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cifar10_part2_inference_at_local.ipynb
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| { | |
| "nbformat": 4, | |
| "nbformat_minor": 0, | |
| "metadata": { | |
| "colab": { | |
| "name": "cifar10_part2_inference_at_local.ipynb", | |
| "version": "0.3.2", | |
| "provenance": [], | |
| "collapsed_sections": [], | |
| "toc_visible": true, | |
| "include_colab_link": true | |
| }, | |
| "kernelspec": { | |
| "display_name": "Python 3", | |
| "language": "python", | |
| "name": "python3" | |
| }, | |
| "accelerator": "GPU" | |
| }, | |
| "cells": [ | |
| { | |
| "cell_type": "markdown", | |
| "metadata": { | |
| "id": "view-in-github", | |
| "colab_type": "text" | |
| }, | |
| "source": [ | |
| "<a href=\"https://colab.research.google.com/gist/x1001000/3f99cfd5eaae885d4fcae5bdde29fb7a/cifar10_part2_inference_at_local.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>" | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "colab_type": "text", | |
| "id": "W149WvAduEEJ" | |
| }, | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Kaggle" | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "colab_type": "text", | |
| "id": "4ZtvmbWB6-G6" | |
| }, | |
| "cell_type": "markdown", | |
| "source": [ | |
| "- 競賽方式：詳讀題目敘述，自行訓練模型，下載測試資料給模型推論，上傳推論結果給Kaggle評分\n", | |
| "\n", | |
| "- https://www.kaggle.com/c/cifar-10 是沒有獎金的練習題，題目敘述重點有二：\n", | |
| "> 1. [CIFAR-10](https://www.cs.toronto.edu/~kriz/cifar.html) is an established computer-vision dataset used for object recognition.\n", | |
| "> 2. Kaggle is hosting a CIFAR-10 leaderboard for the machine learning community to use for fun and practice. You can see how your approach compares to the latest research methods on Rodrigo Benenson's [classification results page](http://rodrigob.github.io/are_we_there_yet/build/classification_datasets_results.html).\n", | |
| "\n", | |
| "- 這題的訓練資料train.7z及其標記trainLabels.csv，就是CIFAR-10的5萬張圖，測試資料test.7z是Kaggle準備的30萬張圖\n", | |
| "\n", | |
| "- 因為在Colab上解壓縮test.7z或上傳30萬個檔案都非常耗時，又因為Inference不像Training那麼需要GPU算力，故這個ipynb寫的是在本機上推論的程序\n", | |
| "\n", | |
| "- 將cifar10_part2_inference_at_local.ipynb和test.7z放在同一個工作目錄，將test.7z解壓縮，不要點進有30萬個檔案的資料夾以免當機\n", | |
| "\n", | |
| "- 開Terminal或Cmd，pip安裝或更新所需的各種套件，執行`jupyter notebook`，在瀏覽器打開這個ipynb\n", | |
| "\n", | |
| "- 首先，匯入三個基本函式庫" | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "6XaLQJu_fICP", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "cell_type": "code", | |
| "source": [ | |
| "import numpy as np\n", | |
| "import pandas as pd\n", | |
| "import matplotlib.pyplot as plt" | |
| ], | |
| "execution_count": 1, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "GAIlCDC8fICT", | |
| "colab_type": "text" | |
| }, | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Inference" | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "omqgdhrAfICU", | |
| "colab_type": "text" | |
| }, | |
| "cell_type": "markdown", | |
| "source": [ | |
| "- 將cifar10_params_model.h5放在同一個工作目錄\n", | |
| "\n", | |
| "- 匯入之前訓練好的model" | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "j5qHJx-qfICV", | |
| "colab_type": "code", | |
| "colab": {}, | |
| "outputId": "b165702f-56d3-4896-f93a-2a76d9180776" | |
| }, | |
| "cell_type": "code", | |
| "source": [ | |
| "from keras.models import load_model\n", | |
| "model = load_model('cifar10_params_model.h5')" | |
| ], | |
| "execution_count": 2, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "Using TensorFlow backend.\n" | |
| ], | |
| "name": "stderr" | |
| } | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "R7N5tYpNfICa", | |
| "colab_type": "text" | |
| }, | |
| "cell_type": "markdown", | |
| "source": [ | |
| "- 用匯入的模型/神經網路做推論/預測\n", | |
| "\n", | |
| "- 將30萬張圖的分類(0~9)結果記在prediction串列\n", | |
| "\n", | |
| "- 先用註解掉的那行估算時間" | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "KXDqy_IUfICc", | |
| "colab_type": "code", | |
| "colab": {}, | |
| "outputId": "547c8b11-de99-4d7c-b451-04c431685b44" | |
| }, | |
| "cell_type": "code", | |
| "source": [ | |
| "from time import time\n", | |
| "start = time()\n", | |
| "prediction = []\n", | |
| "for i in range(1, 300001):\n", | |
| " im = plt.imread('test/%d.png'%i)\n", | |
| " prediction.append(model.predict_classes(im.reshape(1, 32, 32, 3))[0])\n", | |
| " #if i%1000 == 0: print(i)\n", | |
| "print('It took', (time()-start)/60, 'minutes')" | |
| ], | |
| "execution_count": 3, | |
| "outputs": [ | |
| { | |
| "output_type": "stream", | |
| "text": [ | |
| "It took 35.930204304059345 minutes\n" | |
| ], | |
| "name": "stdout" | |
| } | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "x7PyMjijfICi", | |
| "colab_type": "text" | |
| }, | |
| "cell_type": "markdown", | |
| "source": [ | |
| "# Submission" | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "TI1hhd6EfICj", | |
| "colab_type": "text" | |
| }, | |
| "cell_type": "markdown", | |
| "source": [ | |
| "- 將sampleSubmission.csv放在同一個工作目錄\n", | |
| "- 看看提交的範例格式" | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "C1E5mbI_fICk", | |
| "colab_type": "code", | |
| "colab": {}, | |
| "outputId": "45f3fcfb-52b7-41e8-dafa-af643cd20a8d" | |
| }, | |
| "cell_type": "code", | |
| "source": [ | |
| "submission = pd.read_csv('sampleSubmission.csv')\n", | |
| "submission" | |
| ], | |
| "execution_count": 4, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "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>id</th>\n", | |
| " <th>label</th>\n", | |
| " </tr>\n", | |
| " </thead>\n", | |
| " <tbody>\n", | |
| " <tr>\n", | |
| " <th>0</th>\n", | |
| " <td>1</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>1</th>\n", | |
| " <td>2</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>2</th>\n", | |
| " <td>3</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>3</th>\n", | |
| " <td>4</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>4</th>\n", | |
| " <td>5</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>5</th>\n", | |
| " <td>6</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>6</th>\n", | |
| " <td>7</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>7</th>\n", | |
| " <td>8</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>8</th>\n", | |
| " <td>9</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>9</th>\n", | |
| " <td>10</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>10</th>\n", | |
| " <td>11</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>11</th>\n", | |
| " <td>12</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>12</th>\n", | |
| " <td>13</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>13</th>\n", | |
| " <td>14</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>14</th>\n", | |
| " <td>15</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>15</th>\n", | |
| " <td>16</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>16</th>\n", | |
| " <td>17</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>17</th>\n", | |
| " <td>18</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>18</th>\n", | |
| " <td>19</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>19</th>\n", | |
| " <td>20</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>20</th>\n", | |
| " <td>21</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>21</th>\n", | |
| " <td>22</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>22</th>\n", | |
| " <td>23</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>23</th>\n", | |
| " <td>24</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>24</th>\n", | |
| " <td>25</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>25</th>\n", | |
| " <td>26</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>26</th>\n", | |
| " <td>27</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>27</th>\n", | |
| " <td>28</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>28</th>\n", | |
| " <td>29</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>29</th>\n", | |
| " <td>30</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>...</th>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299970</th>\n", | |
| " <td>299971</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299971</th>\n", | |
| " <td>299972</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299972</th>\n", | |
| " <td>299973</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299973</th>\n", | |
| " <td>299974</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299974</th>\n", | |
| " <td>299975</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299975</th>\n", | |
| " <td>299976</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299976</th>\n", | |
| " <td>299977</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299977</th>\n", | |
| " <td>299978</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299978</th>\n", | |
| " <td>299979</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299979</th>\n", | |
| " <td>299980</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299980</th>\n", | |
| " <td>299981</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299981</th>\n", | |
| " <td>299982</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299982</th>\n", | |
| " <td>299983</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299983</th>\n", | |
| " <td>299984</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299984</th>\n", | |
| " <td>299985</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299985</th>\n", | |
| " <td>299986</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299986</th>\n", | |
| " <td>299987</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299987</th>\n", | |
| " <td>299988</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299988</th>\n", | |
| " <td>299989</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299989</th>\n", | |
| " <td>299990</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299990</th>\n", | |
| " <td>299991</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299991</th>\n", | |
| " <td>299992</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299992</th>\n", | |
| " <td>299993</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299993</th>\n", | |
| " <td>299994</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299994</th>\n", | |
| " <td>299995</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299995</th>\n", | |
| " <td>299996</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299996</th>\n", | |
| " <td>299997</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299997</th>\n", | |
| " <td>299998</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299998</th>\n", | |
| " <td>299999</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299999</th>\n", | |
| " <td>300000</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>300000 rows × 2 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " id label\n", | |
| "0 1 cat\n", | |
| "1 2 cat\n", | |
| "2 3 cat\n", | |
| "3 4 cat\n", | |
| "4 5 cat\n", | |
| "5 6 cat\n", | |
| "6 7 cat\n", | |
| "7 8 cat\n", | |
| "8 9 cat\n", | |
| "9 10 cat\n", | |
| "10 11 cat\n", | |
| "11 12 cat\n", | |
| "12 13 cat\n", | |
| "13 14 cat\n", | |
| "14 15 cat\n", | |
| "15 16 cat\n", | |
| "16 17 cat\n", | |
| "17 18 cat\n", | |
| "18 19 cat\n", | |
| "19 20 cat\n", | |
| "20 21 cat\n", | |
| "21 22 cat\n", | |
| "22 23 cat\n", | |
| "23 24 cat\n", | |
| "24 25 cat\n", | |
| "25 26 cat\n", | |
| "26 27 cat\n", | |
| "27 28 cat\n", | |
| "28 29 cat\n", | |
| "29 30 cat\n", | |
| "... ... ...\n", | |
| "299970 299971 cat\n", | |
| "299971 299972 cat\n", | |
| "299972 299973 cat\n", | |
| "299973 299974 cat\n", | |
| "299974 299975 cat\n", | |
| "299975 299976 cat\n", | |
| "299976 299977 cat\n", | |
| "299977 299978 cat\n", | |
| "299978 299979 cat\n", | |
| "299979 299980 cat\n", | |
| "299980 299981 cat\n", | |
| "299981 299982 cat\n", | |
| "299982 299983 cat\n", | |
| "299983 299984 cat\n", | |
| "299984 299985 cat\n", | |
| "299985 299986 cat\n", | |
| "299986 299987 cat\n", | |
| "299987 299988 cat\n", | |
| "299988 299989 cat\n", | |
| "299989 299990 cat\n", | |
| "299990 299991 cat\n", | |
| "299991 299992 cat\n", | |
| "299992 299993 cat\n", | |
| "299993 299994 cat\n", | |
| "299994 299995 cat\n", | |
| "299995 299996 cat\n", | |
| "299996 299997 cat\n", | |
| "299997 299998 cat\n", | |
| "299998 299999 cat\n", | |
| "299999 300000 cat\n", | |
| "\n", | |
| "[300000 rows x 2 columns]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 4 | |
| } | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "Wc_gVQNGfICn", | |
| "colab_type": "text" | |
| }, | |
| "cell_type": "markdown", | |
| "source": [ | |
| "- 準備要查的字典" | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "kjfqenKYfICp", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "cell_type": "code", | |
| "source": [ | |
| "thing = {0:\"airplane\", 1:\"automobile\", 2:\"bird\", 3:\"cat\", 4:\"deer\", 5:\"dog\", 6:\"frog\", 7:\"horse\", 8:\"ship\", 9:\"truck\"}" | |
| ], | |
| "execution_count": 5, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "bJsLN7_WfICt", | |
| "colab_type": "text" | |
| }, | |
| "cell_type": "markdown", | |
| "source": [ | |
| "- 用數字翻譯成英文的串列建DataFrame" | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "TKtmWSHZfICu", | |
| "colab_type": "code", | |
| "colab": {}, | |
| "outputId": "b9959532-0c3f-400f-f0e5-64f1a2561625" | |
| }, | |
| "cell_type": "code", | |
| "source": [ | |
| "df = pd.DataFrame([ thing[prediction[i]] for i in range(300000) ])\n", | |
| "df" | |
| ], | |
| "execution_count": 6, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "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", | |
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| "\n", | |
| " .dataframe thead th {\n", | |
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| "<table border=\"1\" class=\"dataframe\">\n", | |
| " <thead>\n", | |
| " <tr style=\"text-align: right;\">\n", | |
| " <th></th>\n", | |
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| " <td>automobile</td>\n", | |
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| " <th>8</th>\n", | |
| " <td>cat</td>\n", | |
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| " <th>9</th>\n", | |
| " <td>horse</td>\n", | |
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| " <td>cat</td>\n", | |
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| " <th>15</th>\n", | |
| " <td>airplane</td>\n", | |
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| " <th>16</th>\n", | |
| " <td>deer</td>\n", | |
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| " <th>17</th>\n", | |
| " <td>deer</td>\n", | |
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| " <th>18</th>\n", | |
| " <td>airplane</td>\n", | |
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| " <tr>\n", | |
| " <th>19</th>\n", | |
| " <td>frog</td>\n", | |
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| " <td>airplane</td>\n", | |
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| " <th>21</th>\n", | |
| " <td>ship</td>\n", | |
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| " <tr>\n", | |
| " <th>22</th>\n", | |
| " <td>frog</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>23</th>\n", | |
| " <td>automobile</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>24</th>\n", | |
| " <td>bird</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>25</th>\n", | |
| " <td>truck</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>26</th>\n", | |
| " <td>automobile</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>27</th>\n", | |
| " <td>dog</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>28</th>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>29</th>\n", | |
| " <td>dog</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>...</th>\n", | |
| " <td>...</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299970</th>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299971</th>\n", | |
| " <td>bird</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299972</th>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299973</th>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299974</th>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299975</th>\n", | |
| " <td>dog</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299976</th>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299977</th>\n", | |
| " <td>frog</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299978</th>\n", | |
| " <td>horse</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299979</th>\n", | |
| " <td>airplane</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299980</th>\n", | |
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| " <tr>\n", | |
| " <th>299981</th>\n", | |
| " <td>frog</td>\n", | |
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| " <tr>\n", | |
| " <th>299982</th>\n", | |
| " <td>deer</td>\n", | |
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| " <tr>\n", | |
| " <th>299983</th>\n", | |
| " <td>frog</td>\n", | |
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| " <tr>\n", | |
| " <th>299984</th>\n", | |
| " <td>frog</td>\n", | |
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| " <tr>\n", | |
| " <th>299985</th>\n", | |
| " <td>cat</td>\n", | |
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| " <tr>\n", | |
| " <th>299986</th>\n", | |
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| " <tr>\n", | |
| " <th>299987</th>\n", | |
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| " <tr>\n", | |
| " <th>299988</th>\n", | |
| " <td>deer</td>\n", | |
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| " <th>299989</th>\n", | |
| " <td>cat</td>\n", | |
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| " <tr>\n", | |
| " <th>299990</th>\n", | |
| " <td>ship</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299991</th>\n", | |
| " <td>truck</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299992</th>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299993</th>\n", | |
| " <td>bird</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299994</th>\n", | |
| " <td>airplane</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299995</th>\n", | |
| " <td>automobile</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299996</th>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299997</th>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299998</th>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299999</th>\n", | |
| " <td>automobile</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>300000 rows × 1 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " 0\n", | |
| "0 deer\n", | |
| "1 airplane\n", | |
| "2 automobile\n", | |
| "3 ship\n", | |
| "4 bird\n", | |
| "5 cat\n", | |
| "6 airplane\n", | |
| "7 deer\n", | |
| "8 cat\n", | |
| "9 horse\n", | |
| "10 bird\n", | |
| "11 ship\n", | |
| "12 cat\n", | |
| "13 ship\n", | |
| "14 cat\n", | |
| "15 airplane\n", | |
| "16 deer\n", | |
| "17 deer\n", | |
| "18 airplane\n", | |
| "19 frog\n", | |
| "20 airplane\n", | |
| "21 ship\n", | |
| "22 frog\n", | |
| "23 automobile\n", | |
| "24 bird\n", | |
| "25 truck\n", | |
| "26 automobile\n", | |
| "27 dog\n", | |
| "28 cat\n", | |
| "29 dog\n", | |
| "... ...\n", | |
| "299970 deer\n", | |
| "299971 bird\n", | |
| "299972 deer\n", | |
| "299973 deer\n", | |
| "299974 cat\n", | |
| "299975 dog\n", | |
| "299976 deer\n", | |
| "299977 frog\n", | |
| "299978 horse\n", | |
| "299979 airplane\n", | |
| "299980 cat\n", | |
| "299981 frog\n", | |
| "299982 deer\n", | |
| "299983 frog\n", | |
| "299984 frog\n", | |
| "299985 cat\n", | |
| "299986 bird\n", | |
| "299987 deer\n", | |
| "299988 deer\n", | |
| "299989 cat\n", | |
| "299990 ship\n", | |
| "299991 truck\n", | |
| "299992 cat\n", | |
| "299993 bird\n", | |
| "299994 airplane\n", | |
| "299995 automobile\n", | |
| "299996 deer\n", | |
| "299997 deer\n", | |
| "299998 cat\n", | |
| "299999 automobile\n", | |
| "\n", | |
| "[300000 rows x 1 columns]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 6 | |
| } | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "objdjScWfIC0", | |
| "colab_type": "text" | |
| }, | |
| "cell_type": "markdown", | |
| "source": [ | |
| "- submission的label那欄更新為df" | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "n5FUL491fIC1", | |
| "colab_type": "code", | |
| "colab": {}, | |
| "outputId": "9f7e7735-8269-426d-ccf2-7158018f7629" | |
| }, | |
| "cell_type": "code", | |
| "source": [ | |
| "submission['label'] = df\n", | |
| "submission" | |
| ], | |
| "execution_count": 7, | |
| "outputs": [ | |
| { | |
| "output_type": "execute_result", | |
| "data": { | |
| "text/html": [ | |
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| " <td>horse</td>\n", | |
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| " <td>deer</td>\n", | |
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| " <th>17</th>\n", | |
| " <td>18</td>\n", | |
| " <td>deer</td>\n", | |
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| " <th>18</th>\n", | |
| " <td>19</td>\n", | |
| " <td>airplane</td>\n", | |
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| " <tr>\n", | |
| " <th>19</th>\n", | |
| " <td>20</td>\n", | |
| " <td>frog</td>\n", | |
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| " <th>20</th>\n", | |
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| " <td>airplane</td>\n", | |
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| " <th>21</th>\n", | |
| " <td>22</td>\n", | |
| " <td>ship</td>\n", | |
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| " <tr>\n", | |
| " <th>22</th>\n", | |
| " <td>23</td>\n", | |
| " <td>frog</td>\n", | |
| " </tr>\n", | |
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| " <th>23</th>\n", | |
| " <td>24</td>\n", | |
| " <td>automobile</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>24</th>\n", | |
| " <td>25</td>\n", | |
| " <td>bird</td>\n", | |
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| " <tr>\n", | |
| " <th>25</th>\n", | |
| " <td>26</td>\n", | |
| " <td>truck</td>\n", | |
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| " <th>26</th>\n", | |
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| " <td>automobile</td>\n", | |
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| " <th>27</th>\n", | |
| " <td>28</td>\n", | |
| " <td>dog</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>28</th>\n", | |
| " <td>29</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>29</th>\n", | |
| " <td>30</td>\n", | |
| " <td>dog</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>...</th>\n", | |
| " <td>...</td>\n", | |
| " <td>...</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299970</th>\n", | |
| " <td>299971</td>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299971</th>\n", | |
| " <td>299972</td>\n", | |
| " <td>bird</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299972</th>\n", | |
| " <td>299973</td>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299973</th>\n", | |
| " <td>299974</td>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299974</th>\n", | |
| " <td>299975</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299975</th>\n", | |
| " <td>299976</td>\n", | |
| " <td>dog</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299976</th>\n", | |
| " <td>299977</td>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299977</th>\n", | |
| " <td>299978</td>\n", | |
| " <td>frog</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299978</th>\n", | |
| " <td>299979</td>\n", | |
| " <td>horse</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299979</th>\n", | |
| " <td>299980</td>\n", | |
| " <td>airplane</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299980</th>\n", | |
| " <td>299981</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299981</th>\n", | |
| " <td>299982</td>\n", | |
| " <td>frog</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299982</th>\n", | |
| " <td>299983</td>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299983</th>\n", | |
| " <td>299984</td>\n", | |
| " <td>frog</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299984</th>\n", | |
| " <td>299985</td>\n", | |
| " <td>frog</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299985</th>\n", | |
| " <td>299986</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299986</th>\n", | |
| " <td>299987</td>\n", | |
| " <td>bird</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299987</th>\n", | |
| " <td>299988</td>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299988</th>\n", | |
| " <td>299989</td>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299989</th>\n", | |
| " <td>299990</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299990</th>\n", | |
| " <td>299991</td>\n", | |
| " <td>ship</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299991</th>\n", | |
| " <td>299992</td>\n", | |
| " <td>truck</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299992</th>\n", | |
| " <td>299993</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299993</th>\n", | |
| " <td>299994</td>\n", | |
| " <td>bird</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299994</th>\n", | |
| " <td>299995</td>\n", | |
| " <td>airplane</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299995</th>\n", | |
| " <td>299996</td>\n", | |
| " <td>automobile</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299996</th>\n", | |
| " <td>299997</td>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299997</th>\n", | |
| " <td>299998</td>\n", | |
| " <td>deer</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299998</th>\n", | |
| " <td>299999</td>\n", | |
| " <td>cat</td>\n", | |
| " </tr>\n", | |
| " <tr>\n", | |
| " <th>299999</th>\n", | |
| " <td>300000</td>\n", | |
| " <td>automobile</td>\n", | |
| " </tr>\n", | |
| " </tbody>\n", | |
| "</table>\n", | |
| "<p>300000 rows × 2 columns</p>\n", | |
| "</div>" | |
| ], | |
| "text/plain": [ | |
| " id label\n", | |
| "0 1 deer\n", | |
| "1 2 airplane\n", | |
| "2 3 automobile\n", | |
| "3 4 ship\n", | |
| "4 5 bird\n", | |
| "5 6 cat\n", | |
| "6 7 airplane\n", | |
| "7 8 deer\n", | |
| "8 9 cat\n", | |
| "9 10 horse\n", | |
| "10 11 bird\n", | |
| "11 12 ship\n", | |
| "12 13 cat\n", | |
| "13 14 ship\n", | |
| "14 15 cat\n", | |
| "15 16 airplane\n", | |
| "16 17 deer\n", | |
| "17 18 deer\n", | |
| "18 19 airplane\n", | |
| "19 20 frog\n", | |
| "20 21 airplane\n", | |
| "21 22 ship\n", | |
| "22 23 frog\n", | |
| "23 24 automobile\n", | |
| "24 25 bird\n", | |
| "25 26 truck\n", | |
| "26 27 automobile\n", | |
| "27 28 dog\n", | |
| "28 29 cat\n", | |
| "29 30 dog\n", | |
| "... ... ...\n", | |
| "299970 299971 deer\n", | |
| "299971 299972 bird\n", | |
| "299972 299973 deer\n", | |
| "299973 299974 deer\n", | |
| "299974 299975 cat\n", | |
| "299975 299976 dog\n", | |
| "299976 299977 deer\n", | |
| "299977 299978 frog\n", | |
| "299978 299979 horse\n", | |
| "299979 299980 airplane\n", | |
| "299980 299981 cat\n", | |
| "299981 299982 frog\n", | |
| "299982 299983 deer\n", | |
| "299983 299984 frog\n", | |
| "299984 299985 frog\n", | |
| "299985 299986 cat\n", | |
| "299986 299987 bird\n", | |
| "299987 299988 deer\n", | |
| "299988 299989 deer\n", | |
| "299989 299990 cat\n", | |
| "299990 299991 ship\n", | |
| "299991 299992 truck\n", | |
| "299992 299993 cat\n", | |
| "299993 299994 bird\n", | |
| "299994 299995 airplane\n", | |
| "299995 299996 automobile\n", | |
| "299996 299997 deer\n", | |
| "299997 299998 deer\n", | |
| "299998 299999 cat\n", | |
| "299999 300000 automobile\n", | |
| "\n", | |
| "[300000 rows x 2 columns]" | |
| ] | |
| }, | |
| "metadata": { | |
| "tags": [] | |
| }, | |
| "execution_count": 7 | |
| } | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "vdqSPpbWfIC5", | |
| "colab_type": "text" | |
| }, | |
| "cell_type": "markdown", | |
| "source": [ | |
| "- submission輸出成csv檔，不包含index欄" | |
| ] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "QLm_AMzrfIC7", | |
| "colab_type": "code", | |
| "colab": {} | |
| }, | |
| "cell_type": "code", | |
| "source": [ | |
| "submission.to_csv('submission.csv', index=False)" | |
| ], | |
| "execution_count": 8, | |
| "outputs": [] | |
| }, | |
| { | |
| "metadata": { | |
| "id": "5rYIUzbVfIC9", | |
| "colab_type": "text" | |
| }, | |
| "cell_type": "markdown", | |
| "source": [ | |
| "- 上傳，送出，得分0.77970" | |
| ] | |
| } | |
| ] | |
| } |
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