diff --git a/jupyter.ipynb b/jupyter.ipynb
index 0403147..85dc558 100644
--- a/jupyter.ipynb
+++ b/jupyter.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 1,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -13,7 +13,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/var/folders/t3/dwnz0lh916ng4w7bzf0z56ym0000gn/T/ipykernel_20610/17056051.py:11: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n",
+      "/var/folders/t3/dwnz0lh916ng4w7bzf0z56ym0000gn/T/ipykernel_26663/17056051.py:11: DeprecationWarning: Importing display from IPython.core.display is deprecated since IPython 7.14, please import from IPython display\n",
       "  from IPython.core.display import display, HTML\n"
      ]
     },
@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 2,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -113,7 +113,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 3,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -156,7 +156,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 4,
    "metadata": {
     "pycharm": {
      "name": "#%%\n"
@@ -191,12 +191,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
+   "execution_count": null,
    "outputs": [],
    "source": [
     "def compress_show_gray_images(img_name,k):\n",
@@ -213,28 +208,31 @@
     "    axes[1].set_title(\"compression ratio={:.2f}\".format(compression_ratio)+\"%\")\n",
     "    axes[1].imshow(reconst_img,cmap='gray')\n",
     "    axes[1].axis('off')\n",
-    "    fig.tight_layout()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {
-    "pycharm": {
-     "name": "#%% md\n"
-    }
-   },
-   "source": [
-    "W celu zbadania, jak jakość zrekonstruowanego obrazu zmienia się wraz z $k$ należy użyć poniższego interaktywnego widżetu."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 23,
+    "    fig.tight_layout()\n",
+    "    # compression rate = 100% * (k * (height + width + k)) / (height + width)"
+   ],
    "metadata": {
+    "collapsed": false,
     "pycharm": {
      "name": "#%%\n"
     }
-   },
+   }
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "W celu zbadania, jak jakość zrekonstruowanego obrazu zmienia się wraz z $k$ należy użyć poniższego interaktywnego widżetu."
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%% md\n"
+    }
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "outputs": [],
    "source": [
     "def compute_k_max(img_name):\n",
@@ -256,20 +254,24 @@
     "  int_slider_widget.max = compute_k_max(img_name)\n",
     "\n",
     "list_widget.observe(update_k_max,'value')\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 24,
+   ],
    "metadata": {
+    "collapsed": false,
     "pycharm": {
      "name": "#%%\n"
     }
-   },
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
    "outputs": [],
    "source": [
     "# Print matrices\n",
     "def print_matrices(img_name, k):\n",
+    "    if (img_name not in gray_images.keys()):\n",
+    "        return\n",
+    "    \n",
     "    image=gray_images[img_name]\n",
     "    original_shape = image.shape\n",
     "    print(f\"Input image dimensions. Width:{original_shape[1]} Height:{original_shape[0]}\")\n",
@@ -283,93 +285,57 @@
     "    print('*' * 100)\n",
     "    print(f\"Shape of V matrix: {V[:k,:].shape}\")\n",
     "    print(f\"V MATRIX: {V[:k,:]}\")\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
+   ],
    "metadata": {
+    "collapsed": false,
     "pycharm": {
      "name": "#%%\n"
     }
-   },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "97ddd455e9c8432c9d06874ef2d8d4c8",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'camera', 'coin', 'clock', 'te…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<function __main__.print_matrices(img_name, k)>"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
    "source": [
     "interact(print_matrices, img_name=list_widget, k=int_slider_widget)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
+   ],
    "metadata": {
+    "collapsed": false,
     "pycharm": {
      "name": "#%%\n"
     }
-   },
-   "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "845d2b4394b04d5681141aac8e9cbc29",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'camera', 'coin', 'clock', 'te…"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
    "source": [
     "interact(compress_show_gray_images,img_name=list_widget,k=int_slider_widget);"
-   ]
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
   },
   {
    "cell_type": "markdown",
+   "source": [
+    "### Ładowanie kolorowych obrazów"
+   ],
    "metadata": {
+    "collapsed": false,
     "pycharm": {
      "name": "#%% md\n"
     }
-   },
-   "source": [
-    "### Ładowanie kolorowych obrazów"
-   ]
+   }
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {
-    "pycharm": {
-     "name": "#%%\n"
-    }
-   },
+   "execution_count": null,
    "outputs": [],
    "source": [
     "color_images = {\n",
@@ -378,9 +344,16 @@
     "    \"coffee\":img_as_float(data.coffee()),\n",
     "    \"rocket\":img_as_float(data.rocket()),\n",
     "    \"koala\": img_as_float(Image.open('koala.jpeg')),\n",
-    "    \"orange\": img_as_float(Image.open('orange.jpeg'))\n",
-    "}"
-   ]
+    "    \"orange\": img_as_float(Image.open('orange.jpeg')),\n",
+    "    \"teacher\": img_as_float(Image.open('teacher.jpeg'))\n",
+    "}\n"
+   ],
+   "metadata": {
+    "collapsed": false,
+    "pycharm": {
+     "name": "#%%\n"
+    }
+   }
   },
   {
    "cell_type": "markdown",
@@ -489,12 +462,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "704a0aea9bc64cf991168a250b20c6a7",
+       "model_id": "4715b532b1d64abc9a8451cbfcfcc0e7",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'coffee', 'koala', 'orange'), …"
+       "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'coffee', 'rocket', 'koala', '…"
       ]
      },
      "metadata": {},
@@ -527,12 +500,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "a952305f0af44bbb89f18df43a922d7d",
+       "model_id": "f56619fa4fac4a6b9babba92ed3fb72a",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'coffee', 'koala', 'orange'), …"
+       "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'coffee', 'rocket', 'koala', '…"
       ]
      },
      "metadata": {},
@@ -629,10 +602,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {
     "pycharm": {
-     "is_executing": true,
      "name": "#%%\n"
     }
    },
@@ -640,12 +612,12 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5fcf1a7a0089474db6ae5775db349344",
+       "model_id": "4fa3385da3234652945d611efad33b62",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'coffee', 'koala', 'orange'), …"
+       "interactive(children=(Dropdown(description='img_name', options=('cat', 'astro', 'coffee', 'rocket', 'koala', '…"
       ]
      },
      "metadata": {},
@@ -661,7 +633,6 @@
    "execution_count": null,
    "metadata": {
     "pycharm": {
-     "is_executing": true,
      "name": "#%%\n"
     }
    },
@@ -673,7 +644,6 @@
    "execution_count": null,
    "metadata": {
     "pycharm": {
-     "is_executing": true,
      "name": "#%%\n"
     }
    },
diff --git a/teacher.jpeg b/teacher.jpeg
new file mode 100644
index 0000000..1437b7d
Binary files /dev/null and b/teacher.jpeg differ