diff --git a/assignment_4_5_indexing_template/image_search.py b/assignment_4_5_indexing_template/image_search.py
index f45a37d0f17c8c55265c84c33e472c65c40b9af1..cee10bf51d30e8a1a7501d515f9b8819e6d3000c 100644
--- a/assignment_4_5_indexing_template/image_search.py
+++ b/assignment_4_5_indexing_template/image_search.py
@@ -38,8 +38,8 @@ def nearest(means: np.ndarray, data: np.ndarray) -> (np.ndarray, np.ndarray):
 def create_db(imgs_visual_words: np.ndarray, num_words: int) -> csr_matrix:
     """
     Create database [num_words, num_imgs] of word weights represented as csr_matrix. Details explained at tutorial page.
-    imgs_visual_words is of dimensions [num_imgs, visual_words_in_img]. Number of visual_words_in_img differs for
-    each img.
+    imgs_visual_words is an array of arrays of length num_imgs. Each np.array is a list of visual words in an image.
+    Number of visual_words_in_img differs for each img.
 
     :param imgs_visual_words:
     :param num_words:
@@ -71,8 +71,8 @@ def create_db_tfidf(imgs_visual_words: np.ndarray, num_words: int, idf: np.ndarr
 def get_idf(imgs_visual_words: np.ndarray, num_words: int) -> np.ndarray:
     """
     Create Inverse Document Frequency of shape: [num_words, num_imgs]
-    imgs_visual_words is of dimensions [num_imgs, visual_words_in_img]. Number of visual_words_in_img differs for
-    each img.
+    imgs_visual_words is an array of arrays of length num_imgs. Each np.array is a list of visual words in an image.
+    Number of visual_words_in_img differs for each img.
     idf is of shape: [num_words, 1]
 
     :param imgs_visual_words:
diff --git a/assignment_4_5_indexing_template/spatial_verification.ipynb b/assignment_4_5_indexing_template/spatial_verification.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..bf57c5165b9bc2d0fe178126909a13722867970f
--- /dev/null
+++ b/assignment_4_5_indexing_template/spatial_verification.ipynb
@@ -0,0 +1,130 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "# TODO:\n",
+    "\"\"\"\n",
+    "corrs=corrm2m(qvw, vw, relevant, max_tc, max_MxN)\n",
+    "qvw - visual words in query image\n",
+    "vw - K x visual words\n",
+    "relevant - list of relevant img indices (of len K)\n",
+    "\n",
+    "return a list of lists of tentative correspondences (K x Tk), K - #imgs, Tk - tentative\n",
+    "corrs between query and k-th relevant image (qvw_i, vw_i)\n",
+    "\n",
+    "\"\"\"\n",
+    "\n",
+    "\n",
+    "\n",
+    "# TODO: what is a minimum number of features in common\n",
+    "# M x N - cartesian product of the same visual word instances\n",
+    "# maximum min(N,M) TRUE correspondences\n",
+    "\n",
+    "# sort common visual words w.r.t. MxN\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "from image_search import *\n",
+    "import scipy.io"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "outputs": [
+    {
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-1-30f4565421d9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mscipy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloadmat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'data/mpvdb_haff2.mat'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'data'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mT\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;31m# idf = getidf(VW, 10000);\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;31m# DB  = createdb_tfidf(VW, 10000, idf);\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;31m#\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;31m# opt = [];\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mNameError\u001b[0m: name 'scipy' is not defined"
+     ],
+     "ename": "NameError",
+     "evalue": "name 'scipy' is not defined",
+     "output_type": "error"
+    }
+   ],
+   "source": [
+    "data = scipy.io.loadmat('data/mpvdb_haff2.mat')['data'].T\n",
+    "# idf = getidf(VW, 10000);\n",
+    "# DB  = createdb_tfidf(VW, 10000, idf);\n",
+    "# \n",
+    "# opt = [];\n",
+    "# opt.max_tc=600;\n",
+    "# opt.max_MxN=10;\n",
+    "# opt.max_spatial=50;\n",
+    "# % directory where you unzipped mpvimgs.zip\n",
+    "# opt.root_dir='./';\n",
+    "# % opt.subplot=1;\n",
+    "# opt.threshold=8;"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% load data and create inverted file\n",
+     "is_executing": false
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "\n"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  },
+  "pycharm": {
+   "stem_cell": {
+    "cell_type": "raw",
+    "source": [],
+    "metadata": {
+     "collapsed": false
+    }
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
\ No newline at end of file
diff --git a/assignment_4_5_indexing_template/spatila_verification.py b/assignment_4_5_indexing_template/spatila_verification.py
new file mode 100644
index 0000000000000000000000000000000000000000..99012d0784ae1803f9b3640b01f0d3b73c75bc08
--- /dev/null
+++ b/assignment_4_5_indexing_template/spatila_verification.py
@@ -0,0 +1,85 @@
+import numpy as np
+from scipy.sparse import csr_matrix
+
+
+def get_tentative_correspondencies(
+        query_vw: np.ndarray, vw: np.ndarray, relevant_idxs: np.ndarray, max_tc: int, max_MxN: int) -> np.ndarray:
+    """
+    Compute tentative correspondencies.
+
+    :param query_vw: [num_keypoints_in_query x 1]
+    :param vw: [num_imgs x num_words_in_img] visual_words
+    :param relevant_idxs: [num_imgs, ]
+    :param max_tc: maximum tentative correspondences
+    :param max_MxN: maximum pairs
+    :return: correspondencies np.ndarray of shape [num_correspondencies x 2]
+    """
+
+    correspondencies = np.zeros((0, 2), dtype=np.int)
+
+    return correspondencies
+
+
+def get_A_matrix_from_geom(geom: np.ndarray):
+    """
+    returns a matrix
+    [
+        a11 a12 x
+        a21 a22 y
+        0   0   1
+    ]
+
+    :param geom:
+    :return: 3x3 matrix
+    """
+    return np.array([
+        [geom[2], geom[3], geom[0]],
+        [geom[4], geom[5], geom[1]],
+        [0, 0, 1],
+    ])
+
+
+def ransac_affine(
+        q_geom: np.ndarray, geometries: np.ndarray, correspondencies: np.ndarray, relevant: np.ndarray,
+        inlier_threshold: float) -> (np.ndarray, np.ndarray):
+    """
+
+    :param q_geom: query geometry of shape [num_keypoints x 6]
+    :param geometries: np.ndarray of object of len num_images. each object is np.ndarray [num_keypoints_in_img x 6]
+    :param correspondencies: [num_correspondencies x 2]
+    :param relevant: relevant indices
+    :param inlier_threshold: maximum transformed point to corresponding point distance to be considered as an inlier
+    :return: (As, inliers_counts), where As are estimated affine matrices for each image and number of inliers in each image
+    """
+
+    K = len(relevant)
+    As = np.zeros((K, 3, 3))
+    inliers_counts = np.zeros((K, ))
+
+    return As, inliers_counts
+
+
+def query_spatial_verification(
+        query_visual_words: np.ndarray, query_geometry: np.ndarray, bbox: list, visual_words: np.ndarray,
+        geometries: np.ndarray, db: csr_matrix, idf: np.ndarray, params: dict) -> (np.ndarray, np.ndarray, np.ndarray):
+    """
+
+    :param query_visual_words: [num_keypoints_in_query x 1]
+    :param query_geometry: query geometry of shape [num_keypoints x 6]
+    :param bbox: list [x, y, xx, yy]
+    :param visual_words: [num_imgs x num_words_in_img] visual_words
+    :param geometries: np.ndarray of object of len num_images. each object is np.ndarray [num_keypoints_in_img x 6]
+    :param db: [num_words, num_imgs]
+    :param idf: Inverse Document Frequency. Shape: [num_words, 1]
+    :param params: dictionary, important keys here: minimum_score, max_tc, max_MxN, use_query_expansion
+
+    :return:
+    """
+
+    num_relevant = ...  # you need to get number based on scores and params['minimum_score']
+    inliers_counts = np.zeros((num_relevant, ), dtype=np.int)
+    relevant_idxs = np.zeros((num_relevant, ), dtype=np.int)
+    As = np.zeros((num_relevant, 3, 3))
+
+    return inliers_counts, relevant_idxs, As
+
diff --git a/assignment_4_5_indexing_template/test.ipynb b/assignment_4_5_indexing_template/test.ipynb
index c34b7e28be5d5deb1147ea97e8bed30cd3640bef..207f2d84444ec03482478c9b8b11a06c36cfef46 100644
--- a/assignment_4_5_indexing_template/test.ipynb
+++ b/assignment_4_5_indexing_template/test.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 11,
    "metadata": {
     "pycharm": {
      "is_executing": false,
@@ -12,19 +12,15 @@
    "outputs": [
     {
      "name": "stdout",
-     "output_type": "stream",
      "text": [
-      "The autoreload extension is already loaded. To reload it, use:\n",
-      "  %reload_ext autoreload\n",
-      "Started on: 2020-04-04 21:06:13\n"
-     ]
+      "The autoreload extension is already loaded. To reload it, use:\n  %reload_ext autoreload\nStarted on: 2020-04-13 16:40:24\n"
+     ],
+     "output_type": "stream"
     },
     {
      "data": {
-      "image/png": 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Mk5YfVpeyr6bTx/VXy71CAThCLSJngkoBiNorYhKQxVqXpRo0RvWzyp2Hwk6OWUr2CQMJOUF0AKoFXq/XXUlAak3xKEJmiizRhS7KUSwynHNPAhIAbZZqkBUd5D4JmhyzluwTBhJygugAdC4FuRCWWho2iZCZ3q+O4dy5c7hx44YziQBwTSiyIANeP3uYzxrU2k5HHv3oJOQEkXHSWOabXAq2bTubjkk2BE3+d5H4Mzg4iHq97iQZiZ6a09PTjuUOwLUBqgp/2NR6teRAVP9/Hv3oJOQEkWHSXOYLC9y2bSwtLcGyLMzPzzubk3FbrQX537e3t524cbWkrpz5Ktc7F8IrqikODg5G9t3LWahRLOusJfuEgYS8Q8nbZk6nkvYy36/2uBxvHUXITP53OS1ePoec8Snau4kIFvl1srDv7Oygp6fnyMI3s5TsEwYS8g4kj5s5aZDHySvtZb6u9rgQc/n4UYTM5H8XafFBJXUBbxYoYwz7+/sui1ptFh30ffpZ1nm8F/wgIe9A8riZk5S8Tl66wlFxsjEFusJYaphg0jGKY6gJSHIUixwzDsBjkQcRpXyB+vu83gt+kJB3IHnczElKnicv2bedVICO2v9rsuzV36uuGM45urq6nCJbIvtUUKlUYn+feb4XTJCQdyB53MxJSjtMXmkJUNr+X9MEEzUWXa1QKMoGqIWuAHd0i6h9HpZ2uBdUSMg7lLxt5iTlqCYvOZwvrqvCRFYFyFS2N8zqQb1eag0W8R75WGfPnnWVAYh6ndvRkCEhJzqGZk9etm3j8uXLnnC+tNLAsypAugkmzOpBd72mpqYcf7kIQdS1fJPPNzw8HOtaZuX6pQEJOUFEwE8w1O45fu6PuP7uLAqQbkO2Vqs5DZNNqwfd9VJDE8UxVeGWs1GB9ixNGwUScoIISZD4qo2J/dwfJos1yLLMetic3N6tUChgZGTE6PrQXS81NFF8TlNUDOBusNwum5dRSSzkjLEXAPx3AKcAcACvc86/nPS4BJEWaYlfmGJMs7OzoXzkOndE0ETR7LC5uNfJr6phd3e38Vim66UrZ+u3Esnq3sFRkoZF/gjA5zjnc4yxEwCuMca+wTn/QQrHJohYyHWv1XTwuOIXRjDCuj50VqbJshSfpVarNc3yTDJJ6JKMgHCVCnXXK6r7KKt7B0dJYiHnnG8C2Hz8//uMsSUAZwCQkBMtwWQhxikApVrcaQqGKlhBVnqhUAj0O8clSWijLslILWHbbLK4d3CUpOojZ4wNA5gC8F3N314D8BoADA0NpXlagnCRxEIM02m+WYIRZKVzzjEyMoLu7u7URTJpXZJOt4hbTWpCzhg7DuCvAfwm5/ye+nfO+esAXgeAmZkZrv6dINIijIVosrr9LNOj2GgMstLTjk2Xz5tEjPNoEWd94zgKqQg5Y+xpNET8a5zzr6dxTIKIS5Ao+VndJsu0VfU5mmXt6kQsj2Icl3art5JG1AoD8GcAljjnf5h8SERY2smiSBs/UfKzusvlsrYGtil78Siu/1Gl1HcS7VZvJQ2L/KMAfhHAdcbYwuPffZFz/vcpHJswQA9jfPz8wbZtO1Eutm07NbDV91iWldvr324iFod2C1lMI2rl2wBYCmMhIkAPY3xM7gq/ju3qe9K8/vLKCghn5SdZjbWbiMWh3TZoKbOzhTTrYSSXSzCqu0Je4Qj8qurFEUP1exEFo0QXHNFk4fDw0GmJpgvj07VWC7uZKz57O4lYXNppT4CEvEUkdY34WZV5XfKbOIqJSe3YrhuDel2jdJ/Ria9w4QjkuiMHBweYm5tzYsZFfZFyuexpbixeJ/e/DLoH2knECBLyQJolImkszXUPY7u5XI5qYhIWtiysnHPn+umu68TEhGNZi649gF5EVfFdXV31TBzCIpdT3MX55E7w8mpAfZ3YhG2ne4AIhoTch2aKSLP8lO3m/0xjYgpbiEq0PatUKp7sSdN1XVlZcVnEZ8+e1Ua31Go11znv3r3rZGkyxjA8PIxSqeS0XSuVSlqLXW2OLEoQHB4egjGGWq2GUqnUVvcAEQwJuQ/NtG7j+imTNJzNI0knpjiFqOQSqXJYonpdbdt2RBx4YgWboltk1CxNwG3Jy00WdBOLvBrr6elxXre6uurrXyfaExJyH+Qym1HbSYUhqp8yScPZvJJ0YlIn40ql4jqWn8tENxY1C1SIuKBUKqFUKjlx6PV63eh739/fd/zeuoJZYhzqxKJO5uJzyB3nhYiLFUHacejtYii0CyTkCmooWJZoN/93WJJMTLJFzxhzIkTERGhZllNYSy5UJdwWpqgR8Xe5KBcAVKtVp8ONbduYnJz0+N4FGxsb2N7e9vi91ZWH/PlNk/lRxbm342Z6O0BCLqHepHJvQHnjq1W0m/87KWEsQ9mir9VqWF1dBfDEOl9bW3OE+MyZMwDgcYXIUSPy34vFIsbHx3Hjxg3HR76/v++abOv1unP+er3uvFag83v7fR7TZJ5GnHuY69mpxkTWISGXUG9SAJkSznbzfychimUohM62baytrTnWebVadQn2O++8g0ePHnmsZzlqRN3MtCwLr776qmOhz8/Pu94ruz+AxmQRxu8tf075+w5ruQPR7t2w1zMrxgS5d9yQkEvoKs3pNr6A1t1I7eT/TkIcy1BMhEJIRYSIzMOHD42uENPkLr6TpaUlVyy4aQwyftUMTeIaZjKPOumHvZ5ZMCbIveOFhFzCdJPqrKR2v5GyZPHoxhLXMlQ3BlVGR0edVmOWZXnCEf0m976+Pk+rM1UQ1XtHuGt0JC3UFWXSj3I9W21MkHvHCwm5QpibNMyNtLKy4kQujI2NNW28zSBLE5VpLEksQzkaqVAo4Pz587h7967ru5KPZwpHVCmXyxgfH8dbb73l/M6yLNdEFEWE4m5gxpmEs2BphyUr7p0sQUIeg6AbaWVlBdeuXQMAbG9vA0CuxDxLFk+QVToxMWF8r6m2yf7+vmvD8fjx47AsCz09PcZjWJYVKpTPsizXz9Vq1UnsYYxhfHzcmUQ456jX605WqByZIsYddQMzySTcaks7LHmadI4KEvIYBN1I6+vrnp/zJOSttnhkIVNT5+v1emDBKHEM9XXz8/Mel8rh4aGxpomukJZJHN98803cvn0bzz33nOvaAU8ShTjnnqgVYb371UmRJyv5WqiTBpCtSbiZ5GXSOSpIyGPidyP19vY6lrj4OU+00uLRWZSTk5OO2MpuC13BKDFWVdDW19eNfnG1psmtW7cwPT2tTeZRxXFlZQVLS0v44Q9/CAB48OABhoaG0NPT40yAt27d8tRPUQlTJ6VcLruuxcLCglMvXSC7jTjnjtjHKZVL5AcS8oSI5TrwJAJBtZR0llOS8wU9hGlsVLbK4jG5UkwCqBaMMm2GDg4O4s6dO57jqAk94phzc3OYnp72RLCodVaEC03mvffew0c+8hHnZ9lvLkRWRT6u32qoXq8bP7N6TQA44ZDCvaOWym3HjfpOhIQ8AbZt4/Lly86DWalUMDs72zTXRBj/Z5Y2KuNguna6kMCBgQFsb28bY6rVVUW1WnUSggR+E4SczCNneQLA0tKSx4UmEIlFcr1xoDFpnD9/Hnfu3HGFPp46dQoXL150vie/1VDQvSUibARiNaLmR4j/i4kgS1FKRHRIyBOghrGJbMGZmZmmuCbC+D/z7iM1uXV0BaQuXLiACxcuGK+zuqoYHh520ucFsoUqI2rrqMfQ+c0FlmVhZGQEr7zyivZ1Oh95sVh0ibhu3GGujxibmDTkzzc4OAjbtp1EKDEWuSRBnid/goRcS1jrRPZHCiqViuNi0UUhJHlAwlj6rd6oTAOTkHV3d2NqasqzuRknxE62sPf29rC+vo5nnnkG77zzjvN6IYqyxVqr1TwiXiqVXPHn4rXq61Q3jmqJhy23q0bryGOT78VSqYSpqSmUy2VnbDofua5gFwl5viAhV4ia+j07O4v5+XlnqawmgYQ9XtS6IaZwtXYMzZKvIWMM09PTqfj+1VZrwloFGt+jSMuXu/kIC17m2LFjqFarTlSMiJIR7iDGGPr7+9Hf3++8plAoOCK+srKC1dVV3L1716lPPj097Yp0Mt1H6rURFItFR8T9rgHgLSxWq9Vg23Zb3DudAgm5QlTXRLlcxujoqCuETbaCw2TnyQ+jGgKnO59fmJ2cMNMuyNdQbETK0RpqRIa6+azD5PpQrWbVx8w5x4kTJ3D//n3nNRsbG65jHxwcoFqtuiJMtre30d/f7xnHm2++6YrEMX1G032pXhugYflPTk6GNibE5C/XNBfdiOLcR+RvP3pSEXLG2CcAfBlAEcBXOOe/l8ZxW0FU14Rt21hYWHBEQH6AdMer1+t44403XCFz6kMa5UFKwyee9QdPjfqRVz3yhrMqwrdu3cKrr77q+kwi49ZUT2V8fBwffPCBEzLIGMPg4KCzH8IYw8DAgEd8VcRkIkeYyCGQnHNHNHWoKzvTfanG2Qvq9brzf/keOTg40N4jYlKQa5rHvZfI3370JBZyxlgRwJ8C+LcA1gF8jzH2d5zzHyQ9diuI6ppQfaH1et3o6rAsy9NRRrxOfRjVB8kktkl94mm6fpqBmChlisWiy/pWe1cKOOdYXl7GyZMnHV+4LlxQxrIsp0KhKaJFtsYBcwijGKscAmnbtvM97+/vG8chf0bA3KFoZ8e/RZ34TOpnTLN+jUzeN9vzShoW+YcB3OScrwIAY+x/APgUgFwIue6G1rkvwoaDmephiE0l+YGXIyP82nr5ia06UYRJI5dRrbXFxUVPFMVRW1mm2iSAd4MwiI2NDWxsbKBYLOLZZ591/a2rq8slpuL7kC1TzrnLkj48PHS5UgqFAp577jnYtu06tl+BLTGZb21teTbL/Vxrqn8/TIs627Y9YZJy2YC06tcI2mGzPY+kIeRnALwr/bwO4F+rL2KMvQbgNQAYGhpK4bRu4liMfgIl19jQ3fSmehiVSsXYWky2vNVNO/Eg6R7GICtH/D+O2Kqrge3tbdi27Zsl2UwrS5daLwuDKuLDw8Muq9zE4eGhsykpeP75511RKi+88ILzncvZkb29vZ5QU8Hp06extbXl+t3AwAC6uroAeI0CNaFH9bcfHh6iu7s7cFWkTsAi7DUoVLJYLDrvEedT298l+W7bcbM9DxzZZifn/HUArwPAzMyMfs0ak7gWoyq6st9VjgRQM+kAeMQGAPb29jxxvGprMfkmB+ApmKRbDdRqNafjusnKiSu24sFbXFx0ygoEZUk2w8rShfepHXZMseKzs7Ou6BMdIu68v7/faVCsukjeffddvPPOO861Frz11ltORAhjDIwxV5SLes6trS0cHh5q9znUiVPnppGvr8mgmJycdFnzctirQF3NiH6ipVLJt/1dUvFtt832PJCGkN8G8IL08+Dj3x0ZcURMTZ5gjMGyLCwtLbnERGx4AU/SqFVrSPhdVV9pb2+vYwHKLb3UySLMaqBQKGBkZMT1sOqKS8UR23K5jIsXLzpJI2GyJNNEjdpRJ60gYVBXM/J1E3//0Ic+5Bxjb29PmwAkT9gqcq2UY8eO4eHDh457RMVvw1A3ccpjkFdpfgZFvV7H8PCws1mqq32uhhXu7e2hWq26io2p7e/Ip51P0hDy7wE4zxgbQUPAfx7Af0zhuKGJI2LqUvn06dMu0ZTFRFdhT1czQxbxQqGA0dFRLCwsaMdlmnxWVlYcH6r68FarVacRgW4iSCK2QWLdTCtLvRbCavQLH9QhxmjbNkqlkuO3tm0be3t7nsgMwalTpzA4OOjEeMvZjzpEgSwx3nK5jN3dXed+4Zw735/uXlQnTsaY1i+uCy0EnljtfX19Tus63X0vf6eqYNfrdUxMTLja35FPO78kFnLO+SPG2G8A+Ec0wg+/yjlfTDyyCMSxGFXx7+rqcj00IyMj6O7uNora6dOnPfHDgNuy6+npMY5LN/nYtu2KalHFvFqt4o033vBU5hM+UtN4gfAJR62wxlR3Q7Vaxb1793y755gwpdCLUsJqNq7wuwNusTx27JhLsP147733nO9E9O0UYq7LDg2buKVa1Gp0TphjyJObTrDJp90eMJPV0UxmZmb41atXUzmWrnlA2JtSTSS5cuWKc6MH+UETsGQAACAASURBVAqvXr1qjAEWvPzyy5EaHywtLeH69evO30VGoDphiAYFciyzEHydnzMPsb22bbvcDYwxvPTSS77XT4d6DQU/+qM/6mRK6ipWfvvb39ZOzIKhoSE89dRTrpK0AnmsuvOL71H4zqN8B+Ie2d3ddY1vdHQUMzMzge/XHYsEO78wxq5xzj1ffK4zO3URDroIExNyVIYafbK3t4f5+XkcO3YMFy5c8BxHFy2h+sjV+N2gmtC6qJaenh5HAAScc9y9e9d1bDU23bREz6ofNMhPHxbZigUa+xSiDoq8saxOdJubm77Hfeqpp1AqlbC/v6+dWEVau67+Dufc9R7dd2ASWTHWuIaPetysfe9EOuRayFWBUst1BgmWKTVeThypVqvY2NjwbJiJaAmxuaZuHAHu7Dr1XGKMYeJ4Z2dnsby8jM3NTcfqlivaAfCdQHSx7mq0TLOJWksmTky8egxdCQTdBL+zs2P0hwt0qy/Z0pazceVNSB3qJCXvi8idguTPUCqVXMdQf9aRh5UYkQ65FnJVoGRx87PoTKFu4mFUE0fEe771rW+5lug6y860caROOgJ1wtFZTeVyGT/+4z/uEUNR0c5vAhHvlwVS3tT1q+sSFVPDaTmNvlAoYHZ21lfMgXgx8SbUa6/GTeus6LAcHBx4olRMIqu73uq+iNjvEOV2xedXv1M5Hj7M5xbHjXsdyS2TbXIt5DrrSy7Xadr0U0PdVGFVE0dk1GJGpvGoFqUsFiIW2S8u3PR5dcvuMJEH4rVqydKkBZIEfg2nZReUEFK/cyVxBemsUHXTUBc3HWRF69B1Hurr68Py8rLntaOjo87mrXxfqKUARMSMOvGIv4nX6uLGVdQJKsx7dJBln31yLeSAWdwEqiWhhnSNjIwAeNJZRU4ckXsxCnTxuup4ALgs0KmpKWxubnrCHbu6ulKxhsUEoiYj6QhT1yUOaTacThITr5sEJiYmjGF44nPrmk6o9PT0YGhoyFPLXI4yun37tnbTtLu7G4D3vrh165bzGnlfREzM8sSjltkN+s7UCSrMe3TkYY+l08m9kPsRZJ2Jpa644dVNobGxMU9zXVHMyG+pqVqgaqEmsflVLBZjhdjpPqec2aha2LqwN1NdlyjnlI85ODjoSnAZHBx0/i9vDItr7keSkDjTJBAmDG9ychKrq6vG1Vh3d7cTRSM+vzp5rq2ted4nzqPeF2q3oP7+fmfy0008uuS0IMQEldYGMsWaZ5O2FHKTD1y1zvxS4wU9PT14//33ATyp8wxAu0ka1UrR+WuDPpMaZqlmMcqf1W+jT568om4s6o4pBEjnI5c3hsMKc9wIC9NmpxxuaGrOIa6jKSFoa2vLSTIytXs7fvw46vW6a/V1/vx57Ozs+FY7BODUZ5E/vzrx6JLTol6PqFCsefZpOyEPSvcG3GGH8s861HoV9Xrds9RU/cyyBaorcSrX7dD5a3WibQqz1B1f/qx+y+K4G4umY46NjRndKUcZ+iafS95oBZ40yFbj09XveWRkxBNqKNfa0Yk4Ywxnz551GksIhOUtu0aARnGtt99+23elkpYQp+G+IwHPLm0n5DofuJrxGGXzxrIs7cakn59ZDU2UU7+FD9TkrwW8wuoXZikLhC7VO2hZHMf/edRL7agRE2qVQL8oIYH6mUqlEubm5jzHtiwLPT09rtcKK1m3OpInWnXCvXnzprYHqQqJKBFE2wm5yQcuE1a8/Lr/BPmZ5SgRWUjq9bpx2WxZFhYXFz1jUycTNczSb7kdZNHFEeWjXGrrYqyDXFDq6kWO3BDF0YI+kym2fG5uDtPT09rPL0cEAU9quKjiLhCWe1CGZtLQPwodbH/aTsjDiEzYBBmdW0U+j26T1O9camNbeaz1et0VTww0RGd3d9dJBAIa4uBXw8V0TfysvTiifBRWoi7GOmjFoE7S9Xods7Oz+P73vw/btsE5x8LCghNC6pf5qGuhJvppTk9Pu8YpJlxd7fSenh5jmV0RtWLaY4kSg2+6hhQ62P60nZADwSIji5euzrOwbv2sVVkA/OqBqFEiqj+9XC5jb2/PU5+jVCphb2/PE8q2sbGB7e1tXLp0KVQdEp01phOvLD3c8ma1ruqfH6bvbHd313mNSI4BzPsDIoplfX0dvb29rggTIeZqtUMRUqiujtRJX66bwjn3jeWPGoOvQqGDnUFbCrnfUlIVYHk5fHBw4FnGmyIcolg55bK5sa2wOlX8kpLCPpC6cQLpZk2mjSlhS63VbUK3wlBb7AENgdzf3zeKnBzFsrOzg5MnTzqlak21y0WpYZOrRHapbW9vpx7Lr4NCBzuDthPyoIYNatig3C0FcHc9F+GKfj528aCL3we5WMT7hJ/W5Ivd2trSRqQA4WOIddaYGLP8uywJeZjN6iDUFYYpCUpe7Qhr3xS6atu209yjVCo5deajVg8N2zBZEKXGiqn/LIUOtj9tJ+R+S0ld2KDsThFuliDrRd0sq9frgVauWKoLi1/4aeWNTJnDw0aDBdkqHxgYcDrCh3kgTdZYGHdRqx74MJvVUVHdW7ooEhH6F1S+oVaruWLR5aikoGQn3UasfH7d51RrrKyvr2tLRAQ16E7j+8zC/UHoaTsh91tKmiwz0S0FQGCtFsD7cN29ezdUcSK58e7BwQGWl5extbWlteoYY54OQ7pyun4Pl84as20bZ8+eBeAWj6xsijXLgpT91JVKxZUaL8IN5YghuXyDXINcbk4d5Z4BvCs5kfHrl+Gr3rO65tjqsYMiseJc26zcH4SethJyedmqC8fTWWZyd56gzUtTdIJaOEkUJwLc7pa+vj6X9a2ray18sNPT0xgbG/OIhK4ZRtBKQLzv6tWrrgQkWTyytCnWzM1XsV8hT55ymz+BbF2rha1MFStt2/YtD6wzJAD/aBxxz/o1x5aP7beajCLGfjWKWn1/EF7aRsjD3qS6sEEgWBB1y2IxWagcHh7ie9/7ntMhXd5o9POpPvvss+jq6nKluMuipo5BZBGKc5oeLjkWWx6j/Pp22BQLa23KVQHVNn9AI8RThA6qeQCAfo8izP2nE2UgOBqnXA5uuhFmJRPFag+qUZTH+6OdaRshj2oxyAKplnbVbV6qy2K5ee3i4qJHoIWIi9eLY/px79497O3tYWdnB5ubm57qiOpnBMz+boEaiy3QJTC1alMsDd9rkqW/vOEtx38D3jwAU12dsPefLMqixELcaBzda4ImsDBirPssphpFcSBfe/q0jZAnsRh0CUKqKKh+ccuyjI1+VWSLS7e0Fq+RI2aE20XUBgGAWq3mqh0jREVeWahLe11UTKlUwtTUlNENc5Sk5XuNMpHLoaCcc9TrdaNIhZ3gZCs/jIXdiiSsKJ/FL4ktCeRrbw5tI+RJLEr1vaooLC8ve/zZ1WrVVfMEeJKSLaIYBLLFJUc7iEgZufu6uowXSSCiVnahUEB/f79TKU/2z+oeEFlggMaEoRPxVpGW7zXKRK57rZ9INWOCa8WkGfa86l5SUPORKBY2+dqbQyIhZ4z9PoB/D6AOYAXAr3DO7/q/Kz5BN0ySh0N9r2yRqI155aqF8usvXryIvb09p6jSs88+61mGm8Zo2zZ6eno8SUCiv6d884tJRX64TA9Iudwo4KV2jRfnbPUSNy3fa5SJXH0t4F3JBKHbDJSt/CgCpZbZzYKwqZ/JJLpRSwiQr705JLXIvwHgC5zzR4yx/wrgCwD+S/JheTE1Sk7zppcfTl1hf0F/f7/LQhebY3LTZgA4e/Zs4PjUphAC0dj3woULAOD5O+B+uPweEN3kkZUlbpq++SgTedBKxo80NwNNZXazIOamJDaZqCUEWrkX084kEnLO+T9JP34HwM8lG44ZXTJPGr0mBbqHU2xmCreGXIZ2e3vbszm2uLjoOubq6qpviVI/H/v4+DheeeUV52e5ZZdArbEe5QHJ0hK3VW4GIN51SHMzULZ6o4whzdWU6Vjlsj6JLen5Wvl9tytp+sh/FcBfpng8F6ZknrQEyM81oXtAdb9T253dvXsX1WrVuOSUz6ly967bQyW37DJFT0R5QGiJ2yDOdTC9J45AqbkFYcaQ5moq6FhyEpvueZObqIRp49dMsuAqbBWBQs4Y+yaA05o/fYlz/rePX/MlAI8AfM3nOK8BeA0AhoaGIg9U3YDxq08R5wv1izrQPaC638ntzg4ODpy2YKYlpywIamSJ3PNS/vy6zxXn89ISt0Gc65D2tZMTwcJsREddRfjdH0HH0k1a6vGmpqacFn+t2n/JiquwVQQKOef8435/Z4z9MoBPAvgY98l24Zy/DuB1AJiZmYlWaegxQjz9aoC3+gsV7c6uXr3qCLkJVRD29va0PS/l16f5eWmJ2yDOdUjr2qmuFTXMVUfYVYS6/6K7P4L84Lp7VK4QKrcdFBv2wNFX2MySq7AVJI1a+QSAzwO4xDn/YTpDCsbvIYr7hSaJOtARdskpf5ZyudH3UqTTi+P4jaPTb+A8obNS47h2wqwIdPsvulK9Ozs7OHfunFNvXZRUVptni41htdGHHIJ7cHCAxcVFdHd3H/k92emuwqQ+8j8B8AyAbzzuG/kdzvmvJR5VROQHJO4XmvaNIML+oi4vo0YxdPoNnBdMK6e4bpqgFYFu/0W+P+TxqH1F5+bmXJuafo0+RNtBuaiXqel5M+l0V2HSqJVzaQ0kLroHxO8L9duhT/tGkC2ZsHHKcaIYdNUMBWqRrU690VuN38opLTeNyaDRbY7L41E9ovKK1NToA2hEVonCbnL9GF0d+aPwmXeyqzD3mZ2mULCg5aau6UQzbrSoPmxdJqYufld3bNV9oz6EAIy+UvF6Evrm0OyVU1SDRh2P7F4pFouuiV8W/P7+fqeH7Ntvv40zZ86gXPYW9cpiieR2JvdCHuUBMVlFzbzRovqwhUtmeXnZeWBM8btBx9YV2TK9lh625EStDZ8mUQwa03jOnDkT6MMH3F20RDSW3+fTjU38noyGdMi9kEd5QEyi38wNw7ibWSdPnnSyR01jCjq2urwGYPRb0sOWjLBlbJNcR7+JIu59FrQiVZ8vUUog6Hh+Y9MVpTsq90u7knshB8I/ICbRb+ayN64lFmZMQcdW/w6YhTnsw0boaXb0UNBEEfY+U8UyTIii+nxFTQBSx2YyGuh+i09bCHkUdKLf7GVv3DjlMGMKOrb697BLbQprjEazfeBhvg/1u9aJttocRe2MFPRdR43GMnXeUq9VpVLx/XxkrfvTcUIuUG+MLO5468bUzBtaPV9QwSTiCc02BqJOFDoLXp0Mbty44RuiqDumTpTDjIExhvHxcViWhb6+Pte12tvbc/VQ5Zy77jfavwmmI4U8aunNVhK1R6f6njh/B5pXMCmvhL1mUa9P2InZNFGYwkt1Frw8GQDuLlYAMDo6akxAiyOmspXNOcdbb70F4EnrQ1GUTtfBSr7faHUYTEcKedTSm60iTo/OoAcuygMZVDCpUwhzzeKslKKKo8518sYbbzjfkUjsKRQKmJqa8tQOkieDSqXiEvITJ05gZmbGeG5ZTP2aRctjM22MyvfSzo63g5X6GnXTXu5YRDQotHoAhBld+GCxWARjzLgENm0khf27jHiA/M7XCQRdMyHI169fx5UrV7Q1dkRSmPy3KN+FjuXlZZcIypOu2gxFUC6XMTExgRMnTrh+/8wzz/ieS3WtiVaH6mcSqIltMvK9JO4xoDERiX+6Es0jIyMAGuWhTde5U+lIizxLpTf9UP2iao/OMKFefiGJQeLcbL9vXgi6ZkFLf782fGqkkF8GsGr1q64RmYcPHxprB9m27bQKFOzu7vpauWrnqs3NTWej1K8YlzwGoCHWk5OTzmvDRlYJ6z2oY1Gn0pFCHmXnvZW75SYhjeNLDft33fE69WHRdYyKE8NtEnr5u7Asy1cYdREnfkJ+4sQJ7O3tOSWShUVtambCOXdcIWI8Qrx1hs7Dhw99Jy/5s+3u7jo5EZxzz6QQNrKK6gqZ6UghB8IJVBZ2y+OGLuo2w+SJoFPFOSymjlE6giZHPwES38XS0lLoLN2DgwNPtyiVd9991/Xz/Pw8enp6XBuQKsJ3rrpEKpWKy+deKBQwOjqKhYUF3zrl4p+o5CnTDjX0sxQS2bFCHoa875ZnYSI6atJ6uMJ+92FC8sIIUBiXmFyDR+0gpaJuIIpNfXkDUs72BbxRLPJ76/W6ZxXb09MTKqJKdWWWSqXc19DP2rNFQu5DnpZyOgFr5kSUJWtEoHM/+PVM9SPMdx/lYQ4SoDAuMblvK+ccAwMDTj0eAOjp6cG9e/ecyBXOuauFHOCuudPb24vR0VGsr6+7WhSqyFEvqgtE/CyvKNSoFtWV6XdfpnFfHcW9mTUjj4Tch7SXckddYbFZE1HWrBGB6n6QO9lEHWOY7z7thzlI7EulkutnEXki/M8PHjzA9PS0M3kBcCxw4ecWjcSBxgbm/Pw8zp8/jzt37jgTwPDwMJ5++mmnGqKw3P1Qo1rq9bpr41Y2LizL0iabpXFfHdW9mTUjj4Q8gLSWcq2osNgsn2LWrBGBKVIi7hiDvvtmPsy6SV9tAyeEViBcIMLFY9u2qyY40GgaPj8/72w4igxPuWfo2NgYlpaWAq+fGKNlWVhfX9eOTdzrwBPXS6FQwHPPPYfd3V1Xslka99VR3ZtZ89eTkKdAGEs7zRtMPV+YzbQ0yZo1ItBFgTRzjEEPc9wV2MrKirOaKBQKOH36NLq6ulAqlbQTlUAOYTRFwZTLZRw7dswVOSIfR0wWurhx0xhV5I5Dcny8fP/LMeC6zNO439lR3ptZ8dcDJOSJCWtpp3WDmc53lNZB1qwRGfnhkjfjmuUWMz3McVdgasr64eGh4zoRGZv1et01UYkOQKVSyRFvnZiK86sx5AJ5IqjVaq6/yasBU1o9AJw6dQqDg4PaSVR2p6jnVTNP45aXyPK92UxIyBMS1tJO6wbzc6Mc5U2bJWvERCvdYnFXYKaUdXEc2XUiJirLslCv11GtVl21TYRvW7XUdcgCLLd1U+vX27aNxcVF7RiLxSIuXrzoiWgxuXWAht9/amoqVGhs2O8hD/dm2pCQJyRqpmTSGyyrbo12Jo4ox/2exPtUq1ogbwyqiUSq+IqonTt37uDatWuu48ihh6KJcr1e97R1Ozg4wODgIMpldxlc+TiiqqFlWY4bRXevl8tlTE1NuQrWySIeRFb3ZrIACXlCyK3R/sgx3CIUL4gkboKzZ89if38fXV1dePrpp52qgUAjsQeA1oWia3r85ptvGkMLT548Cdu2nQ3HyclJV6z61taW489WNyOBhhUvLPCwoZ9qKGKU+5eMGDMk5ClAbg1CR1Q3AQCtxStzeHiI9fV1l+Usv1YtQ3v79m3j+OQNx4ODA88GqOpjV4VUiDiQbuinibyEA7eCVIScMfY5AH8AoI9zTiXJWkg73ZxZQS7WpBagiouuIw4Az2agLjJlcHAQtm0HvhYAzpw547LoS6US7t6963mtmDDkhCHZx65uRqpuFMuynNWBvEpQk4OShuHmIRy4FSQWcsbYCwB+CsA7yYdDJKHdbs6skPaSXq3VLbtrZNeGDGMM/f39uHDhAoCG+6VarXqsaLXwlWVZGBoawnvvvYczZ87ggw8+8BStEn7uDz74wOVjP3fuHO7cuYNjx465Xl+r1bC4uOhcj9OnT2Nra8sR8eeff97lzpE3WFXLvVV+7nbzt6dhkf8RgM8D+NsUjkUkoN1uzqyQ9pJetvABOO4Q2dXBGENvb69LdE+ePAkATjMJUbtbtq5v3brlKXwlu24uX77sOkd/fz8A4O2333b2APr7+9Hf3++4R6rVKjY2NnDixAk8ePDAk4QkwiOBxmSi+uTl0MWg+PSjot387YmEnDH2KQC3OedvBqXxMsZeA/AaAAwNDSU5LWGg3W7OLJHmvoT6PYn0eVXgS6US7t2750pll5tJcM5RLpdd/m3Zty2QXTfy8fv7+7G9ve1y0XDOsbGxgVqt5jmOX9lcgS7SRr4P1exU9eejot2CBgKFnDH2TQCnNX/6EoAvouFWCYRz/jqA1wFgZmZGHyhLJKLdbs52pVxu9ENdX193QvsAvcCXSiVcu3YNnHPMz8+ju7vbdayDgwOMjo56wgtl5Eldjr6Rww1V9vb2In8u4aIR1r34HfDEnbS/v6+NT0+DqPtD7RQ0ECjknPOP637PGHsZwAgAYY0PAphjjH2Yc76V6iiJ0LTTzdmuyOntOzs7qFarjntF3Uzc3d113nd4eIhnnnnGZRk///zzvlYtYwznzp1zjilb80lbpRWLRZw6dcrlWrEsC6dPn3Y1klheXnZCGcWY+vv7nQxTec/A1Pw5iE7fH4rtWuGcXwfwvPiZMVYBMENRKwThRu10r6bgr66uYm1tzSU+QpRUl+Wzzz6LkydPOpEoN27ccPzcOjjnrqJYpqzR0dFRPHr0CO+88yRmoVwu4/333ze6VM6dO4czZ864RNqyLE8JgPv377tcOpxzp/xupVJxuYNEE4uo5Yc7fX+I4sgJoomoluLZs2cDu8bLoqQK8P7+Pvb39533CZ+2KtLyBCBb4TqKxSJKpZKTbCSP3Y8bN27g+PHjruPPzc1henra5cJ58OCB573yRKZehzgx6J2+P5SakHPOh9M6FkG0C6qlCOg3BHWd5YUonTt3zrGqZTeGjCr4nHOcOHECAwMDuHnzpmPdizBDeTLo6urC5uamseu9Cc451tfXXZ9FRLlMTU1hfX0dxWLRNeZSqYTnn3/eFdsu41fsy49O3x8ii5wgmohpA1MuUzs8POzyDauipCukpbPARcq94P79+3j77bdx/vx5ZyK4efMmJicnnRT/JDDG8Mwzz3h+v7+/76n/Iqzz0dFRj09/dHTU+b+o4BjHsu7k/SEScoJoIjpL0VQdUH2f/Hs5UUgUm6pWq7h3757ToOG9997zHOfw8NCVySkaN4cR8YGBAfT392Ntbc2ZIIrFomuFoDZ5BoCHDx+6ViEnTpzA/fv3XTVd1MlN/qxplh/uFJjJb9ZMZmZmuK6zNkEQeuTIjqeffhp37tzRptqriAgRubenSCQKcqUI0ZbdIENDQ3j//fddST9yaj5g9sWL17700kvOSsNPrKnchBfG2DXO+Yz6e7LICSIndHd3o16vh/IvAw3Bf/TokbMZKjM8POwcT24Zp/qo1aJbclQLAFelw1qt5jSHBhq+d9kXD7jrtviJc6eHE0aFhJwgMo6uDrgMYwwjIyPY3993bSx+8MEHzv/VRhPCnSH35gSA48ePO1mdhULBU3RLRi5jK8a5trbmuEyOHz/uEnK1iYQfnR5OGBUScoLIOGodcBVRvhaAMaoFgBOxIiM3sgAaG6RiYhBif/z4cayvr6O3txc3b97UlrEFvD1T5+bmXOcaHR11ib6f20TeJGaMoVarwbZtEnMDJOQEkSF0Aqd2DXrhhRfw3nvvOfHZIkN0YmICAwMDRjG/f/++4yuXE5DUFmzCQhfnHxsbw9jYGGzbdiYCUwamcJmolj7wpK5KGLeJGFelUkGlUsHq6ioqlYonwodoUGj1AAiiE7BtG0tLS9okG/G3lZUVXLlyBdevX8eVK1ec14raLMJ/ffv2bbz44osoFotgjLnC9C5cuIBCwftYFwoF14anKCErjl8qlXzHLMRXZKEGfT7RVUk+vxijzm2io1wuo7u729mUFVmw8rUhGpBFThBNxq8NGuBOxzclw9Trddff6vW6MQFGrnUCNMIIu7q6XBuRasu64eFhp/xtoVBAqVTyZKSafNYmC3t2dlZbQyVKFqbq+jGdv9OjW0jICaLJ+LVBkwVS3ZCUBU4nfmrkh2lTdHNzE+Pj464wwenpad9emrqMVJP4mjYmTZEpstskCNXFolZNpOiWBiTkBNFkZBEGvHVGZIH0a1oclIJu2hRVC2dNT09jbGzM8zpVeGVLuFQqYXh42FX8a2lpCX19fbHrnKytreHg4CDQ9y3GJZ9f1yu0k6NbSMgJosmo0RxyCroQMD+BXllZcWqXT0xMGM8j/NIi0kMXG845D9XMQfjlxephYWEBly5dwsTEhNYK1k0ywuVhWZZnclIFOMxmps7C7/RiWQIScoJIQFj/rCxCuhR003tXVlacphHb29t48OABLMsKPJ+wvOv1uieJKGx7NdUvr6vOKDZNJyYmAt08suvD5PvWlfT1o9OLZQlIyAkiJnH9s1GKO62vr7t+FoKsO5/cKk5Y3hMTE1haWnIdI2x7NZO1G6bvps7No/rPZd+3XC7g4OAAi4uLnjh1E51cLEtAQk4QMYnin40bWTE4OOhpZmw6n0l447ofTNZumL6blmV5Sgao55Z936qgb29vw7btjt28jAoJOUHEJKxAJomsEJuSusxK9Xwm4Q1yP/hNMnH80rZtY2FhwdlcHR8f93UHyYK+uLjoTFydvHkZFRJygohJWP9s0sgKkVkJAGfOnIlU/jbo92EmGVXogz636laxLMt3k1Ye48WLF2HbdsdvXkaFhJwgEhDGP5tmZEXa/mB141L1TZuE3m8cST4vbV7Gg4ScIJpMFsVJDg2Uo0e2t7dx584dJ9bclE4ftCpI8nlp8zI6JOQEcQRkSZx0JQPW19cd37RootzT0+Oxri3LCuXvz9Ln7QSoaBZBtDlqQSvVyq7X67h48aKr+YSoqCis65deegmXLl1CvV4PVfAqzDiI9EhskTPGPgPg1wEcAPg/nPPPJx4VQeSMLBZuEu3hRFifsKBNdVump6dddWD6+vq0nyuO/5tqojSXRELOGHsVwKcAvMI5f58x9nw6wyKI/JBFkbJtG5cvX3Yl2ggLemJiQuvDHhsbc2WdAtB+rjj+b6qJ0lySWuSfBvB7nPP3AYBzfif5kAgiX2RRpNRsScCdkBMmTHFpaSlSVUM/qCZKc0kq5OMAfoIx9rsA9gH8Fuf8e7oXMsZeA/AaNCU2vgAABXlJREFU0OjETRDtQh5EKkq/TEHaYZNZi9xpJ5jajsnzAsa+CeC05k9fAvC7AN4A8J8A/BiAvwQwygMOOjMzw69evRprwASRRbLmI5ddK4VCAbOzs7HGlbXP1ekwxq5xzmfU3wda5Jzzj/sc9NMAvv5YuP+ZMXYIoAwg/FY2QbQBWQu3UxtFxB1b1j4XoSepa+VvALwK4A3G2DgACwDFFhFEBiAR7hySCvlXAXyVMfYvAOoAfinIrUIQBBEGcuuEJ5GQc87rAH4hpbEQBEEAyGZIZ5ahzE6CaCPaJXvSVOOF0EO1VgiiTWgnKzYPIZ1ZgoScINqELCYm6Qjj+6a482iQkBNEm5AHKzbKqoGibsJDQk4QbUIerNi8rBryBgk5QbQRWbdi87BqyCMk5ARBHBl5WDXkERJygiCOlKyvGvIIxZETBEHkHBJygiCInENCThAEkXNIyAmCIHIOCTlBEETOISEnCILIOYGt3ppyUsZ2AKwd+YnDU0Z+G2TQ2FtDnscO5Hv8nTT2s5xzTxZVS4Q86zDGrur64uUBGntryPPYgXyPn8ZOrhWCIIjcQ0JOEASRc0jI9bze6gEkgMbeGvI8diDf4+/4sZOPnCAIIueQRU4QBJFzSMgJgiByDgm5D4yxzzDGlhlji4yx/9bq8USFMfY5xhhnjOWmZihj7PcfX/PvM8b+F2Ost9VjCoIx9gnG2FuMsZuMsd9u9XjCwhh7gTH2BmPsB4/v8c+2ekxRYYwVGWPzjLH/3eqxRIEx1ssY+6vH9/oSY+zfJDkeCbkBxtirAD4F4BXO+UUAf9DiIUWCMfYCgJ8C8E6rxxKRbwB4iXP+IQA3AHyhxePxhTFWBPCnAP4dgB8B8B8YYz/S2lGF5hGAz3HOfwTARwD8eo7GLvgsgKVWDyIGXwbwD5zzCwBeQcLPQEJu5tMAfo9z/j4AcM7vtHg8UfkjAJ8HkKvdbM75P3HOHz3+8TsABls5nhB8GMBNzvkq57wO4H+gYQBkHs75Jud87vH/76MhJmdaO6rwMMYGAfwMgK+0eixRYIz1APhJAH8GAJzzOuf8bpJjkpCbGQfwE4yx7zLGrjDGfqzVAwoLY+xTAG5zzt9s9VgS8qsA/m+rBxHAGQDvSj+vI0diKGCMDQOYAvDd1o4kEn+MhrFy2OqBRGQEwA6AP3/sFvoKY6w7yQE7utUbY+ybAE5r/vQlNK7Nc2gsOX8MwP9kjI3yjMRrBoz9i2i4VTKJ39g553/7+DVfQmPp/7WjHFsnwhg7DuCvAfwm5/xeq8cTBsbYJwHc4ZxfY4zNtno8EXkKwDSAz3DOv8sY+zKA3wbwO0kO2LFwzj9u+htj7NMAvv5YuP+ZMXaIRoGbnaManx+msTPGXkZjxn+TMQY0XBNzjLEPc863jnCIRvyuOwAwxn4ZwCcBfCwrE6cPtwG8IP08+Ph3uYAx9jQaIv41zvnXWz2eCHwUwM8yxn4aQBeAZxljf8E5/4UWjysM6wDWOedi9fNXaAh5bMi1YuZvALwKAIyxcQAWclBhjXN+nXP+POd8mHM+jMZNM50VEQ+CMfYJNJbLP8s5/2GrxxOC7wE4zxgbYYxZAH4ewN+1eEyhYI2Z/s8ALHHO/7DV44kC5/wLnPPBx/f4zwP4Vk5EHI+fxXcZYy8+/tXHAPwgyTE72iIP4KsAvsoY+xcAdQC/lAPrsB34EwDPAPjG4xXFdzjnv9baIZnhnD9ijP0GgH8EUATwVc75YouHFZaPAvhFANcZYwuPf/dFzvnft3BMncJnAHzt8eS/CuBXkhyMUvQJgiByDrlWCIIgcg4JOUEQRM4hIScIgsg5JOQEQRA5h4ScIAgi55CQEwRB5BwScoIgiJzz/wEl4JepY0vbOgAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
+      "text/plain": "<Figure size 432x288 with 1 Axes>",
+      "image/png": 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\n"
      },
      "metadata": {
       "needs_background": "light"
@@ -57,7 +53,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 12,
    "metadata": {
     "pycharm": {
      "is_executing": false,
@@ -67,22 +63,15 @@
    "outputs": [
     {
      "name": "stdout",
-     "output_type": "stream",
      "text": [
-      "[[ 2.90934205  3.97108298]\n",
-      " [ 2.01651379 -3.89961585]\n",
-      " [-0.02765316  0.05197939]\n",
-      " [-4.93744921 -1.04516013]] (4, 2)\n",
-      "1244.6696109096708\n",
-      "K-Means computed in: 0.003s\n"
-     ]
+      "[[ 2.90934205  3.97108298]\n [ 2.01142454 -3.88593535]\n [-4.93744921 -1.04516013]\n [-0.03634573  0.06470214]] (4, 2)\n1244.7784687926492\nK-Means computed in: 0.469s\n"
+     ],
+     "output_type": "stream"
     },
     {
      "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
+      "text/plain": "<Figure size 432x288 with 1 Axes>",
+      "image/png": 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\n"
      },
      "metadata": {
       "needs_background": "light"
@@ -116,7 +105,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 13,
    "metadata": {
     "pycharm": {
      "is_executing": false,
@@ -126,17 +115,15 @@
    "outputs": [
     {
      "name": "stdout",
-     "output_type": "stream",
      "text": [
       "Nearest mean search done in 1.59e+09s\n"
-     ]
+     ],
+     "output_type": "stream"
     },
     {
      "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
+      "text/plain": "<Figure size 432x288 with 1 Axes>",
+      "image/png": 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\n"
      },
      "metadata": {
       "needs_background": "light"
@@ -158,7 +145,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 14,
    "metadata": {
     "pycharm": {
      "is_executing": false,
@@ -176,7 +163,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 15,
    "metadata": {
     "pycharm": {
      "is_executing": false,
@@ -186,13 +173,10 @@
    "outputs": [
     {
      "name": "stdout",
-     "output_type": "stream",
      "text": [
-      "DB created in 0.0942s\n",
-      "Lenghts of #2: 1.00, #18: 1.00, #30: 1.00\n",
-      "First 10 weights of the 2nd image [0.01720561 0.01720561 0.03441123 0.03441123 0.01720561 0.03441123\n",
-      " 0.03441123 0.03441123 0.01720561 0.03441123]\n"
-     ]
+      "DB created in 0.0872s\nLenghts of #2: 1.00, #18: 1.00, #30: 1.00\nFirst 10 weights of the 2nd image [0.01720561 0.01720561 0.03441123 0.03441123 0.01720561 0.03441123\n 0.03441123 0.03441123 0.01720561 0.03441123]\n"
+     ],
+     "output_type": "stream"
     }
    ],
    "source": [
@@ -216,7 +200,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 16,
    "metadata": {
     "pycharm": {
      "is_executing": false,
@@ -226,21 +210,11 @@
    "outputs": [
     {
      "name": "stdout",
-     "output_type": "stream",
      "text": [
-      "query done in 0.003s\n",
-      "Ordering with query #1: [ 1  3  2  4  0  6 38 18 15  8] ...\n",
-      "Scores with query #1: [1.         0.41454077 0.36248969 0.32113335 0.30047525 0.26458203\n",
-      " 0.26048549 0.23940936 0.2281929  0.21324433] ...\n",
-      "query done in 0.005s\n",
-      "Ordering with query #17: [17 19 15 16 18 21 36 38 35 23] ...\n",
-      "Scores with query #17: [1.         0.488779   0.48785903 0.47457137 0.40553172 0.3009667\n",
-      " 0.28671491 0.28220734 0.27909532 0.276393  ] ...\n",
-      "query done in 0.004s\n",
-      "Ordering with query #29: [29 25 28 26 27 30 32 12 10  8] ...\n",
-      "Scores with query #29: [1.         0.77617251 0.76642581 0.76578309 0.74120908 0.2370221\n",
-      " 0.20867384 0.17483023 0.16542248 0.13262136] ...\n"
-     ]
+      "query done in 0.004s\nOrdering with query #1: [ 1  3  2  4  0  6 38 18 15  8] ...\nScores with query #1: [1.         0.41454077 0.36248969 0.32113335 0.30047525 0.26458203\n 0.26048549 0.23940936 0.2281929  0.21324433] ...\n",
+      "query done in 0.005s\nOrdering with query #17: [17 19 15 16 18 21 36 38 35 23] ...\nScores with query #17: [1.         0.488779   0.48785903 0.47457137 0.40553172 0.3009667\n 0.28671491 0.28220734 0.27909532 0.276393  ] ...\nquery done in 0.003s\nOrdering with query #29: [29 25 28 26 27 30 32 12 10  8] ...\nScores with query #29: [1.         0.77617251 0.76642581 0.76578309 0.74120908 0.2370221\n 0.20867384 0.17483023 0.16542248 0.13262136] ...\n"
+     ],
+     "output_type": "stream"
     }
    ],
    "source": [
@@ -268,7 +242,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 17,
    "metadata": {
     "pycharm": {
      "is_executing": false,
@@ -279,7 +253,8 @@
     {
      "name": "stdout",
      "text": [
-      "IDF weights of first 10 visual words: [[0.        ]\n [1.49165488]\n [2.59026717]\n [1.49165488]\n [2.59026717]\n [2.30258509]\n [2.59026717]\n [1.74296931]\n [1.89711998]\n [1.49165488]]\nTfidf db created in 0.103s\nLenghts of #2: 1.00, #18: 1.00, #30: 1.00\nFirst 10 weights of the 2nd image [0.02114542 0.01942724 0.02505479 0.03885449 0.01662608 0.03885449\n 0.04229083 0.02186477 0.01942724 0.03325216]\n"
+      "IDF weights of first 10 visual words: [[0.        ]\n [1.49165488]\n [2.59026717]\n [1.49165488]\n [2.59026717]\n [2.30258509]\n [2.59026717]\n [1.74296931]\n [1.89711998]\n [1.49165488]]\n",
+      "Tfidf db created in 0.0837s\nLenghts of #2: 1.00, #18: 1.00, #30: 1.00\nFirst 10 weights of the 2nd image [0.02114542 0.01942724 0.02505479 0.03885449 0.01662608 0.03885449\n 0.04229083 0.02186477 0.01942724 0.03325216]\n"
      ],
      "output_type": "stream"
     }
@@ -320,7 +295,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 18,
    "metadata": {
     "pycharm": {
      "is_executing": false,
@@ -331,7 +306,8 @@
     {
      "name": "stdout",
      "text": [
-      "query done in 0.003s\nOrdering with query #1: [ 1  3  2  4  0 18 38 15  6 16] ...\nScores with query #1: [1.         0.34769609 0.27926659 0.24722959 0.22218653 0.19315731\n 0.19033621 0.18754003 0.18137179 0.16862458] ...\nquery done in 0.004s\nOrdering with query #17: [17 15 16 19 18 36 21 23 38 35] ...\nScores with query #17: [1.         0.39321295 0.37421666 0.37148899 0.32282792 0.2145326\n 0.20846252 0.2039332  0.20305652 0.1999066 ] ...\nquery done in 0.003s\nOrdering with query #29: [29 25 28 26 27 30 32 12 33 31] ...\nScores with query #29: [1.         0.74945053 0.74755832 0.74576836 0.69990948 0.23522774\n 0.19714164 0.11651091 0.10915757 0.10866817] ...\n"
+      "query done in 0.003s\nOrdering with query #1: [ 1  3  2  4  0  6 38 18 15 16] ...\nScores with query #1: [0.94791945 0.35270807 0.30156876 0.2635144  0.24076235 0.22179365\n 0.21915386 0.20893068 0.20333552 0.18551524] ...\n",
+      "query done in 0.006s\nOrdering with query #17: [17 15 19 16 18 21 31 36 38 35] ...\nScores with query #17: [0.94763798 0.40451262 0.40104596 0.38776628 0.32864506 0.22977905\n 0.22949758 0.22775004 0.22145334 0.21935064] ...\nquery done in 0.004s\nOrdering with query #29: [29 25 28 26 27 30 32 12 31 33] ...\nScores with query #29: [0.96863615 0.75062597 0.7493514  0.73925355 0.71326389 0.26178122\n 0.23040533 0.12926027 0.12105814 0.11816718] ...\n"
      ],
      "output_type": "stream"
     }
@@ -348,22 +324,22 @@
     "# with idf = np.ones((num_visual_words, 1)) you should get following. With idf = get_idf(labels, num_visual_words), \n",
     "#   you should get max score = 1.0\n",
     "# Expected results:\n",
-    "# Ordering with query #1: [ 1  3  2  4  0 38 18  6 15 16] ...\n",
-    "# Scores with query #1: [1.86384425 0.73507323 0.60909155 0.53208607 0.48905146 0.40485071\n",
-    "#  0.40120768 0.38893817 0.3802747  0.34839662] ...\n",
+    "# Ordering with query #1: [ 1  3  2  4  0  6 38 18 15 16] ...\n",
+    "# Scores with query #1: [0.94791945 0.35270807 0.30156876 0.2635144  0.24076235 0.22179365\n",
+    "#  0.21915386 0.20893068 0.20333552 0.18551524] ...\n",
+    "# query done in 0.006s\n",
+    "# Ordering with query #17: [17 15 19 16 18 21 31 36 38 35] ...\n",
+    "# Scores with query #17: [0.94763798 0.40451262 0.40104596 0.38776628 0.32864506 0.22977905\n",
+    "#  0.22949758 0.22775004 0.22145334 0.21935064] ...\n",
     "# query done in 0.004s\n",
-    "# Ordering with query #17: [17 15 16 19 18 21 36 23 38 35] ...\n",
-    "# Scores with query #17: [1.78793393 0.82735267 0.79641385 0.7820111  0.69018981 0.47755897\n",
-    "#  0.46806813 0.44974778 0.44740665 0.4404922 ] ...\n",
-    "# query done in 0.002s\n",
-    "# Ordering with query #29: [29 26 25 28 27 30 32 12 10 33] ...\n",
-    "# Scores with query #29: [3.02196469 2.28403288 2.27227205 2.22677334 2.14190393 0.61222181\n",
-    "#  0.52785324 0.43436869 0.39584066 0.31937223] ..."
+    "# Ordering with query #29: [29 25 28 26 27 30 32 12 31 33] ...\n",
+    "# Scores with query #29: [0.96863615 0.75062597 0.7493514  0.73925355 0.71326389 0.26178122\n",
+    "#  0.23040533 0.12926027 0.12105814 0.11816718] ...\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {
     "pycharm": {
      "is_executing": false,
@@ -371,9 +347,47 @@
     }
    },
    "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "outputs": [],
+   "source": [],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n",
+     "is_executing": false
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "outputs": [],
+   "source": [],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n",
+     "is_executing": false
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
    "source": [
     "\n"
-   ]
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
   }
  ],
  "metadata": {