original_capsnet_test.ipynb

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   "source": [
    "# Original CapsNet Model Test\n",
    "\n",
    "In this notebook we provide a simple interface to test the original CapsNet model described in \"Dynamic routinig between capsules\". The model is copycat of the original Sara's repository (https://github.com/Sarasra/models/tree/master/research/capsules) and also the weights, provided with our repository, are derived from the original ones. "
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   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
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   "source": [
    "import tensorflow as tf\n",
    "from utils import Dataset, plotImages, plotWrongImages\n",
    "from models import CapsNet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "gpus = tf.config.experimental.list_physical_devices('GPU')\n",
    "tf.config.experimental.set_visible_devices(gpus[0], 'GPU')\n",
    "tf.config.experimental.set_memory_growth(gpus[0], True)"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "# some parameters\n",
    "model_name = 'MNIST' # only MNIST is available\n",
    "n_routing = 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1.0 Import the Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "dataset = Dataset(model_name, config_path='config.json') # only MNIST"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.1 Visualize imported dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-25T22:03:11.531218Z",
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   "outputs": [],
   "source": [
    "n_images = 20 # number of images to be plotted\n",
    "plotImages(dataset.X_test[:n_images,...,0], dataset.y_test[:n_images], n_images, dataset.class_names)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2.0 Load the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-25T22:03:15.707231Z",
     "start_time": "2021-01-25T22:03:14.733048Z"
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   },
   "outputs": [],
   "source": [
    "model_test = CapsNet(model_name, mode='test', verbose=True, n_routing=n_routing)\n",
    "\n",
    "model_test.load_graph_weights() # load graph weights (bin folder)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3.0 Test the Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-25T22:03:25.415576Z",
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   },
   "outputs": [],
   "source": [
    "model_test.evaluate(dataset.X_test, dataset.y_test) # if \"smallnorb\" use X_test_patch\n",
    "y_pred = model_test.predict(dataset.X_test)[0] # if \"smallnorb\" use X_test_patch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3.1 Plot misclassified images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-25T22:03:26.222073Z",
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   },
   "outputs": [],
   "source": [
    "n_images = 20\n",
    "plotWrongImages(dataset.X_test, dataset.y_test, y_pred, # if \"smallnorb\" use X_test_patch\n",
    "                n_images, dataset.class_names)"
   ]
  }
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