31-satellite-widget.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
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   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import PIL\n",
    "import numpy as np\n",
    "\n",
    "scene = PIL.Image.open('data/scenes/sfbay_1.png')\n",
    "scene = np.array(scene).astype('uint8') / 255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ipywidgets import widgets\n",
    "from IPython.display import display,clear_output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/thead/anaconda/envs/toolbox-talk/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n",
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from keras.models import load_model\n",
    "\n",
    "net = load_model(\"conv-net.h5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "f4858631be2d4280836023d563e4990e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/html": [
       "<p>Failed to display Jupyter Widget of type <code>HBox</code>.</p>\n",
       "<p>\n",
       "  If you're reading this message in the Jupyter Notebook or JupyterLab Notebook, it may mean\n",
       "  that the widgets JavaScript is still loading. If this message persists, it\n",
       "  likely means that the widgets JavaScript library is either not installed or\n",
       "  not enabled. See the <a href=\"https://ipywidgets.readthedocs.io/en/stable/user_install.html\">Jupyter\n",
       "  Widgets Documentation</a> for setup instructions.\n",
       "</p>\n",
       "<p>\n",
       "  If you're reading this message in another frontend (for example, a static\n",
       "  rendering on GitHub or <a href=\"https://nbviewer.jupyter.org/\">NBViewer</a>),\n",
       "  it may mean that your frontend doesn't currently support widgets.\n",
       "</p>\n"
      ],
      "text/plain": [
       "HBox(children=(IntSlider(value=473, max=1777, min=1, orientation='vertical'), VBox(children=(Output(), IntSlider(value=1677, max=2825, min=1), Button(description='Run', style=ButtonStyle())))))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.ioff()\n",
    "fig, ax = plt.subplots(1, 1, figsize=(12,12))\n",
    "\n",
    "out = widgets.Output()\n",
    "button = widgets.Button(description='Run')\n",
    "width = widgets.IntSlider(min=1, max=scene.shape[1], value=1677)\n",
    "height = widgets.IntSlider(min=1, max=scene.shape[0], value=473,\n",
    "                           orientation='vertical')\n",
    "vbox = widgets.VBox(children=(out, width, button))\n",
    "hbox = widgets.HBox(children=(height, vbox))\n",
    "display(hbox)\n",
    "\n",
    "def run(b):\n",
    "    ax.clear()\n",
    "    \n",
    "    x = width.value\n",
    "    y = height.value\n",
    "\n",
    "    small_image = scene[y-40:y+40, x-40:x+40]\n",
    "    scene_ = np.array(scene)\n",
    "    scene_[:80, :80] = small_image\n",
    "    \n",
    "    p = net.predict(scene[np.newaxis,y-40:y+40, x-40:x+40,:3])\n",
    "\n",
    "    ax.imshow(scene_)\n",
    "    \n",
    "    xs = [x - 40, x+40, x+40, x-40, x-40]\n",
    "    ys = [y - 40, y-40, y+40, y+40, y-40]\n",
    "    ax.plot(xs, ys, c='r')\n",
    "    ax.set_xlabel(p)\n",
    "    \n",
    "    with out:\n",
    "        clear_output(wait=True)\n",
    "        display(ax.figure)\n",
    "\n",
    "button.on_click(run)\n",
    "run(None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[9.9981242e-01, 1.8761845e-04]], dtype=float32)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "net.predict(scene[np.newaxis,:80,:80,:3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(80, 80, 4)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scene[:80,:80].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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