n",
" \n",
" Решения:\n",
" - Настройка скорости обучения (learning rate).\n",
" - Оптимизация размера батча (batch size).\n",
" - Попробовать другие оптимизаторы (например, Adam, SGD с различными параметрами). \n",
"\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "975fb98d",
"metadata": {},
"source": [
"<div class=\"alert\" style=\"background-color:#ead7f7;color:#8737bf\">\n",
" <font size=\"3\"><b>Комментарий студента</b></font>\n",
" \n",
"Я перепробовал кучу всяких конфигураций: и с Droput'ами, и скорость обучения менял, и количество слоев, и архитектуру слоев. Везде упирался в то, что на валидации MSE болтается на уровне 0.048-0.050. Не знаю как улучшить метрику. Есть мнение, что на имеющихся исходных данных это потолок.\n",
"\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "c6cb461d",
"metadata": {},
"source": [
"**Сравним полученные метрики моделей с DummyRegressor**"
]
},
{
"cell_type": "code",
"execution_count": 103,
"id": "10742291",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.05092452470314514\n"
]
}
],
"source": [
"dummy = DummyRegressor()\n",
"dummy.fit(features_train, y_train)\n",
"print(mean_squared_error(y_valid, dummy.predict(features_valid)))"
]
},
{
"cell_type": "markdown",
"id": "1a77ef94",
"metadata": {},
"source": [
"Линейная регрессия оказалась гораздо хуже, чем *DummyRegressor*. Нейросеть показала результат незначительно лучше, чем baseline-модель.\n",
"\n",
"Тестирование проведем на нейросети."
]
},
{
"cell_type": "markdown",
"id": "66ed5b6c",
"metadata": {},
"source": [
"<img src=\"https://upload.wikimedia.org/wikipedia/commons/b/ba/Warning_sign_4.0.png\" align=left width=44, heigth=33>\n",
"<div class=\"alert alert-warning\">\n",
"Мы решаем новую задачу и не знаем, наксколько хороши наши метрики и наши модели. Поэтому советую начать с бейзлайна - константной модели (можешь взять простой DummyRegressor).</div>"
]
},
{
"cell_type": "markdown",
"id": "2a1100da",
"metadata": {},
"source": [
"<div class=\"alert\" style=\"background-color:#ead7f7;color:#8737bf\">\n",
" <font size=\"3\"><b>Комментарий студента</b></font>\n",
" \n",
"Сравнил с *DummyRegressor'ом*. Увы, мои модели либо на уровне, либо значительно хуже бейзлайна.\n",
"\n",
"</div>"
]
},
{
"cell_type": "markdown",
"id": "8f73a132",
"metadata": {},
"source": [
"## Тестирование модели\n",
"\n",
"Для тестирования получим эмбеддинги для всех тестовых изображений из папки `test_images`, выберем случайные 10 запросов из файла `test_queries.csv`, для каждого запроса выведем наиболее релевантное изображение и визуально оценим качество поиска."
]
},
{
"cell_type": "markdown",
"id": "25afb802",
"metadata": {},
"source": [
"Загрузим данные с именами изображений в переменную *test_images_df*."
]
},
{
"cell_type": "code",
"execution_count": 104,
"id": "7e56efa7",
"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>file_name</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>3356748019_2251399314.jpg</td>\n",
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"text/plain": [
" file_name\n",
"0 3356748019_2251399314.jpg\n",
"1 2887171449_f54a2b9f39.jpg"
]
},
"execution_count": 104,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test_images_df = pd.read_csv(path + 'test_images.csv')\n",
"test_images_df.columns = ['file_name']\n",
"test_images_df.head(2)"
]
},
{
"cell_type": "markdown",
"id": "bc75d985",
"metadata": {},
"source": [
"Векторизуем тестовые изображения."
]
},
{
"cell_type": "code",
"execution_count": 105,
"id": "7a17452c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"CPU times: total: 56.2 s\n",
"Wall time: 9.35 s\n"
]
}
],
"source": [
"%%time\n",
"test_images_df = df_img_vectorizer(test_images_df, 'test_images')"
]
},
{
"cell_type": "markdown",
"id": "335b0e6a",
"metadata": {},
"source": [
"<img src=\"https://emojigraph.org/media/apple/check-mark-button_2705.png\" align=left width=33, heigth=33>\n",
"<div class=\"alert alert-success\">\n",
" да, тестовые изображения оптимально векторизовать заранее </div>"
]
},
{
"cell_type": "markdown",
"id": "581a2899",
"metadata": {},
"source": [
"Загрузим данные с запросами в переменную *test_images_df*."
]
},
{
"cell_type": "code",
"execution_count": 106,
"id": "d4e39e45",
"metadata": {},
"outputs": [
{
"data": {
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" }\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>file_name</th>\n",
" <th>img_vector</th>\n",
" </tr>\n",
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" <tr>\n",
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"</table>\n",
"</div>"
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"text/plain": [
" file_name \\\n",
"0 3356748019_2251399314.jpg \n",
"1 2887171449_f54a2b9f39.jpg \n",
"\n",
" img_vector \n",
"0 [0.61694926, 0.14355318, 0.6335749, 0.3363443,... \n",
"1 [0.2899826, 1.6637969, 0.5832518, 0.90192753, ... "
]
},
"execution_count": 106,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test_images_df.head(2)"
]
},
{
"cell_type": "code",
"execution_count": 107,
"id": "12712742",
"metadata": {
"scrolled": true
},
"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>index</th>\n",
" <th>query_id</th>\n",
" <th>query_text</th>\n",
" <th>file_name</th>\n",
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" <td>1</td>\n",
" <td>1177994172_10d143cb8d.jpg#1</td>\n",
" <td>Two boys are squirting water guns at each other .</td>\n",
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"</div>"
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"text/plain": [
" index query_id \\\n",
"0 0 1177994172_10d143cb8d.jpg#0 \n",
"1 1 1177994172_10d143cb8d.jpg#1 \n",
"\n",
" query_text \\\n",
"0 Two blonde boys , one in a camouflage shirt an... \n",
"1 Two boys are squirting water guns at each other . \n",
"\n",
" file_name \n",
"0 1177994172_10d143cb8d.jpg \n",
"1 1177994172_10d143cb8d.jpg "
]
},
"execution_count": 107,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test_queries_df = pd.read_csv(path + 'test_queries.csv', sep='|')\n",
"test_queries_df.columns=['index', 'query_id', 'query_text', 'file_name']\n",
"test_queries_df.head(2)"
]
},
{
"cell_type": "markdown",
"id": "a4b34971",
"metadata": {},
"source": [
"**Тестирование.**\n",
"\n",
"Для тестирования напишем функцию, которая принимает на вход текстовое описание, делает его векторизацию и возвращает картинку с максимальным значением метрики. Если запрос ведёт на юридически вредный контент, функция выводит дисклеймер. Отдельно сделаем функцию для нейронной сети и отдельно для линейной регрессии."
]
},
{
"cell_type": "code",
"execution_count": 108,
"id": "84338678",
"metadata": {},
"outputs": [],
"source": [
"def query_to_image_nn(query_text): \n",
" global test_images_df\n",
" # создаем маркер наличия стоп-слова\n",
" stop = 0\n",
" # проверяем на наличие стоп-слов в запросе\n",
" for word in stop_words:\n",
" if word in query_text:\n",
" stop = 1 \n",
" break \n",
" \n",
" if stop == 0: \n",
" # заполняем столбец текстом запроса\n",
" test_images_df['query_text'] = query_text\n",
" # получаем эмбеддинги \n",
" test_images_df = get_text_embeddings(test_images_df)\n",
" # создаем массив признаков и применяем масштабирование\n",
" features_test = scaler.transform(make_features(test_images_df))\n",
" # приводим матрицу признаков к типу tensor\n",
" X_test_tensor = torch.tensor(features_test, dtype=torch.float32) \n",
" # получаем предсказания\n",
" test_preds = nn_model.forward(X_test_tensor)\n",
" # находим индекс иозображения с наибольшей оценкой\n",
" img_index = np.argsort(test_preds.detach().numpy().ravel())[::-1][0]\n",
" # выводим изображение на экран\n",
" display(Image.open(path + 'test_images/' + test_images_df.loc[img_index, \n",
" 'file_name']).convert('RGB'))\n",
" # выодим текст запроса на экран\n",
" print(query_text)\n",
" # выводим оценку, которую поставила модель, на экран\n",
" print(round(test_preds.detach().numpy().ravel()[img_index], 3))\n",
" \n",
" else:\n",
" # если в запросе есть стоп-слова - выводим дисклеймер\n",
" result = print('This image is unavailable in your country in compliance with local laws.') \n",
" return ''"
]
},
{
"cell_type": "markdown",
"id": "12ad424f",
"metadata": {},
"source": [
"Напечатаем несколько примеров предсказания картинки по тексту."
]
},
{
"cell_type": "markdown",
"id": "62a6a1dc",
"metadata": {},
"source": [
"**1. Нейронная сеть.**"
]
},
{
"cell_type": "code",
"execution_count": 109,
"id": "3a0ad08a",
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "10b71fb63fc046bdbec7b5cb473002e4",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/1 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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\n",
"text/plain": [
"<PIL.Image.Image image mode=RGB size=500x333 at 0x2C9235CC2B0>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"A man with something orange on his helmet riding a bike in a busy setting .\n",
"0.166\n",
"\n"
]
},
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "ab66c1f1d6b94ebd8e1b2e04bbf71b33",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/1 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": 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