27-using-a-pretrained-convnet.ipynb

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    "<img src=\"http://akhavanpour.ir/notebook/images/srttu.gif\" alt=\"SRTTU\" style=\"width: 150px;\"/>\n",
    "\n",
    "[![Azure Notebooks](https://notebooks.azure.com/launch.png)](https://notebooks.azure.com/import/gh/Alireza-Akhavan/class.vision)"
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   "source": [
    "# <div style=\"direction:rtl;text-align:right;font-family:B Lotus, B Nazanin, Tahoma\">استفاده از شبکه‌های از قبل آموزش داده شده</div>\n"
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   "source": [
    "<div style=\"direction:rtl;text-align:right;font-family:Tahoma\">\n",
    "خطای رایج:\n",
    "<br>\n",
    "[cannot download vgg16_weights](https://github.com/fchollet/deep-learning-models/issues/33)\n",
    "<br>\n",
    "راهکار؟\n",
    "<br>\n",
    "</div>\n",
    "You can download it manually from here: https://github.com/fchollet/deep-learning-models/releases/download/v0.1/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
    "and paste it on\n",
    "~/.keras/models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
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   "outputs": [
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       "'C:\\\\Users\\\\A s u s/.keras/models'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import os\n",
    "os.path.expanduser('~/.keras/models')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
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    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "from keras.applications.vgg16 import VGG16\n",
    "from keras.preprocessing import image\n",
    "from keras.applications.vgg16 import preprocess_input, decode_predictions\n",
    "import numpy as np\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
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   "outputs": [],
   "source": [
    "\n",
    "model = VGG16(weights='imagenet')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predicted: [('n02504458', 'African_elephant', 0.75295341), ('n01871265', 'tusker', 0.2060758), ('n02504013', 'Indian_elephant', 0.040970467)]\n"
     ]
    }
   ],
   "source": [
    "img_path = './images/elephant.jpg'\n",
    "img = image.load_img(img_path, target_size=(224, 224))\n",
    "x = image.img_to_array(img)\n",
    "x = np.expand_dims(x, axis=0)\n",
    "x = preprocess_input(x)\n",
    "\n",
    "preds = model.predict(x)\n",
    "# decode the results into a list of tuples (class, description, probability)\n",
    "# (one such list for each sample in the batch)\n",
    "print('Predicted:', decode_predictions(preds, top=3)[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "<div style=\"direction:rtl;text-align:right;font-family:B Lotus, B Nazanin, Tahoma\"> دانشگاه تربیت دبیر شهید رجایی<br>مباحث ویژه - آشنایی با بینایی کامپیوتر<br>علیرضا اخوان پور<br>96-97<br>\n",
    "</div>\n",
    "<a href=\"https://www.srttu.edu/\">SRTTU.edu</a> - <a href=\"http://class.vision\">Class.Vision</a> - <a href=\"http://AkhavanPour.ir\">AkhavanPour.ir</a>\n",
    "</div>"
   ]
  }
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