filtere.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import csv\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#u novi folder prebacuje slike za koje postoje anotacije u csv fajlu\n",
    "filename = \"mpii_human_pose.csv\"\n",
    "\n",
    "fields = []\n",
    "rows = []\n",
    " \n",
    "with open(filename, 'r') as csvfile:\n",
    "    csvreader = csv.reader(csvfile)\n",
    " \n",
    "    fields = next(csvreader)\n",
    " \n",
    "    for row in csvreader:\n",
    "        rows.append(row)\n",
    " \n",
    "for row in rows[:len(rows)]:\n",
    "    name = row[1]\n",
    "    if os.path.exists(\"images/\"+name):\n",
    "        os.replace(\"images/\"+name, \"images_extract/\"+name)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ucitava inforacije o slikama koje sadrze vise od jedne osobe\n",
    "file1 = open(\"images.txt\",\"r\")\n",
    "b = []\n",
    "lines = file1.readlines()\n",
    "for i in range(len(lines)):\n",
    "    lines[i] = lines[i].rstrip()\n",
    "    #brise slike\n",
    "    if os.path.exists(\"images_extract/\" + i):\n",
    "        os.remove( \"images_extract/\" + i)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# csv fajl cita kao pandas dataframe\n",
    "df = pd.read_csv(filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "#izbacuje sve redove iz tabele koji sadrze indeks slike koja se nalazi u fajlu images.txt\n",
    "df = df.drop(df[df['NAME'].isin(lines)].index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>NAME</th>\n",
       "      <th>r ankle_X</th>\n",
       "      <th>r ankle_Y</th>\n",
       "      <th>r knee_X</th>\n",
       "      <th>r knee_Y</th>\n",
       "      <th>r hip_X</th>\n",
       "      <th>r hip_Y</th>\n",
       "      <th>l hip_X</th>\n",
       "      <th>l hip_Y</th>\n",
       "      <th>...</th>\n",
       "      <th>r shoulder_Y</th>\n",
       "      <th>l shoulder_X</th>\n",
       "      <th>l shoulder_Y</th>\n",
       "      <th>l elbow_X</th>\n",
       "      <th>l elbow_Y</th>\n",
       "      <th>l wrist_X</th>\n",
       "      <th>l wrist_Y</th>\n",
       "      <th>Scale</th>\n",
       "      <th>Activity</th>\n",
       "      <th>Category</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <td>961</td>\n",
       "      <td>223</td>\n",
       "      <td>3.806403</td>\n",
       "      <td>curling</td>\n",
       "      <td>sports</td>\n",
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       "      <th>6</th>\n",
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       "      <td>371</td>\n",
       "      <td>213</td>\n",
       "      <td>396</td>\n",
       "      <td>309</td>\n",
       "      <td>393</td>\n",
       "      <td>290</td>\n",
       "      <td>2.204083</td>\n",
       "      <td>truck driving, loading and unloading truck, ty...</td>\n",
       "      <td>occupation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
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       "      <td>-1</td>\n",
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       "      <td>4.143112</td>\n",
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       "      <td>occupation</td>\n",
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       "      <td>319</td>\n",
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       "      <td>376</td>\n",
       "      <td>39</td>\n",
       "      <td>4.431105</td>\n",
       "      <td>truck driving, loading and unloading truck, ty...</td>\n",
       "      <td>occupation</td>\n",
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       "      <td>050240222.jpg</td>\n",
       "      <td>607</td>\n",
       "      <td>689</td>\n",
       "      <td>599</td>\n",
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       "      <td>691</td>\n",
       "      <td>410</td>\n",
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       "      <td>663</td>\n",
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       "      <td>623</td>\n",
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       "      <td>555</td>\n",
       "      <td>333</td>\n",
       "      <td>3.480000</td>\n",
       "      <td>pushing car</td>\n",
       "      <td>transportation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>17368</td>\n",
       "      <td>033474347.jpg</td>\n",
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       "      <td>815</td>\n",
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       "      <td>779</td>\n",
       "      <td>296</td>\n",
       "      <td>742</td>\n",
       "      <td>303</td>\n",
       "      <td>...</td>\n",
       "      <td>214</td>\n",
       "      <td>663</td>\n",
       "      <td>223</td>\n",
       "      <td>674</td>\n",
       "      <td>286</td>\n",
       "      <td>631</td>\n",
       "      <td>260</td>\n",
       "      <td>2.003677</td>\n",
       "      <td>pushing car</td>\n",
       "      <td>transportation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17368</th>\n",
       "      <td>17369</td>\n",
       "      <td>082650067.jpg</td>\n",
       "      <td>1038</td>\n",
       "      <td>656</td>\n",
       "      <td>950</td>\n",
       "      <td>504</td>\n",
       "      <td>903</td>\n",
       "      <td>328</td>\n",
       "      <td>831</td>\n",
       "      <td>337</td>\n",
       "      <td>...</td>\n",
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       "      <td>220</td>\n",
       "      <td>704</td>\n",
       "      <td>332</td>\n",
       "      <td>675</td>\n",
       "      <td>269</td>\n",
       "      <td>3.235820</td>\n",
       "      <td>pushing car</td>\n",
       "      <td>transportation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17369</th>\n",
       "      <td>17370</td>\n",
       "      <td>072772110.jpg</td>\n",
       "      <td>562</td>\n",
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       "      <td>539</td>\n",
       "      <td>553</td>\n",
       "      <td>452</td>\n",
       "      <td>511</td>\n",
       "      <td>458</td>\n",
       "      <td>...</td>\n",
       "      <td>377</td>\n",
       "      <td>490</td>\n",
       "      <td>378</td>\n",
       "      <td>470</td>\n",
       "      <td>411</td>\n",
       "      <td>461</td>\n",
       "      <td>414</td>\n",
       "      <td>1.494952</td>\n",
       "      <td>pushing car</td>\n",
       "      <td>transportation</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17370</th>\n",
       "      <td>17371</td>\n",
       "      <td>039361034.jpg</td>\n",
       "      <td>496</td>\n",
       "      <td>377</td>\n",
       "      <td>466</td>\n",
       "      <td>322</td>\n",
       "      <td>510</td>\n",
       "      <td>278</td>\n",
       "      <td>540</td>\n",
       "      <td>280</td>\n",
       "      <td>...</td>\n",
       "      <td>253</td>\n",
       "      <td>466</td>\n",
       "      <td>251</td>\n",
       "      <td>436</td>\n",
       "      <td>293</td>\n",
       "      <td>410</td>\n",
       "      <td>325</td>\n",
       "      <td>1.459468</td>\n",
       "      <td>pushing car</td>\n",
       "      <td>transportation</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>11431 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          ID           NAME  r ankle_X  r ankle_Y  r knee_X  r knee_Y  \\\n",
       "4          5  060111501.jpg        980        322       896       318   \n",
       "6          7  002058449.jpg        918        456       659       518   \n",
       "13        14  029122914.jpg         -1         -1       301       473   \n",
       "14        15  061185289.jpg         -1         -1        -1        -1   \n",
       "15        16  013949386.jpg         -1         -1        -1        -1   \n",
       "...      ...            ...        ...        ...       ...       ...   \n",
       "17366  17367  050240222.jpg        607        689       599       542   \n",
       "17367  17368  033474347.jpg        876        461       815       380   \n",
       "17368  17369  082650067.jpg       1038        656       950       504   \n",
       "17369  17370  072772110.jpg        562        617       558       539   \n",
       "17370  17371  039361034.jpg        496        377       466       322   \n",
       "\n",
       "       r hip_X  r hip_Y  l hip_X  l hip_Y  ...  r shoulder_Y  l shoulder_X  \\\n",
       "4          865      248      943      226  ...           147           923   \n",
       "6          713      413      979      288  ...           270           877   \n",
       "13         302      346      362      345  ...           220           371   \n",
       "14          -1       -1       -1       -1  ...           288           552   \n",
       "15         110      385      208      355  ...           303           212   \n",
       "...        ...      ...      ...      ...  ...           ...           ...   \n",
       "17366      605      416      691      410  ...           232           663   \n",
       "17367      779      296      742      303  ...           214           663   \n",
       "17368      903      328      831      337  ...           204           729   \n",
       "17369      553      452      511      458  ...           377           490   \n",
       "17370      510      278      540      280  ...           253           466   \n",
       "\n",
       "       l shoulder_Y  l elbow_X  l elbow_Y  l wrist_X  l wrist_Y     Scale  \\\n",
       "4               123        995        163        961        223  3.806403   \n",
       "6               247       1112        384       1012        489  8.280870   \n",
       "13              213        396        309        393        290  2.204083   \n",
       "14              355         -1         -1         -1         -1  4.143112   \n",
       "15              153        319        123        376         39  4.431105   \n",
       "...             ...        ...        ...        ...        ...       ...   \n",
       "17366           228        623        289        555        333  3.480000   \n",
       "17367           223        674        286        631        260  2.003677   \n",
       "17368           220        704        332        675        269  3.235820   \n",
       "17369           378        470        411        461        414  1.494952   \n",
       "17370           251        436        293        410        325  1.459468   \n",
       "\n",
       "                                                Activity        Category  \n",
       "4                                                curling          sports  \n",
       "6                                                curling          sports  \n",
       "13     truck driving, loading and unloading truck, ty...      occupation  \n",
       "14     truck driving, loading and unloading truck, ty...      occupation  \n",
       "15     truck driving, loading and unloading truck, ty...      occupation  \n",
       "...                                                  ...             ...  \n",
       "17366                                        pushing car  transportation  \n",
       "17367                                        pushing car  transportation  \n",
       "17368                                        pushing car  transportation  \n",
       "17369                                        pushing car  transportation  \n",
       "17370                                        pushing car  transportation  \n",
       "\n",
       "[11431 rows x 37 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "#konvertuje df u csv i cuva ga\n",
    "x = df.to_csv('mpii_new.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from PIL import Image\n",
    "\n",
    "#Funkcija za pravljenje padding-a\n",
    "def make_square(im, min_size=256, fill_color=(0, 0, 0, 255)):\n",
    "    x, y = im.size\n",
    "    size = max(min_size, x, y)\n",
    "    new_im = Image.new('RGBA', (size, size), fill_color)\n",
    "    new_im.paste(im, (0, 0))\n",
    "    return new_im\n",
    "\n",
    "image_path = \"images_extract/000234747.jpg\"\n",
    "im = Image.open(image_path)\n",
    "make_square(im).show()\n"
   ]
  }
 ],
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