test_traffic_network.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import cv2\n",
    "import pickle\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "%matplotlib inline\n",
    "\n",
    "\n",
    "from keras import backend as K\n",
    "from keras.models import Sequential, Model\n",
    "from keras.layers import Activation, Input, Embedding, LSTM, Dense, merge, Convolution2D, MaxPooling2D, Reshape, Flatten, Dropout\n",
    "from keras.optimizers import RMSprop, Adam\n",
    "from keras import initializations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def my_init(shape, name=None):\n",
    "    return initializations.normal(shape, scale=0.01, name=name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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1fFZmrLl+pbrgHVJuuHBON4j38mfw7ltSR8kTCGuiopziqd6+RuA7DjuAEXCj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\njdD/B8nAYT0LPUVLAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f7538299f10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "my_image = cv2.imread('im0002.png')\n",
    "my_image = cv2.resize(my_image, (32,32))\n",
    "plt.imshow(my_image)\n",
    "my_data = np.zeros(shape=(1,32,32,3))\n",
    "my_data[0,:,:,0] = my_image[:,:,2]\n",
    "my_data[0,:,:,1] = my_image[:,:,1]\n",
    "my_data[0,:,:,2] = my_image[:,:,0]\n",
    "my_data = my_data.astype(np.float32)/255\n",
    "my_data -= 0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Read data\n",
    "training_file = '/home/autti/Downloads/traffic-signs-data/train_p2.p'\n",
    "testing_file = '/home/autti/Downloads/traffic-signs-data/test_p2.p'\n",
    "\n",
    "\n",
    "with open(training_file, mode='rb') as f:\n",
    "    train = pickle.load(f)\n",
    "with open(testing_file, mode='rb') as f:\n",
    "    test = pickle.load(f)\n",
    "\n",
    "\n",
    "X_train, y_train = train['features'], train['labels']\n",
    "X_test, y_test = test['features'], test['labels']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[-0.20588234 -0.20980391 -0.17450979 ..., -0.23725489 -0.24509802\n",
      "  -0.24117646]\n",
      " [-0.17843136 -0.1862745  -0.15882352 ..., -0.21372548 -0.20588234\n",
      "  -0.19019607]\n",
      " [-0.19019607 -0.17058823 -0.14313725 ..., -0.21764705 -0.20980391\n",
      "  -0.19411764]\n",
      " ..., \n",
      " [-0.00588235 -0.0372549  -0.07647058 ..., -0.1235294  -0.1117647\n",
      "  -0.1117647 ]\n",
      " [-0.14705881 -0.14313725 -0.1980392  ..., -0.09215686 -0.08039215\n",
      "  -0.12745097]\n",
      " [-0.16666666 -0.13529411 -0.22941175 ..., -0.10392156 -0.11568627\n",
      "  -0.14705881]]\n",
      "('max', 42, 'min', 0)\n"
     ]
    }
   ],
   "source": [
    "# normalize data\n",
    "X_train = X_train.astype(np.float32)/255\n",
    "X_train -= 0.5\n",
    "X_test = X_test.astype(np.float32)/255\n",
    "X_test -= 0.5\n",
    "\n",
    "print(X_train[0,:,:,0])\n",
    "print(\"max\",np.max(y_train),\"min\",np.min(y_train))\n",
    "y_label_train = np.zeros(shape=(y_train.shape[0], np.max(y_train) + 1))\n",
    "y_label_test = np.zeros(shape=(y_test.shape[0], np.max(y_test) + 1))\n",
    "\n",
    "for i in range(y_train.shape[0]):\n",
    "    y_label_train[i, y_train[i]]=1\n",
    "\n",
    "for i in range(y_test.shape[0]):\n",
    "    y_label_test[i, y_test[i]]=1\n",
    "\n",
    "#X_train = X_train[:10]\n",
    "#y_label = y_label[:10]\n",
    "#print(y_label[-2:,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "prefix = 'traffic'\n",
    "model_path ='.model_{0}.h5'.format(prefix) \n",
    "sgd_select = Adam(lr=0.0001, beta_1=0.9, beta_2=0.999, epsilon=1e-08, decay=0.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('final', <tf.Tensor 'Softmax_1:0' shape=(?, 43) dtype=float32>)\n"
     ]
    }
   ],
   "source": [
    "# input layer\n",
    "main_input = Input(shape=(32, 32, 3), name='main_input')\n",
    "\n",
    "color_map = Convolution2D(3, 1, 1, init=my_init, border_mode='same')(main_input)\n",
    "\n",
    "conv1 = Convolution2D(32, 3, 3, init=my_init, border_mode='same')(color_map)\n",
    "conv2 = Convolution2D(32, 3, 3, init=my_init, border_mode='same')(conv1)\n",
    "pool1 = MaxPooling2D(pool_size=(3, 3))(conv2)\n",
    "drop1 = Dropout(0.5)(pool1)\n",
    "\n",
    "conv3 = Convolution2D(64, 3, 3, init=my_init, border_mode='same')(drop1)\n",
    "conv4 = Convolution2D(64, 3, 3, init=my_init, border_mode='same')(conv3)\n",
    "pool2 = MaxPooling2D(pool_size=(3, 3))(conv4)\n",
    "drop2 = Dropout(0.5)(pool2)\n",
    "\n",
    "conv5 = Convolution2D(128, 3, 3, init=my_init, border_mode='same')(drop2)\n",
    "conv6 = Convolution2D(128, 3, 3, init=my_init, border_mode='same')(conv5)\n",
    "pool3 = MaxPooling2D(pool_size=(3, 3))(conv6)\n",
    "drop3 = Dropout(0.5)(pool3)\n",
    "\n",
    "# flatten layer\n",
    "flat1 = Flatten()(drop1)\n",
    "flat2 = Flatten()(drop2)\n",
    "flat3 = Flatten()(drop3)\n",
    "\n",
    "# concatenate all vectors\n",
    "merged1 = merge([flat1, flat2, flat3], name='merge1', mode='concat',concat_axis = 1)\n",
    "\n",
    "fc1 = Dense(1024)(merged1)\n",
    "drop4 = Dropout(0.5)(fc1)\n",
    "\n",
    "fc2 = Dense(1024)(drop4)\n",
    "drop5 = Dropout(0.5)(fc2)\n",
    "\n",
    "softmax_layer = Dense(43)(drop5)\n",
    "main_output = Activation('softmax')(softmax_layer)\n",
    "print(\"final\", main_output)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12630/12630 [==============================] - 1s       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      "acc: 5.23%\n"
     ]
    }
   ],
   "source": [
    "sign_model = Model(input = [main_input], output = [main_output])\n",
    "sign_model.compile(optimizer = sgd_select, loss = 'categorical_crossentropy', metrics=['accuracy'])\n",
    "prefix = 'traffic'\n",
    "model_path ='.model_{0}.h5'.format(prefix)\n",
    "sign_model.load_weights(model_path)\n",
    "scores = sign_model.evaluate(X_test, y_label_test)\n",
    "print(\"%s: %.2f%%\" % (sign_model.metrics_names[1], scores[1]*100))\n",
    "#print(predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "predictions = sign_model.predict(my_data)\n",
    "print(predictions)\n",
    "my_pred = np.argmax(predictions) \n",
    "print(my_pred)\n",
    "print(predictions[0, my_pred])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "idx = y_train == my_pred\n",
    "class_11 = train['features'][idx]\n",
    "print(class_11.shape)\n",
    "print(np.sum(idx))\n",
    "plt.imshow(class_11[110,:,:,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plt.imshow(train['features'][2310,:,:,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for j in range(43):\n",
    "    plt.figure()\n",
    "    idy = y_train == j\n",
    "    class_y = train['features'][idy]\n",
    "    plt.imshow(class_y[1,:,:,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "idy = y_train == 1\n",
    "class_y = train['features'][idy]\n",
    "for j in range(200,228):\n",
    "    plt.figure()\n",
    "    plt.imshow(class_y[j,:,:,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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