convert_pc_to_depth.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "from pyntcloud import PyntCloud\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from perception import DepthImage, CameraIntrinsics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "## Set the camera intrinsics\n",
    "# Kinect parameters from NYU dataset, used to be close to my kinect data\n",
    "\n",
    "# Depth Intrinsic Parameters\n",
    "fx_d = 5.8262448167737955e+02;\n",
    "fy_d = 5.8269103270988637e+02;\n",
    "cx_d = 3.1304475870804731e+02;\n",
    "cy_d = 2.3844389626620386e+02;\n",
    "\n",
    "# RGB Distortion Parameters\n",
    "k1_d = -9.9897236553084481e-02;\n",
    "k2_d = 3.9065324602765344e-01;\n",
    "p1_d = 1.9290592870229277e-03;\n",
    "p2_d = -1.9422022475975055e-03;\n",
    "k3_d = -5.1031725053400578e-01;\n",
    "\n",
    "# % 3D Translation\n",
    "t_x = -1500;\n",
    "t_z = -800;\n",
    "t_y = -500;\n",
    "\n",
    "intrinsics = CameraIntrinsics(\"kinect\", fx=fx_d, fy=fy_d, cx=cx_d, cy=cy_d, skew=0.0, height=480, width=620)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "base_dir = \"/Users/stephenhansen/Code/grasping_cornell_dataset/data/\"\n",
    "cloud = PyntCloud.from_file(base_dir+\"point_cloud/pcd0100.pcd\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>x</th>\n",
       "      <th>y</th>\n",
       "      <th>z</th>\n",
       "      <th>rgb</th>\n",
       "      <th>index</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1924.063965</td>\n",
       "      <td>-647.111023</td>\n",
       "      <td>-119.417603</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1924.411987</td>\n",
       "      <td>-649.677979</td>\n",
       "      <td>-119.714699</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1919.928955</td>\n",
       "      <td>-650.559082</td>\n",
       "      <td>-116.983902</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1920.276001</td>\n",
       "      <td>-653.116577</td>\n",
       "      <td>-117.279900</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1920.621948</td>\n",
       "      <td>-655.674072</td>\n",
       "      <td>-117.575996</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25551</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1916.134033</td>\n",
       "      <td>-656.517822</td>\n",
       "      <td>-114.840797</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1916.479980</td>\n",
       "      <td>-659.065918</td>\n",
       "      <td>-115.135803</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25553</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1911.020020</td>\n",
       "      <td>-659.534729</td>\n",
       "      <td>-111.790703</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1911.364014</td>\n",
       "      <td>-662.071716</td>\n",
       "      <td>-112.084396</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25555</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1707.098022</td>\n",
       "      <td>829.543579</td>\n",
       "      <td>59.061298</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1707.441040</td>\n",
       "      <td>827.006714</td>\n",
       "      <td>58.767639</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1707.785034</td>\n",
       "      <td>824.469788</td>\n",
       "      <td>58.473980</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25609</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1721.208008</td>\n",
       "      <td>833.919922</td>\n",
       "      <td>50.484982</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1721.556030</td>\n",
       "      <td>831.353027</td>\n",
       "      <td>50.187851</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1721.902954</td>\n",
       "      <td>828.786011</td>\n",
       "      <td>49.890709</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1722.250977</td>\n",
       "      <td>826.219116</td>\n",
       "      <td>49.593571</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1727.510010</td>\n",
       "      <td>828.102295</td>\n",
       "      <td>46.405418</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1722.947021</td>\n",
       "      <td>821.085083</td>\n",
       "      <td>48.999290</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1723.295044</td>\n",
       "      <td>818.518188</td>\n",
       "      <td>48.702148</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1723.642944</td>\n",
       "      <td>815.951172</td>\n",
       "      <td>48.405010</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25617</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1723.990967</td>\n",
       "      <td>813.384277</td>\n",
       "      <td>48.107868</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1724.338989</td>\n",
       "      <td>810.817383</td>\n",
       "      <td>47.810730</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1724.687012</td>\n",
       "      <td>808.250427</td>\n",
       "      <td>47.513592</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1725.035034</td>\n",
       "      <td>805.683472</td>\n",
       "      <td>47.216450</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1725.383057</td>\n",
       "      <td>803.116516</td>\n",
       "      <td>46.919312</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1730.655029</td>\n",
       "      <td>804.898376</td>\n",
       "      <td>43.719440</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1731.005005</td>\n",
       "      <td>802.320190</td>\n",
       "      <td>43.420990</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1731.354004</td>\n",
       "      <td>799.742004</td>\n",
       "      <td>43.122551</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1731.703979</td>\n",
       "      <td>797.163818</td>\n",
       "      <td>42.824100</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1736.161987</td>\n",
       "      <td>798.172119</td>\n",
       "      <td>40.102409</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>25627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253644</th>\n",
       "      <td>721.810608</td>\n",
       "      <td>239.279205</td>\n",
       "      <td>-0.178309</td>\n",
       "      <td>2.083118e-38</td>\n",
       "      <td>305992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253645</th>\n",
       "      <td>709.068176</td>\n",
       "      <td>343.320099</td>\n",
       "      <td>0.457740</td>\n",
       "      <td>1.972553e-38</td>\n",
       "      <td>306560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253646</th>\n",
       "      <td>709.252808</td>\n",
       "      <td>341.957794</td>\n",
       "      <td>0.300048</td>\n",
       "      <td>1.972517e-38</td>\n",
       "      <td>306561</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253647</th>\n",
       "      <td>709.437500</td>\n",
       "      <td>340.595490</td>\n",
       "      <td>0.142355</td>\n",
       "      <td>2.000141e-38</td>\n",
       "      <td>306562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253648</th>\n",
       "      <td>709.622070</td>\n",
       "      <td>339.233185</td>\n",
       "      <td>-0.015337</td>\n",
       "      <td>2.027763e-38</td>\n",
       "      <td>306563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253649</th>\n",
       "      <td>710.101013</td>\n",
       "      <td>339.327911</td>\n",
       "      <td>-2.125181</td>\n",
       "      <td>2.009432e-38</td>\n",
       "      <td>306564</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253650</th>\n",
       "      <td>710.286194</td>\n",
       "      <td>337.961792</td>\n",
       "      <td>-2.283309</td>\n",
       "      <td>2.000284e-38</td>\n",
       "      <td>306565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253651</th>\n",
       "      <td>710.471375</td>\n",
       "      <td>336.595795</td>\n",
       "      <td>-2.441436</td>\n",
       "      <td>2.009396e-38</td>\n",
       "      <td>306566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253652</th>\n",
       "      <td>710.360779</td>\n",
       "      <td>333.784088</td>\n",
       "      <td>-0.646107</td>\n",
       "      <td>2.027799e-38</td>\n",
       "      <td>306567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253653</th>\n",
       "      <td>710.545471</td>\n",
       "      <td>332.421814</td>\n",
       "      <td>-0.803799</td>\n",
       "      <td>2.018616e-38</td>\n",
       "      <td>306568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253654</th>\n",
       "      <td>711.026917</td>\n",
       "      <td>332.497711</td>\n",
       "      <td>-2.915818</td>\n",
       "      <td>2.009432e-38</td>\n",
       "      <td>306569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253655</th>\n",
       "      <td>711.806580</td>\n",
       "      <td>334.000397</td>\n",
       "      <td>-6.983346</td>\n",
       "      <td>2.009396e-38</td>\n",
       "      <td>306570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253656</th>\n",
       "      <td>711.992798</td>\n",
       "      <td>332.626892</td>\n",
       "      <td>-7.142339</td>\n",
       "      <td>2.018579e-38</td>\n",
       "      <td>306571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253657</th>\n",
       "      <td>712.477173</td>\n",
       "      <td>332.680206</td>\n",
       "      <td>-9.256886</td>\n",
       "      <td>2.009360e-38</td>\n",
       "      <td>306572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253658</th>\n",
       "      <td>712.663879</td>\n",
       "      <td>331.302887</td>\n",
       "      <td>-9.416316</td>\n",
       "      <td>2.000141e-38</td>\n",
       "      <td>306573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253659</th>\n",
       "      <td>713.150024</td>\n",
       "      <td>331.345001</td>\n",
       "      <td>-11.532230</td>\n",
       "      <td>2.000141e-38</td>\n",
       "      <td>306574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253660</th>\n",
       "      <td>713.037415</td>\n",
       "      <td>328.548309</td>\n",
       "      <td>-9.735177</td>\n",
       "      <td>2.009325e-38</td>\n",
       "      <td>306575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253661</th>\n",
       "      <td>713.224121</td>\n",
       "      <td>327.170990</td>\n",
       "      <td>-9.894607</td>\n",
       "      <td>2.000141e-38</td>\n",
       "      <td>306576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253662</th>\n",
       "      <td>713.410706</td>\n",
       "      <td>325.793701</td>\n",
       "      <td>-10.054040</td>\n",
       "      <td>2.000140e-38</td>\n",
       "      <td>306577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253663</th>\n",
       "      <td>713.597412</td>\n",
       "      <td>324.416412</td>\n",
       "      <td>-10.213470</td>\n",
       "      <td>2.009359e-38</td>\n",
       "      <td>306578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253664</th>\n",
       "      <td>713.784119</td>\n",
       "      <td>323.039093</td>\n",
       "      <td>-10.372900</td>\n",
       "      <td>2.018507e-38</td>\n",
       "      <td>306579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253665</th>\n",
       "      <td>713.668518</td>\n",
       "      <td>320.265015</td>\n",
       "      <td>-8.573302</td>\n",
       "      <td>2.036911e-38</td>\n",
       "      <td>306580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253666</th>\n",
       "      <td>713.854675</td>\n",
       "      <td>318.891388</td>\n",
       "      <td>-8.732297</td>\n",
       "      <td>2.055385e-38</td>\n",
       "      <td>306581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253667</th>\n",
       "      <td>714.040771</td>\n",
       "      <td>317.517914</td>\n",
       "      <td>-8.891294</td>\n",
       "      <td>2.046130e-38</td>\n",
       "      <td>306582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253668</th>\n",
       "      <td>714.227112</td>\n",
       "      <td>316.144287</td>\n",
       "      <td>-9.050291</td>\n",
       "      <td>2.036983e-38</td>\n",
       "      <td>306583</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253669</th>\n",
       "      <td>714.717590</td>\n",
       "      <td>316.152588</td>\n",
       "      <td>-11.170050</td>\n",
       "      <td>2.027764e-38</td>\n",
       "      <td>306584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253670</th>\n",
       "      <td>714.904297</td>\n",
       "      <td>314.775299</td>\n",
       "      <td>-11.329480</td>\n",
       "      <td>2.027764e-38</td>\n",
       "      <td>306585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253671</th>\n",
       "      <td>714.785583</td>\n",
       "      <td>312.023712</td>\n",
       "      <td>-9.527277</td>\n",
       "      <td>2.036983e-38</td>\n",
       "      <td>306586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253672</th>\n",
       "      <td>714.971802</td>\n",
       "      <td>310.650208</td>\n",
       "      <td>-9.686271</td>\n",
       "      <td>2.046202e-38</td>\n",
       "      <td>306587</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>253673</th>\n",
       "      <td>715.158020</td>\n",
       "      <td>309.276611</td>\n",
       "      <td>-9.845264</td>\n",
       "      <td>2.027799e-38</td>\n",
       "      <td>306588</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>253674 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  x           y           z           rgb   index\n",
       "0       1924.063965 -647.111023 -119.417603  0.000000e+00   25547\n",
       "1       1924.411987 -649.677979 -119.714699  0.000000e+00   25548\n",
       "2       1919.928955 -650.559082 -116.983902  0.000000e+00   25549\n",
       "3       1920.276001 -653.116577 -117.279900  0.000000e+00   25550\n",
       "4       1920.621948 -655.674072 -117.575996  0.000000e+00   25551\n",
       "5       1916.134033 -656.517822 -114.840797  0.000000e+00   25552\n",
       "6       1916.479980 -659.065918 -115.135803  0.000000e+00   25553\n",
       "7       1911.020020 -659.534729 -111.790703  0.000000e+00   25554\n",
       "8       1911.364014 -662.071716 -112.084396  0.000000e+00   25555\n",
       "9       1707.098022  829.543579   59.061298  0.000000e+00   25607\n",
       "10      1707.441040  827.006714   58.767639  0.000000e+00   25608\n",
       "11      1707.785034  824.469788   58.473980  0.000000e+00   25609\n",
       "12      1721.208008  833.919922   50.484982  0.000000e+00   25610\n",
       "13      1721.556030  831.353027   50.187851  0.000000e+00   25611\n",
       "14      1721.902954  828.786011   49.890709  0.000000e+00   25612\n",
       "15      1722.250977  826.219116   49.593571  0.000000e+00   25613\n",
       "16      1727.510010  828.102295   46.405418  0.000000e+00   25614\n",
       "17      1722.947021  821.085083   48.999290  0.000000e+00   25615\n",
       "18      1723.295044  818.518188   48.702148  0.000000e+00   25616\n",
       "19      1723.642944  815.951172   48.405010  0.000000e+00   25617\n",
       "20      1723.990967  813.384277   48.107868  0.000000e+00   25618\n",
       "21      1724.338989  810.817383   47.810730  0.000000e+00   25619\n",
       "22      1724.687012  808.250427   47.513592  0.000000e+00   25620\n",
       "23      1725.035034  805.683472   47.216450  0.000000e+00   25621\n",
       "24      1725.383057  803.116516   46.919312  0.000000e+00   25622\n",
       "25      1730.655029  804.898376   43.719440  0.000000e+00   25623\n",
       "26      1731.005005  802.320190   43.420990  0.000000e+00   25624\n",
       "27      1731.354004  799.742004   43.122551  0.000000e+00   25625\n",
       "28      1731.703979  797.163818   42.824100  0.000000e+00   25626\n",
       "29      1736.161987  798.172119   40.102409  0.000000e+00   25627\n",
       "...             ...         ...         ...           ...     ...\n",
       "253644   721.810608  239.279205   -0.178309  2.083118e-38  305992\n",
       "253645   709.068176  343.320099    0.457740  1.972553e-38  306560\n",
       "253646   709.252808  341.957794    0.300048  1.972517e-38  306561\n",
       "253647   709.437500  340.595490    0.142355  2.000141e-38  306562\n",
       "253648   709.622070  339.233185   -0.015337  2.027763e-38  306563\n",
       "253649   710.101013  339.327911   -2.125181  2.009432e-38  306564\n",
       "253650   710.286194  337.961792   -2.283309  2.000284e-38  306565\n",
       "253651   710.471375  336.595795   -2.441436  2.009396e-38  306566\n",
       "253652   710.360779  333.784088   -0.646107  2.027799e-38  306567\n",
       "253653   710.545471  332.421814   -0.803799  2.018616e-38  306568\n",
       "253654   711.026917  332.497711   -2.915818  2.009432e-38  306569\n",
       "253655   711.806580  334.000397   -6.983346  2.009396e-38  306570\n",
       "253656   711.992798  332.626892   -7.142339  2.018579e-38  306571\n",
       "253657   712.477173  332.680206   -9.256886  2.009360e-38  306572\n",
       "253658   712.663879  331.302887   -9.416316  2.000141e-38  306573\n",
       "253659   713.150024  331.345001  -11.532230  2.000141e-38  306574\n",
       "253660   713.037415  328.548309   -9.735177  2.009325e-38  306575\n",
       "253661   713.224121  327.170990   -9.894607  2.000141e-38  306576\n",
       "253662   713.410706  325.793701  -10.054040  2.000140e-38  306577\n",
       "253663   713.597412  324.416412  -10.213470  2.009359e-38  306578\n",
       "253664   713.784119  323.039093  -10.372900  2.018507e-38  306579\n",
       "253665   713.668518  320.265015   -8.573302  2.036911e-38  306580\n",
       "253666   713.854675  318.891388   -8.732297  2.055385e-38  306581\n",
       "253667   714.040771  317.517914   -8.891294  2.046130e-38  306582\n",
       "253668   714.227112  316.144287   -9.050291  2.036983e-38  306583\n",
       "253669   714.717590  316.152588  -11.170050  2.027764e-38  306584\n",
       "253670   714.904297  314.775299  -11.329480  2.027764e-38  306585\n",
       "253671   714.785583  312.023712   -9.527277  2.036983e-38  306586\n",
       "253672   714.971802  310.650208   -9.686271  2.046202e-38  306587\n",
       "253673   715.158020  309.276611   -9.845264  2.027799e-38  306588\n",
       "\n",
       "[253674 rows x 5 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cloud.points"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "def get_depth_image(cloud):\n",
    "    #camera image height and width\n",
    "    W = intrinsics.height;\n",
    "    H = intrinsics.width;\n",
    "\n",
    "    X_world = cloud.points.values[:,0]+t_x\n",
    "    Y_world = cloud.points.values[:,1]+t_y\n",
    "    Z_world = -cloud.points.values[:,2]+t_z\n",
    "    depth = np.sqrt((X_world**2+Y_world**2+Z_world**2))\n",
    "    #color = \n",
    "\n",
    "    X_plane = (X_world * intrinsics.fx / Z_world)\n",
    "    Y_plane = (Y_world * intrinsics.fy / Z_world)\n",
    "    \n",
    "    # Finally, project back onto the RGB plane.\n",
    "    X_plane = np.round(X_plane).flatten().astype('int')\n",
    "    Y_plane = np.round(Y_plane).flatten().astype('int')\n",
    "\n",
    "    #find the indicies that will hit the image plane\n",
    "    goodInds = np.where(np.logical_and(np.logical_and(np.logical_and(X_plane > 0, X_plane < W), Y_plane > 0), Y_plane < H))\n",
    "    goodInds = goodInds[0]\n",
    "    \n",
    "    #sort the remaining depth values to be projected back\n",
    "    to_sort = -depth[goodInds]\n",
    "    depthSorted = np.sort(to_sort);\n",
    "    order = np.argsort(to_sort)\n",
    "    depthSorted = -depthSorted;\n",
    "    \n",
    "    depthOut = np.zeros((H,W))\n",
    "    # Z-buffer projection\n",
    "    for ii in range(len(order)):\n",
    "        depthOut[Y_plane[goodInds[order[ii]]], X_plane[goodInds[order[ii]]]] = depthSorted[ii]\n",
    "\n",
    "    # Fix weird values...\n",
    "    # depthOut(depthOut > maxDepth) = maxDepth;\n",
    "    depthOut[depthOut < 0] = 0;\n",
    "    # depthOut[np.isnan[depthOut]] = 0;\n",
    "#     depthOut = np.rot90(depthOut);\n",
    "    return depthOut"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x127064048>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "depth_out = get_depth_image(cloud)\n",
    "plt.imshow(depth_out,cmap='gray')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "depthImage = DepthImage(depth_out)\n",
    "depthImage.save(base_dir+\"depth_images/test_depth.npy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.imshow(res.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/stephenhansen/Code/grasping_cornell_dataset/data/depth_images/test_depth.npy'"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "base_dir+\"depth_images/test_depth.npy\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100\n",
      "200\n",
      "300\n",
      "400\n",
      "500\n",
      "600\n",
      "700\n",
      "800\n",
      "900\n"
     ]
    },
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: '/Users/stephenhansen/Code/grasping_cornell_dataset/data/point_cloud/pcd0950.pcd'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-53-91f4129c8b16>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      7\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m         \u001b[0mfile_name\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"{}.pcd\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m     \u001b[0mcloud\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mPyntCloud\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfrom_file\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbase_dir\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0msource_folder\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0;34m\"pcd\"\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mfile_name\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     10\u001b[0m     \u001b[0mdepth_out\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_depth_image\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcloud\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m     \u001b[0mdepthImage\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mDepthImage\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdepth_out\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/stephenhansen/Code/grasping_cornell_dataset/envGraspData/lib/python3.6/site-packages/pyntcloud/core_class.py\u001b[0m in \u001b[0;36mfrom_file\u001b[0;34m(cls, filename, **kwargs)\u001b[0m\n\u001b[1;32m    128\u001b[0m                 \"Unsupported file format; supported formats are: {}\".format(list(FROM)))\n\u001b[1;32m    129\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 130\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mFROM\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mext\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    131\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    132\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mto_file\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0malso_save\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/stephenhansen/Code/grasping_cornell_dataset/envGraspData/lib/python3.6/site-packages/pyntcloud/io/pcd.py\u001b[0m in \u001b[0;36mread_pcd\u001b[0;34m(filename)\u001b[0m\n\u001b[1;32m     90\u001b[0m     \"\"\"\n\u001b[1;32m     91\u001b[0m     \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 92\u001b[0;31m     \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'rb'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     93\u001b[0m         \u001b[0mheader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     94\u001b[0m         \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: '/Users/stephenhansen/Code/grasping_cornell_dataset/data/point_cloud/pcd0950.pcd'"
     ]
    }
   ],
   "source": [
    "base_dir = \"/Users/stephenhansen/Code/grasping_cornell_dataset/data/\"\n",
    "source_folder = \"point_cloud/\"\n",
    "dest_folder = \"depth_images/\"\n",
    "for i in range(100,1035):\n",
    "    if i < 1000:\n",
    "        file_name = \"0{}.pcd\".format(i)\n",
    "    else:\n",
    "        file_name = \"{}.pcd\".format(i)\n",
    "    cloud = PyntCloud.from_file(base_dir+source_folder+\"pcd\"+file_name)\n",
    "    depth_out = get_depth_image(cloud)\n",
    "    depthImage = DepthImage(depth_out)\n",
    "    depthImage.save(base_dir+dest_folder+\"depth_{}.npy\".format(i))\n",
    "    \n",
    "    if i%100 == 0:\n",
    "        print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "101\n"
     ]
    }
   ],
   "source": [
    "for i in range(100,1035):\n",
    "    if i == 101:\n",
    "        print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x126409eb8>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "idx = 110\n",
    "res = DepthImage.open(base_dir+dest_folder+\"depth_{}.npy\".format(idx))\n",
    "plt.imshow(res.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x122056f60>"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(res.inpaint().data,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from gqcnn import RgbdImageState, ParallelJawGrasp\n",
    "\n",
    "# read images\n",
    "color_im, depth_im, _ = sensor.frames()\n",
    "color_im = color_im.inpaint(rescale_factor=inpaint_rescale_factor)\n",
    "depth_im = depth_im.inpaint(rescale_factor=inpaint_rescale_factor)\n",
    "rgbd_im = RgbdImage.from_color_and_depth(color_im, depth_im)\n",
    "state = RgbdImageState(rgbd_im, camera_intr)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}