keras/Visualization_sushi.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizatiton"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "%run ../oscilloscope/script/dataset.py\n",
    "\n",
    "from keras import layers\n",
    "from keras import models\n",
    "\n",
    "DATASET_FOLDER = \"../dataset/data_restaurant\"\n",
    "SAVED_MODEL = \"../dataset/data_restaurant/key_word_detection_cnn_20190325053252.h5\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['umai',\n",
       " 'mazui',\n",
       " 'oishii',\n",
       " 'silence',\n",
       " 'others',\n",
       " 'a',\n",
       " 'i',\n",
       " 'o',\n",
       " 'sushi',\n",
       " 'sashimi',\n",
       " 'gyouza',\n",
       " 'hashi',\n",
       " 'spoon',\n",
       " 'fork',\n",
       " 'syouyu',\n",
       " 'sakana',\n",
       " 'niku',\n",
       " 'gohan']"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = DataSet(DATASET_FOLDER)\n",
    "train_data, train_labels, test_data, test_labels = ds.generate(update=False, shuffle=False)['mfsc']\n",
    "\n",
    "model = models.load_model(SAVED_MODEL)\n",
    "ds.class_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_data, train_labels = ds.reshape_per_class(train_data, train_labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'sushi'"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x14e7574d0f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "l = ds.class_labels.index('sushi')\n",
    "image_number = 16\n",
    "\n",
    "plt.imshow(np.rot90(train_data[l, image_number,:,:,0]), cmap='gray')\n",
    "plt.savefig('input.png')\n",
    "ds.class_labels[np.argmax(train_labels[l, image_number])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "layer_outputs = [layer.output for layer in model.layers]\n",
    "activation_model = models.Model(inputs=model.input, outputs=layer_outputs)\n",
    "activations = activation_model.predict(train_data[l])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x14e7233d080>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_layer(activations, image_number, 0, 4)\n",
    "plt.savefig('layer0.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x14e76341f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_layer(activations, image_number, 1, 4)\n",
    "plt.savefig('layer1.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x14e76537e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_layer(activations, image_number, 3, 8)\n",
    "plt.savefig('layer3.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x14e76348d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_layer(activations, image_number, 4, 8)\n",
    "plt.savefig('layer4.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x14e7717da20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_layer(activations, image_number, 6, 16)\n",
    "plt.savefig('layer4.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x14e76ede208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_layer(activations, image_number, 7, 16)\n",
    "plt.savefig('layer5.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}