add grayscale image example

examples/pydensecrf_GrayscaleImageExample.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "sys.path.insert(0,'/home/dlr16/Applications/anaconda2/envs/PyDenseCRF/lib/python2.7/site-packages')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "from PIL import Image\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "%matplotlib inline\n",
+    "plt.rcParams['figure.figsize'] = (20, 20)\n",
+    "plt.rcParams['image.interpolation'] = 'nearest'\n",
+    "plt.rcParams['image.cmap'] = 'gray'\n",
+    "\n",
+    "import pydensecrf.densecrf as dcrf\n",
+    "from pydensecrf.utils import unary_from_softmax, create_pairwise_bilateral, create_pairwise_gaussian"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "collapsed": true
+   },
+   "source": [
+    "## Start from scratch"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "from scipy.stats import multivariate_normal\n",
+    "\n",
+    "x, y = np.mgrid[0:512, 0:512]\n",
+    "pos = np.empty(x.shape + (2,))\n",
+    "pos[:, :, 0] = x; pos[:, :, 1] = y\n",
+    "rv = multivariate_normal([256, 256], 128*128)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "probs = rv.pdf(pos)\n",
+    "probs = (probs-probs.min()) / (probs.max()-probs.min())\n",
+    "probs = 0.2 * (probs-0.5) + 0.5\n",
+    "probs = np.tile(probs[:,:,np.newaxis],(1,1,2))\n",
+    "probs[:,:,1] = 1 - probs[:,:,0]\n",
+    "\n",
+    "# permute for graph\n",
+    "probs = np.transpose(probs,(2,0,1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "collapsed": false,
+    "scrolled": false
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(-0.5, 511.5, 511.5, -0.5)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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gbDXrR4uj1R0he85GRvJEZ+hIdUfO9DmL8NmqL1sIHsiemAAiInrLW95yzS+S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8rG//4dm80TibtuknfPiIjO+Olv2ncv3RrTrbpXLNMaByTW3jzW4MWrN1pO2phZ6v94rv1xf228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\nnTLHy/cEhxWTqceTSm+QPVLsamEk1RHtSyRfqtNrf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+      "text/plain": [
+       "<matplotlib.figure.Figure at 0x7f947a878990>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "nchannels=1\n",
+    "\n",
+    "# Inference without pair-wise terms\n",
+    "U = unary_from_softmax(probs) # note: num classes is first dim\n",
+    "d = dcrf.DenseCRF2D(probs.shape[1],probs.shape[2],probs.shape[0])\n",
+    "d.setUnaryEnergy(U)\n",
+    "\n",
+    "Q_Unary = d.inference(10)\n",
+    "map_soln_Unary = np.argmax(Q_Unary, axis=0).reshape((probs.shape[1],probs.shape[2]))\n",
+    "\n",
+    "\n",
+    "# Create simple image\n",
+    "tmp_img = np.zeros((probs.shape[1],probs.shape[2],nchannels)).astype(np.uint8)\n",
+    "tmp_img[150:362,150:362,:] = 1\n",
+    "\n",
+    "# Inference with pair-wise terms\n",
+    "pairwise_energy = create_pairwise_bilateral(sdims=(10,10),\n",
+    "                                           schan=(0.01,),\n",
+    "                                           img=tmp_img,\n",
+    "                                           chdim=2)\n",
+    "\n",
+    "d.addPairwiseEnergy(pairwise_energy, compat=10)\n",
+    "\n",
+    "Q = d.inference(100)\n",
+    "map_soln = np.argmax(Q, axis=0).reshape((probs.shape[1],probs.shape[2]))\n",
+    "\n",
+    "# plot\n",
+    "plt.subplot(2,2,1)\n",
+    "plt.imshow(probs[0,:,:])\n",
+    "plt.title('Probability')\n",
+    "plt.axis('off')\n",
+    "\n",
+    "plt.subplot(2,2,2)\n",
+    "plt.imshow(map_soln_Unary)\n",
+    "plt.title('MAP Solution without pairwise terms')\n",
+    "plt.axis('off')\n",
+    "\n",
+    "plt.subplot(2,2,3)\n",
+    "plt.imshow(tmp_img[:,:,0])\n",
+    "plt.title('Raw image')\n",
+    "plt.axis('off')\n",
+    "\n",
+    "plt.subplot(2,2,4)\n",
+    "plt.imshow(map_soln)\n",
+    "plt.title('MAP Solution with fully connected CRF')\n",
+    "plt.axis('off')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "anaconda-cloud": {},
+  "kernelspec": {
+   "display_name": "Python [default]",
+   "language": "python",
+   "name": "python2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}