RunParts.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using gpu device 3: GeForce GTX TITAN Z (CNMeM is disabled, cuDNN 5110)\n",
      "/home/baque/.local/lib/python2.7/site-packages/theano/sandbox/cuda/__init__.py:600: UserWarning: Your cuDNN version is more recent than the one Theano officially supports. If you see any problems, try updating Theano or downgrading cuDNN to version 5.\n",
      "  warnings.warn(warn)\n"
     ]
    }
   ],
   "source": [
    "import matplotlib\n",
    "matplotlib.use(\"nbagg\")\n",
    "import math\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import cv2\n",
    "import re, os, glob, pickle, shutil,sys\n",
    "from random import randint\n",
    "import time\n",
    "from shutil import *\n",
    "\n",
    "os.environ[\"THEANO_FLAGS\"] = \"mode=FAST_RUN,device=gpu3,floatX=float32\"\n",
    "import theano\n",
    "import theano.tensor as T\n",
    "from theano import *\n",
    "theano.__version__\n",
    "from theano.sandbox.cuda import dnn\n",
    "\n",
    "import pandas as pd\n",
    "from theano import tensor as T\n",
    "from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams\n",
    "\n",
    "\n",
    "from theano.compile.nanguardmode import NanGuardMode\n",
    "\n",
    "#from pom_funcs import *\n",
    "from pom_room import POM_room\n",
    "from pom_evaluator import POM_evaluator\n",
    "import POMLayers1\n",
    "from EM_funcs import *\n",
    "import ZtoY\n",
    "config.allow_gc =False\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "\n",
    "import Config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/baque/.local/lib/python2.7/site-packages/theano/tensor/signal/downsample.py:6: UserWarning: downsample module has been moved to the theano.tensor.signal.pool module.\n",
      "  \"downsample module has been moved to the theano.tensor.signal.pool module.\")\n",
      "GaussianNet.py:147: UserWarning: theano.function was asked to create a function computing outputs given certain inputs, but the provided input variable at index 2 is not part of the computational graph needed to compute the outputs: dropout.\n",
      "To make this warning into an error, you can pass the parameter on_unused_input='raise' to theano.function. To disable it completely, use on_unused_input='ignore'.\n",
      "  updates=updates_bg, allow_input_downcast=True,on_unused_input='warn')\n",
      "GaussianNet.py:156: UserWarning: theano.function was asked to create a function computing outputs given certain inputs, but the provided input variable at index 0 is not part of the computational graph needed to compute the outputs: X.\n",
      "To make this warning into an error, you can pass the parameter on_unused_input='raise' to theano.function. To disable it completely, use on_unused_input='ignore'.\n",
      "  on_unused_input='warn')\n",
      "GaussianNet.py:156: UserWarning: theano.function was asked to create a function computing outputs given certain inputs, but the provided input variable at index 1 is not part of the computational graph needed to compute the outputs: Y_in.\n",
      "To make this warning into an error, you can pass the parameter on_unused_input='raise' to theano.function. To disable it completely, use on_unused_input='ignore'.\n",
      "  on_unused_input='warn')\n",
      "GaussianNet.py:156: UserWarning: theano.function was asked to create a function computing outputs given certain inputs, but the provided input variable at index 2 is not part of the computational graph needed to compute the outputs: dropout.\n",
      "To make this warning into an error, you can pass the parameter on_unused_input='raise' to theano.function. To disable it completely, use on_unused_input='ignore'.\n",
      "  on_unused_input='warn')\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
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      "Running inference for cam 3, fid 2775:\n",
      "Running inference for cam 3, fid 2780:\n",
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      "Running inference for cam 3, fid 2795:\n",
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      "Running inference for cam 3, fid 2990:\n",
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      "Running inference for cam 3, fid 3000:\n",
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      "Running inference for cam 3, fid 3640:\n",
      "Running inference for cam 3, fid 3645:\n",
      "Running inference for cam 3, fid 3650:\n",
      "Running inference for cam 3, fid 3655:\n",
      "Running inference for cam 3, fid 3660:\n",
      "Running inference for cam 3, fid 3665:\n",
      "Running inference for cam 3, fid 3670:\n",
      "Running inference for cam 3, fid 3675:\n",
      "Running inference for cam 3, fid 3680:\n",
      "Running inference for cam 3, fid 3685:\n",
      "Running inference for cam 3, fid 3690:\n",
      "Running inference for cam 3, fid 3695:\n",
      "Running inference for cam 3, fid 3700:\n",
      "Running inference for cam 3, fid 3705:\n",
      "Running inference for cam 3, fid 3710:\n",
      "Running inference for cam 3, fid 3715:\n",
      "Running inference for cam 3, fid 3720:\n",
      "Running inference for cam 3, fid 3725:\n",
      "Running inference for cam 3, fid 3730:\n",
      "Running inference for cam 3, fid 3735:\n",
      "Running inference for cam 3, fid 3740:\n",
      "Running inference for cam 3, fid 3745:\n",
      "Running inference for cam 3, fid 3750:\n",
      "Running inference for cam 3, fid 3755:\n",
      "Running inference for cam 3, fid 3760:\n",
      "Running inference for cam 3, fid 3765:\n",
      "Running inference for cam 3, fid 3770:\n",
      "Running inference for cam 3, fid 3775:\n",
      "Running inference for cam 3, fid 3780:\n",
      "Running inference for cam 3, fid 3785:\n",
      "Running inference for cam 3, fid 3790:\n",
      "Running inference for cam 3, fid 3795:\n",
      "Running inference for cam 3, fid 3800:\n",
      "Running inference for cam 3, fid 3805:\n",
      "Running inference for cam 3, fid 3810:\n",
      "Running inference for cam 3, fid 3815:\n",
      "Running inference for cam 3, fid 3820:\n",
      "Running inference for cam 3, fid 3825:\n",
      "Running inference for cam 3, fid 3830:\n",
      "Running inference for cam 3, fid 3835:\n",
      "Running inference for cam 3, fid 3840:\n",
      "Running inference for cam 3, fid 3845:\n",
      "Running inference for cam 3, fid 3850:\n",
      "Running inference for cam 3, fid 3855:\n",
      "Running inference for cam 3, fid 3860:\n",
      "Running inference for cam 3, fid 3865:\n",
      "Running inference for cam 3, fid 3870:\n",
      "Running inference for cam 3, fid 3875:\n",
      "Running inference for cam 3, fid 3880:\n",
      "Running inference for cam 3, fid 3885:\n",
      "Running inference for cam 3, fid 3890:\n",
      "Running inference for cam 3, fid 3895:\n",
      "Running inference for cam 3, fid 3900:\n",
      "Running inference for cam 3, fid 3905:\n",
      "Running inference for cam 3, fid 3910:\n",
      "Running inference for cam 3, fid 3915:\n",
      "Running inference for cam 3, fid 3920:\n",
      "Running inference for cam 3, fid 3925:\n",
      "Running inference for cam 3, fid 3930:\n",
      "Running inference for cam 3, fid 3935:\n",
      "Running inference for cam 3, fid 3940:\n",
      "Running inference for cam 3, fid 3945:\n",
      "Running inference for cam 3, fid 3950:\n",
      "Running inference for cam 3, fid 3955:\n",
      "Running inference for cam 3, fid 3960:\n",
      "Running inference for cam 3, fid 3965:\n",
      "Running inference for cam 3, fid 3970:\n",
      "Running inference for cam 3, fid 3975:\n",
      "Running inference for cam 3, fid 3980:\n",
      "Running inference for cam 3, fid 3985:\n",
      "Running inference for cam 3, fid 3990:\n",
      "Running inference for cam 3, fid 3995:\n"
     ]
    }
   ],
   "source": [
    "from GaussianNet import gaussianNet\n",
    "parts_predictor = gaussianNet()\n",
    "parts_predictor.run_inference(bg_pretrained = True,regression_pretrained = True,verbose = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": []
  }
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