IA Notebook #2 - Ataques adversarios.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# IA Notebook #2 - Ataques adversarios\n",
    "Aquí veremos cómo \"romper\" una red neuronal, usando como ejemplo práctico la IA \"Inception V3\", la cual es capaz de hacer reconocimiento de imágenes, pudiendo decir alto grado de probabilidad que hay en dicha imágen.\n",
    "\n",
    "**Nota: Se hizo uso de la versión 1.14.0 de Tensorflow, tener en cuenta antes de ejecutar. También revisar algunas rutas hacia algunos archivos, ya que después de las pruebas realizadas, se hizo una reorganización y se cambió de ruta pero el código no se ha ejecutado, por lo que no es del todo seguro que funcione.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:516: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:517: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:518: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:519: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:520: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\tensorflow\\python\\framework\\dtypes.py:525: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n",
      "C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\tensorboard\\compat\\tensorflow_stub\\dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\tensorboard\\compat\\tensorflow_stub\\dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\tensorboard\\compat\\tensorflow_stub\\dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\tensorboard\\compat\\tensorflow_stub\\dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\tensorboard\\compat\\tensorflow_stub\\dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\tensorboard\\compat\\tensorflow_stub\\dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n",
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "import keras\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "#Los errores mostrados son por lo que se está haciendo uso de una anterior versión de Tensorflow, no afecta al desarrollo de la actividad."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.applications.inception_v3 import InceptionV3, decode_predictions #Aquí importamos el modelo y una función que nos servirá más adelante.\n",
    "from keras import backend as k"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:4070: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.\n",
      "\n",
      "WARNING:tensorflow:From C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:4074: The name tf.nn.avg_pool is deprecated. Please use tf.nn.avg_pool2d instead.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "iv3=InceptionV3()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Resumen:\n"
     ]
    }
   ],
   "source": [
    "#Con esto podemos ver un recuentro de todas las capas del modelo\n",
    "print(\"Resumen:\")\n",
    "#print(iv3.summary())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2440, 1832, 3)\n"
     ]
    }
   ],
   "source": [
    "from keras.preprocessing import image\n",
    "\n",
    "#Con esto podemos cargar una imagen usando Keras:\n",
    "#ximg=image.load_img(\"./Recursos/Robot_Kuka.jpg\")\n",
    "\n",
    "#Pero para que el modelo lo pueda interpretar, convertimos la imagen a una matriz de números:\n",
    "x=image.img_to_array(image.load_img(\"./Recursos/IA Notebook #2/Robot_Kuka.jpg\"))\n",
    "\n",
    "#Con esto podemos ver la forma de la matriz que representa a la imagen:\n",
    "print(x.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "#### Analizando\n",
    "El resultado es:\n",
    "<p><b>(2440, 1832, 3)</b></p>\n",
    "Dónde el primero número representa el alto de la foto, el segundo el ancho y el tercero la profundidad de bit en número de canales, para este caso, los canales son RGB y es por eso que sale 3\n",
    "\n",
    "Pero hay que aclarar que es una matriz y por lo tanto, cada pixel está representado como elemento de dicha matriz.\n",
    "\n",
    "---\n",
    "### Continuando...\n",
    "El modelo InceptionV3 requiere que la matriz cumpla cierto requisitos determinados, como por ejemplo:\n",
    "- La imagen tiene que ser de una proporción de 299x299 pixeles\n",
    "- El rango en que varía el elemento de la matriz tiene que ser entre -1 y 1\n",
    "- Es necesario una dimension adicional que represente la cantidad de imagenes que se le van a dar como entrada al modelo\n",
    "\n",
    "_El rango representa la intensidad de cada pixel en la imagen._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "La forma de la nueva matriz es:  (299, 299, 3)\n",
      "Forma de la nueva matriz ya lista para el modelo:  (1, 299, 299, 3)\n"
     ]
    }
   ],
   "source": [
    "#Por lo indicado anteriormente, se reescribirá la variable ximg:\n",
    "x=image.img_to_array(image.load_img(\"./Recursos/IA Notebook #2/Robot_Kuka.jpg\",target_size=(299, 299)))\n",
    "\n",
    "print(\"La forma de la nueva matriz es: \",x.shape)\n",
    "\n",
    "#Ahora cambiamos el rango de intensidad de cada pixel:\n",
    "x=((x/255)-0.5)*2 #Con esto lo convertimos todo a rango de -1 a 1\n",
    "\n",
    "#Le asignamos la dimensión adicional que representa la cantidad de imagenes:\n",
    "x=x.reshape([1, x.shape[0], x.shape[1], x.shape[2]])\n",
    "print(\"Forma de la nueva matriz ya lista para el modelo: \",x.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From C:\\Users\\Moises\\anaconda3\\lib\\site-packages\\keras\\backend\\tensorflow_backend.py:422: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#Momento de la verdad, ahora vamos a ingresar nuestra matriz al modelo:\n",
    "y=iv3.predict(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tamaño o forma del resultado:  (1, 1000)\n"
     ]
    }
   ],
   "source": [
    "#Debido a la cantidad de clases que tiene el modelo\n",
    "#y que el modelo mismo le asigna una probabilidad a cada clase\n",
    "#es que se espera una matriz de una tamaño de mil:\n",
    "\n",
    "print(\"Tamaño o forma del resultado: \",y.shape)\n",
    "#print(\"------------------------------\\n El resultado como tal es:\\n\",y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[('n03995372', 'power_drill', 0.39098394),\n",
       "  ('n03109150', 'corkscrew', 0.054802377),\n",
       "  ('n03483316', 'hand_blower', 0.039984133),\n",
       "  ('n03208938', 'disk_brake', 0.017700238),\n",
       "  ('n04286575', 'spotlight', 0.0142612215)]]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "decode_predictions(y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inicio de la Mini Sección de Practica"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Forma de la nueva matriz ya lista para el modelo:  (1, 299, 299, 3)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[('n07749582', 'lemon', 0.9945656),\n",
       "  ('n07747607', 'orange', 0.0015342057),\n",
       "  ('n09229709', 'bubble', 0.0014557193),\n",
       "  ('n04509417', 'unicycle', 0.00055174314),\n",
       "  ('n07753592', 'banana', 0.00023650152)]]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Repitiendo el proceso pero más rápido y evaluando dos fotos por separado:\n",
    "\n",
    "#Ingresamos y converimos imagen a matriz:\n",
    "x2=image.img_to_array(image.load_img(\"./Recursos/IA Notebook #2/Robot_Kuka_hacked.png\"))\n",
    "#Ya no se hizo el redimensionamiento porque la imagen ya está con las dimensiones adecuadas.\n",
    "\n",
    "#Ahora cambiamos el rango de intensidad de cada pixel:\n",
    "x2=((x2/255)-0.5)*2 #Con esto lo convertimos todo a rango de -1 a 1\n",
    "\n",
    "#Le asignamos la dimensión adicional que representa la cantidad de imagenes:\n",
    "x2=x2.reshape([1, x2.shape[0], x2.shape[1], x2.shape[2]])\n",
    "print(\"Forma de la nueva matriz ya lista para el modelo: \",x2.shape)\n",
    "\n",
    "y2=iv3.predict(x2)\n",
    "decode_predictions(y2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Forma de la nueva matriz ya lista para el modelo:  (1, 299, 299, 3)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[[('n02786058', 'Band_Aid', 0.078878045),\n",
       "  ('n03982430', 'pool_table', 0.059184298),\n",
       "  ('n03838899', 'oboe', 0.04990664),\n",
       "  ('n03595614', 'jersey', 0.044796944),\n",
       "  ('n04584207', 'wig', 0.030533424)]]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x3=image.img_to_array(image.load_img(\"./Recursos/IA Notebook #2/persona4.jpg\",target_size=(299, 299)))\n",
    "\n",
    "x3=((x3/255)-0.5)*2\n",
    "\n",
    "x3=x3.reshape([1, x3.shape[0], x3.shape[1], x3.shape[2]])\n",
    "print(\"Forma de la nueva matriz ya lista para el modelo: \",x3.shape)\n",
    "\n",
    "y3=iv3.predict(x3)\n",
    "decode_predictions(y3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fin de la Mini Sección de Practica\n",
    "Y continuando..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ataque Adversario\n",
    "Lo que ahora haremos primero será seleccionar la entrada de la primera capa y la salidad de la última capa de nuestro modelo InceptioV3.\n",
    "Luego definimos la clase objetivo (target_class) a la que queremos llegar, modificando nuestra imagen inicial almacenada en \"x\", de esta manera estaremos engañando al modelo, haciendole pensar que la imagen es de la clase que hemos definido.\n",
    "\n",
    "También definimos una función de coste (loss), teniendo en cuenta que la última capa de nuestra red (o modelo) es la que nos da las probabilidades de que sea una clase u otra.\n",
    "<b>Aún no encuentro el significado sobre lo que se está haciendo con la función de coste, según dotCSV es una \"función\" pero en términos informáticos como enfocamos los valores dados en los corchetes?</b>\n",
    "\n",
    "_\"Con esto le estamos diciendo, es que nuestra función de coste que queremos maximizar es el resultado, la probabilidad de la clase 951, es decir, de todo el vector de probabilidades que nos proporciona, queremos que esa sea la clase maximizada.\"_\n",
    "\n",
    "Luego se crea la variable \"grad\" de gradiente, para almacenar el tensor cuyos valores nos dirán en que proporción tienen que variar los pixeles de nuestra imagen para que poco a poco la función de coste se vaya optimizando.\n",
    "La función \"k.gradients\" lo que hace es justamente aplicar ese método o algoritmo del \"descenso del gradiente\", con lo cual, nos dará como resultado una matriz y por razones no del todo claras, solo usaremos el primer elemento de dicha matriz.\n",
    "\n",
    "Ahora será necesario crear la función que se encargará de hacer este proceso del gradiente de manera iterativa (en bucle) y para ello se hace uso de la función Keras, y lo que se le suministra a está tipo de funciones es, por un lado, los valores que le vamos a dar de entrada y por otro lado, cuales son los resultados que esperamos como salida, y automáticamente crea todo el grafo necesario para realizar esa función.\n",
    "\n",
    "Por último, hacemos tres \"sencillos\" pasos, el primero es hacer una copia de nuestra variable x, y la segunda es crear una variable de coste la cual nos dirá si ya hemos llegado o no a nuestro objetivo, y la tercera es crear el bucle while dónde nuestra condición será la variable de coste, y este bucle ejecutará sin parar la función de optimizaciónd el gradiente, además de que se lo ira sumando a nuestra variable para ir modificando la copia de nuestra imagen."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Costo objetivo o target cost:  0.000101386424\n",
      "Costo objetivo o target cost:  0.000101713296\n",
      "Costo objetivo o target cost:  0.00010210419\n",
      "Costo objetivo o target cost:  0.000102570404\n",
      "Costo objetivo o target cost:  0.000103057064\n",
      "Costo objetivo o target cost:  0.00010354299\n",
      "Costo objetivo o target cost:  0.00010403965\n",
      "Costo objetivo o target cost:  0.000104542625\n",
      "Costo objetivo o target cost:  0.00010504624\n",
      "Costo objetivo o target cost:  0.00010555655\n",
      "Costo objetivo o target cost:  0.000106069616\n",
      "Costo objetivo o target cost:  0.00010658538\n",
      "Costo objetivo o target cost:  0.0001071011\n",
      "Costo objetivo o target cost:  0.00010761904\n",
      "Costo objetivo o target cost:  0.00010814476\n",
      "Costo objetivo o target cost:  0.00010868336\n",
      "Costo objetivo o target cost:  0.00010922961\n",
      "Costo objetivo o target cost:  0.00010977617\n",
      "Costo objetivo o target cost:  0.00011032877\n",
      "Costo objetivo o target cost:  0.00011087107\n",
      "Costo objetivo o target cost:  0.00011139239\n",
      "Costo objetivo o target cost:  0.000111903166\n",
      "Costo objetivo o target cost:  0.00011241365\n",
      "Costo objetivo o target cost:  0.00011293588\n",
      "Costo objetivo o target cost:  0.00011346399\n",
      "Costo objetivo o target cost:  0.00011398906\n",
      "Costo objetivo o target cost:  0.00011451309\n",
      "Costo objetivo o target cost:  0.00011504467\n",
      "Costo objetivo o target cost:  0.00011557414\n",
      "Costo objetivo o target cost:  0.00011610512\n",
      "Costo objetivo o target cost:  0.0001166475\n",
      "Costo objetivo o target cost:  0.00011719853\n",
      "Costo objetivo o target cost:  0.0001177486\n",
      "Costo objetivo o target cost:  0.00011831258\n",
      "Costo objetivo o target cost:  0.00011887915\n",
      "Costo objetivo o target cost:  0.000119442964\n",
      "Costo objetivo o target cost:  0.00012000622\n",
      "Costo objetivo o target cost:  0.000120571494\n",
      "Costo objetivo o target cost:  0.000121129546\n",
      "Costo objetivo o target cost:  0.00012168501\n",
      "Costo objetivo o target cost:  0.00012224194\n",
      "Costo objetivo o target cost:  0.00012279976\n",
      "Costo objetivo o target cost:  0.00012335985\n",
      "Costo objetivo o target cost:  0.00012391698\n",
      "Costo objetivo o target cost:  0.00012447235\n",
      "Costo objetivo o target cost:  0.00012503339\n",
      "Costo objetivo o target cost:  0.00012559601\n",
      "Costo objetivo o target cost:  0.00012615752\n",
      "Costo objetivo o target cost:  0.00012672496\n",
      "Costo objetivo o target cost:  0.00012730082\n",
      "Costo objetivo o target cost:  0.00012788172\n",
      "Costo objetivo o target cost:  0.00012846431\n",
      "Costo objetivo o target cost:  0.00012904599\n",
      "Costo objetivo o target cost:  0.00012963032\n",
      "Costo objetivo o target cost:  0.0001302161\n",
      "Costo objetivo o target cost:  0.00013080261\n",
      "Costo objetivo o target cost:  0.0001313916\n",
      "Costo objetivo o target cost:  0.00013198818\n",
      "Costo objetivo o target cost:  0.00013259311\n",
      "Costo objetivo o target cost:  0.00013320002\n",
      "Costo objetivo o target cost:  0.00013380623\n",
      "Costo objetivo o target cost:  0.0001344147\n",
      "Costo objetivo o target cost:  0.00013501542\n",
      "Costo objetivo o target cost:  0.00013561938\n",
      "Costo objetivo o target cost:  0.00013622791\n",
      "Costo objetivo o target cost:  0.00013684366\n",
      "Costo objetivo o target cost:  0.000137468\n",
      "Costo objetivo o target cost:  0.00013809852\n",
      "Costo objetivo o target cost:  0.00013872857\n",
      "Costo objetivo o target cost:  0.00013935995\n",
      "Costo objetivo o target cost:  0.00013999731\n",
      "Costo objetivo o target cost:  0.00014063015\n",
      "Costo objetivo o target cost:  0.00014125787\n",
      "Costo objetivo o target cost:  0.00014188586\n",
      "Costo objetivo o target cost:  0.00014252696\n",
      "Costo objetivo o target cost:  0.00014317219\n",
      "Costo objetivo o target cost:  0.00014382241\n",
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      "Costo objetivo o target cost:  0.0008682228\n",
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      "Costo objetivo o target cost:  0.0010035833\n",
      "Costo objetivo o target cost:  0.0010096031\n",
      "Costo objetivo o target cost:  0.0010156501\n",
      "Costo objetivo o target cost:  0.0010218327\n",
      "Costo objetivo o target cost:  0.001027846\n",
      "Costo objetivo o target cost:  0.0010342258\n",
      "Costo objetivo o target cost:  0.0010404696\n",
      "Costo objetivo o target cost:  0.0010467386\n",
      "Costo objetivo o target cost:  0.0010531286\n",
      "Costo objetivo o target cost:  0.0010595362\n",
      "Costo objetivo o target cost:  0.0010662342\n",
      "Costo objetivo o target cost:  0.001072798\n",
      "Costo objetivo o target cost:  0.0010795855\n",
      "Costo objetivo o target cost:  0.0010863527\n",
      "Costo objetivo o target cost:  0.001093175\n",
      "Costo objetivo o target cost:  0.0011000589\n",
      "Costo objetivo o target cost:  0.0011070115\n",
      "Costo objetivo o target cost:  0.001114018\n",
      "Costo objetivo o target cost:  0.0011210301\n",
      "Costo objetivo o target cost:  0.001128181\n",
      "Costo objetivo o target cost:  0.0011354365\n",
      "Costo objetivo o target cost:  0.001142811\n",
      "Costo objetivo o target cost:  0.0011502191\n",
      "Costo objetivo o target cost:  0.0011578465\n",
      "Costo objetivo o target cost:  0.0011655589\n",
      "Costo objetivo o target cost:  0.0011733146\n",
      "Costo objetivo o target cost:  0.0011810835\n",
      "Costo objetivo o target cost:  0.001188984\n",
      "Costo objetivo o target cost:  0.0011969154\n",
      "Costo objetivo o target cost:  0.0012048878\n",
      "Costo objetivo o target cost:  0.0012128233\n",
      "Costo objetivo o target cost:  0.0012206276\n",
      "Costo objetivo o target cost:  0.0012285418\n",
      "Costo objetivo o target cost:  0.0012364995\n",
      "Costo objetivo o target cost:  0.001244491\n",
      "Costo objetivo o target cost:  0.0012525632\n",
      "Costo objetivo o target cost:  0.001260648\n",
      "Costo objetivo o target cost:  0.0012688027\n",
      "Costo objetivo o target cost:  0.0012768806\n",
      "Costo objetivo o target cost:  0.0012850185\n",
      "Costo objetivo o target cost:  0.0012932419\n",
      "Costo objetivo o target cost:  0.001301512\n",
      "Costo objetivo o target cost:  0.0013099704\n",
      "Costo objetivo o target cost:  0.0013186007\n",
      "Costo objetivo o target cost:  0.0013272371\n",
      "Costo objetivo o target cost:  0.0013357536\n",
      "Costo objetivo o target cost:  0.0013442723\n",
      "Costo objetivo o target cost:  0.0013530513\n",
      "Costo objetivo o target cost:  0.0013618609\n",
      "Costo objetivo o target cost:  0.0013707256\n",
      "Costo objetivo o target cost:  0.0013797072\n",
      "Costo objetivo o target cost:  0.0013887123\n",
      "Costo objetivo o target cost:  0.0013978987\n",
      "Costo objetivo o target cost:  0.0014072832\n",
      "Costo objetivo o target cost:  0.0014166244\n",
      "Costo objetivo o target cost:  0.0014262561\n",
      "Costo objetivo o target cost:  0.0014361836\n",
      "Costo objetivo o target cost:  0.0014460953\n",
      "Costo objetivo o target cost:  0.001455982\n",
      "Costo objetivo o target cost:  0.0014660795\n",
      "Costo objetivo o target cost:  0.0014762295\n",
      "Costo objetivo o target cost:  0.0014867096\n",
      "Costo objetivo o target cost:  0.0014971767\n",
      "Costo objetivo o target cost:  0.0015075889\n",
      "Costo objetivo o target cost:  0.0015179588\n",
      "Costo objetivo o target cost:  0.001528238\n",
      "Costo objetivo o target cost:  0.0015387114\n",
      "Costo objetivo o target cost:  0.0015491181\n",
      "Costo objetivo o target cost:  0.0015596253\n",
      "Costo objetivo o target cost:  0.0015700618\n",
      "Costo objetivo o target cost:  0.0015807503\n",
      "Costo objetivo o target cost:  0.001591085\n",
      "Costo objetivo o target cost:  0.0016020365\n",
      "Costo objetivo o target cost:  0.0016125785\n",
      "Costo objetivo o target cost:  0.0016230929\n",
      "Costo objetivo o target cost:  0.0016336223\n",
      "Costo objetivo o target cost:  0.0016437228\n",
      "Costo objetivo o target cost:  0.0016542003\n",
      "Costo objetivo o target cost:  0.0016647589\n",
      "Costo objetivo o target cost:  0.0016756362\n",
      "Costo objetivo o target cost:  0.0016863643\n",
      "Costo objetivo o target cost:  0.00169712\n",
      "Costo objetivo o target cost:  0.001707824\n",
      "Costo objetivo o target cost:  0.0017186466\n",
      "Costo objetivo o target cost:  0.0017301552\n",
      "Costo objetivo o target cost:  0.0017414644\n",
      "Costo objetivo o target cost:  0.0017527585\n",
      "Costo objetivo o target cost:  0.0017639234\n",
      "Costo objetivo o target cost:  0.001774827\n",
      "Costo objetivo o target cost:  0.001785809\n",
      "Costo objetivo o target cost:  0.0017964907\n",
      "Costo objetivo o target cost:  0.001807872\n",
      "Costo objetivo o target cost:  0.0018189661\n",
      "Costo objetivo o target cost:  0.0018308151\n",
      "Costo objetivo o target cost:  0.0018420136\n",
      "Costo objetivo o target cost:  0.0018539641\n",
      "Costo objetivo o target cost:  0.0018653674\n",
      "Costo objetivo o target cost:  0.0018772901\n",
      "Costo objetivo o target cost:  0.0018886973\n",
      "Costo objetivo o target cost:  0.001900161\n",
      "Costo objetivo o target cost:  0.0019113774\n",
      "Costo objetivo o target cost:  0.0019230316\n",
      "Costo objetivo o target cost:  0.0019342599\n",
      "Costo objetivo o target cost:  0.0019462004\n",
      "Costo objetivo o target cost:  0.0019584203\n",
      "Costo objetivo o target cost:  0.0019708963\n",
      "Costo objetivo o target cost:  0.001983813\n",
      "Costo objetivo o target cost:  0.0019968674\n",
      "Costo objetivo o target cost:  0.0020092628\n",
      "Costo objetivo o target cost:  0.002024283\n",
      "Costo objetivo o target cost:  0.002038017\n",
      "Costo objetivo o target cost:  0.0020529223\n",
      "Costo objetivo o target cost:  0.002067347\n",
      "Costo objetivo o target cost:  0.0020823444\n",
      "Costo objetivo o target cost:  0.0020979317\n",
      "Costo objetivo o target cost:  0.0021140429\n",
      "Costo objetivo o target cost:  0.0021298607\n",
      "Costo objetivo o target cost:  0.002146064\n",
      "Costo objetivo o target cost:  0.0021616183\n",
      "Costo objetivo o target cost:  0.002178019\n",
      "Costo objetivo o target cost:  0.0021937683\n",
      "Costo objetivo o target cost:  0.0022106557\n",
      "Costo objetivo o target cost:  0.0022268784\n",
      "Costo objetivo o target cost:  0.0022451011\n",
      "Costo objetivo o target cost:  0.0022609513\n",
      "Costo objetivo o target cost:  0.0022773591\n",
      "Costo objetivo o target cost:  0.0022953872\n",
      "Costo objetivo o target cost:  0.0023140607\n",
      "Costo objetivo o target cost:  0.0023325528\n",
      "Costo objetivo o target cost:  0.0023514084\n",
      "Costo objetivo o target cost:  0.0023697012\n",
      "Costo objetivo o target cost:  0.00238778\n",
      "Costo objetivo o target cost:  0.0024065424\n",
      "Costo objetivo o target cost:  0.0024260078\n",
      "Costo objetivo o target cost:  0.0024450608\n",
      "Costo objetivo o target cost:  0.0024635752\n",
      "Costo objetivo o target cost:  0.0024824992\n",
      "Costo objetivo o target cost:  0.002505354\n",
      "Costo objetivo o target cost:  0.0025257596\n",
      "Costo objetivo o target cost:  0.0025466266\n",
      "Costo objetivo o target cost:  0.0025672205\n",
      "Costo objetivo o target cost:  0.0025887182\n",
      "Costo objetivo o target cost:  0.002610526\n",
      "Costo objetivo o target cost:  0.0026321337\n",
      "Costo objetivo o target cost:  0.0026545716\n",
      "Costo objetivo o target cost:  0.0026751775\n",
      "Costo objetivo o target cost:  0.0026987444\n",
      "Costo objetivo o target cost:  0.0027205953\n",
      "Costo objetivo o target cost:  0.0027452942\n",
      "Costo objetivo o target cost:  0.0027691533\n",
      "Costo objetivo o target cost:  0.0027950401\n",
      "Costo objetivo o target cost:  0.0028189984\n",
      "Costo objetivo o target cost:  0.0028440421\n",
      "Costo objetivo o target cost:  0.0028703217\n",
      "Costo objetivo o target cost:  0.0028948989\n",
      "Costo objetivo o target cost:  0.0029203717\n",
      "Costo objetivo o target cost:  0.0029483018\n",
      "Costo objetivo o target cost:  0.0029748038\n",
      "Costo objetivo o target cost:  0.0030020806\n",
      "Costo objetivo o target cost:  0.0030303071\n",
      "Costo objetivo o target cost:  0.0030609022\n",
      "Costo objetivo o target cost:  0.0030899176\n",
      "Costo objetivo o target cost:  0.0031205995\n",
      "Costo objetivo o target cost:  0.0031470316\n",
      "Costo objetivo o target cost:  0.0031761993\n",
      "Costo objetivo o target cost:  0.0032063858\n",
      "Costo objetivo o target cost:  0.003241404\n",
      "Costo objetivo o target cost:  0.0032688673\n",
      "Costo objetivo o target cost:  0.0033053749\n",
      "Costo objetivo o target cost:  0.0033322463\n",
      "Costo objetivo o target cost:  0.0033698906\n",
      "Costo objetivo o target cost:  0.003399084\n",
      "Costo objetivo o target cost:  0.0034375908\n",
      "Costo objetivo o target cost:  0.003467887\n",
      "Costo objetivo o target cost:  0.003507069\n",
      "Costo objetivo o target cost:  0.0035495127\n",
      "Costo objetivo o target cost:  0.003591265\n",
      "Costo objetivo o target cost:  0.0036258034\n",
      "Costo objetivo o target cost:  0.003669485\n",
      "Costo objetivo o target cost:  0.003675586\n",
      "Costo objetivo o target cost:  0.0037254982\n",
      "Costo objetivo o target cost:  0.003721744\n",
      "Costo objetivo o target cost:  0.0038170728\n",
      "Costo objetivo o target cost:  0.0037869504\n",
      "Costo objetivo o target cost:  0.0039150277\n",
      "Costo objetivo o target cost:  0.003969881\n",
      "Costo objetivo o target cost:  0.0040051034\n",
      "Costo objetivo o target cost:  0.0039740005\n",
      "Costo objetivo o target cost:  0.0040908013\n",
      "Costo objetivo o target cost:  0.0040678103\n",
      "Costo objetivo o target cost:  0.004209517\n",
      "Costo objetivo o target cost:  0.0042403243\n",
      "Costo objetivo o target cost:  0.0042859116\n",
      "Costo objetivo o target cost:  0.0042646816\n",
      "Costo objetivo o target cost:  0.0043974994\n",
      "Costo objetivo o target cost:  0.004438036\n",
      "Costo objetivo o target cost:  0.004499181\n",
      "Costo objetivo o target cost:  0.0044593294\n",
      "Costo objetivo o target cost:  0.0046427352\n",
      "Costo objetivo o target cost:  0.0046880585\n",
      "Costo objetivo o target cost:  0.0047440133\n",
      "Costo objetivo o target cost:  0.0046609486\n",
      "Costo objetivo o target cost:  0.004912981\n",
      "Costo objetivo o target cost:  0.004968816\n",
      "Costo objetivo o target cost:  0.0050451374\n",
      "Costo objetivo o target cost:  0.0048860065\n",
      "Costo objetivo o target cost:  0.0052215713\n",
      "Costo objetivo o target cost:  0.005327179\n",
      "Costo objetivo o target cost:  0.005265448\n",
      "Costo objetivo o target cost:  0.0054826685\n",
      "Costo objetivo o target cost:  0.005355164\n",
      "Costo objetivo o target cost:  0.005592265\n",
      "Costo objetivo o target cost:  0.005492928\n",
      "Costo objetivo o target cost:  0.0058270283\n",
      "Costo objetivo o target cost:  0.0058981916\n",
      "Costo objetivo o target cost:  0.006019142\n",
      "Costo objetivo o target cost:  0.005756527\n",
      "Costo objetivo o target cost:  0.006255407\n",
      "Costo objetivo o target cost:  0.0063977735\n",
      "Costo objetivo o target cost:  0.0061470084\n",
      "Costo objetivo o target cost:  0.0064925873\n",
      "Costo objetivo o target cost:  0.0063215834\n",
      "Costo objetivo o target cost:  0.0067003444\n",
      "Costo objetivo o target cost:  0.006586923\n",
      "Costo objetivo o target cost:  0.006613597\n",
      "Costo objetivo o target cost:  0.006409229\n",
      "Costo objetivo o target cost:  0.006973497\n",
      "Costo objetivo o target cost:  0.0071741133\n",
      "Costo objetivo o target cost:  0.0071957847\n",
      "Costo objetivo o target cost:  0.006968825\n",
      "Costo objetivo o target cost:  0.0075881956\n",
      "Costo objetivo o target cost:  0.007745297\n",
      "Costo objetivo o target cost:  0.007883775\n",
      "Costo objetivo o target cost:  0.0082028685\n",
      "Costo objetivo o target cost:  0.008067416\n",
      "Costo objetivo o target cost:  0.008509489\n",
      "Costo objetivo o target cost:  0.007942717\n",
      "Costo objetivo o target cost:  0.008546284\n",
      "Costo objetivo o target cost:  0.008787532\n",
      "Costo objetivo o target cost:  0.009065744\n",
      "Costo objetivo o target cost:  0.008830838\n",
      "Costo objetivo o target cost:  0.009139177\n",
      "Costo objetivo o target cost:  0.008586419\n",
      "Costo objetivo o target cost:  0.009512308\n",
      "Costo objetivo o target cost:  0.009945498\n",
      "Costo objetivo o target cost:  0.009925749\n",
      "Costo objetivo o target cost:  0.009367975\n",
      "Costo objetivo o target cost:  0.010766798\n",
      "Costo objetivo o target cost:  0.010641277\n",
      "Costo objetivo o target cost:  0.010622431\n",
      "Costo objetivo o target cost:  0.010223341\n",
      "Costo objetivo o target cost:  0.0112662185\n",
      "Costo objetivo o target cost:  0.011512232\n",
      "Costo objetivo o target cost:  0.0114272125\n",
      "Costo objetivo o target cost:  0.01135806\n",
      "Costo objetivo o target cost:  0.011669213\n",
      "Costo objetivo o target cost:  0.012265335\n",
      "Costo objetivo o target cost:  0.0136019075\n",
      "Costo objetivo o target cost:  0.013646929\n",
      "Costo objetivo o target cost:  0.014111805\n",
      "Costo objetivo o target cost:  0.0140609015\n",
      "Costo objetivo o target cost:  0.014626086\n",
      "Costo objetivo o target cost:  0.014349909\n",
      "Costo objetivo o target cost:  0.015764756\n",
      "Costo objetivo o target cost:  0.015415774\n",
      "Costo objetivo o target cost:  0.016773792\n",
      "Costo objetivo o target cost:  0.017097136\n",
      "Costo objetivo o target cost:  0.01805059\n",
      "Costo objetivo o target cost:  0.017025068\n",
      "Costo objetivo o target cost:  0.01980673\n",
      "Costo objetivo o target cost:  0.02008424\n",
      "Costo objetivo o target cost:  0.022000553\n",
      "Costo objetivo o target cost:  0.021815486\n",
      "Costo objetivo o target cost:  0.022829954\n",
      "Costo objetivo o target cost:  0.023682596\n",
      "Costo objetivo o target cost:  0.025768615\n",
      "Costo objetivo o target cost:  0.026094483\n",
      "Costo objetivo o target cost:  0.024219016\n",
      "Costo objetivo o target cost:  0.028433194\n",
      "Costo objetivo o target cost:  0.025973078\n",
      "Costo objetivo o target cost:  0.03237521\n",
      "Costo objetivo o target cost:  0.029098429\n",
      "Costo objetivo o target cost:  0.03663043\n",
      "Costo objetivo o target cost:  0.037980605\n",
      "Costo objetivo o target cost:  0.04050442\n",
      "Costo objetivo o target cost:  0.035078116\n",
      "Costo objetivo o target cost:  0.04600097\n",
      "Costo objetivo o target cost:  0.04369841\n",
      "Costo objetivo o target cost:  0.05274541\n",
      "Costo objetivo o target cost:  0.054917496\n",
      "Costo objetivo o target cost:  0.064542614\n",
      "Costo objetivo o target cost:  0.06649498\n",
      "Costo objetivo o target cost:  0.08132041\n",
      "Costo objetivo o target cost:  0.071472675\n",
      "Costo objetivo o target cost:  0.08619996\n",
      "Costo objetivo o target cost:  0.110415116\n",
      "Costo objetivo o target cost:  0.079626545\n",
      "Costo objetivo o target cost:  0.14140178\n",
      "Costo objetivo o target cost:  0.19628751\n",
      "Costo objetivo o target cost:  0.10867516\n",
      "Costo objetivo o target cost:  0.23272847\n",
      "Costo objetivo o target cost:  0.16169652\n",
      "Costo objetivo o target cost:  0.21672302\n",
      "Costo objetivo o target cost:  0.24421644\n",
      "Costo objetivo o target cost:  0.18315773\n",
      "Costo objetivo o target cost:  0.4191469\n",
      "Costo objetivo o target cost:  0.22732307\n",
      "Costo objetivo o target cost:  0.41627938\n",
      "Costo objetivo o target cost:  0.3761658\n",
      "Costo objetivo o target cost:  0.4392161\n",
      "Costo objetivo o target cost:  0.5088676\n",
      "Costo objetivo o target cost:  0.2285537\n",
      "Costo objetivo o target cost:  0.48920473\n",
      "Costo objetivo o target cost:  0.27007014\n",
      "Costo objetivo o target cost:  0.36362225\n",
      "Costo objetivo o target cost:  0.088358186\n",
      "Costo objetivo o target cost:  0.8496072\n",
      "Costo objetivo o target cost:  0.9564958\n"
     ]
    }
   ],
   "source": [
    "in_layer=iv3.layers[0].input\n",
    "out_layer=iv3.layers[-1].output\n",
    "\n",
    "#Las salida son tensores:\n",
    "#print(in_layer)\n",
    "#print(out_layer)\n",
    "\n",
    "#Clase objetivo\n",
    "target_class=951 #La clase limón está referenciada por este número.\n",
    "\n",
    "#Función de coste:\n",
    "loss=out_layer[0, target_class] #Aún no encuentro como funciona esto, si son parámetros o la forma de acceder a una matriz.\n",
    "\n",
    "#Gradiente o descenso del gradiente\n",
    "grad=k.gradients(loss, in_layer)[0]\n",
    "\n",
    "#Gradiente optimizado u optimizo gradiente\n",
    "optimize_gradient=k.function([in_layer, k.learning_phase()], [grad, loss])\n",
    "#Para el caso de Keras, es necesario decirle en la parte de entrada la acción que estás queriendo realizar, si vas a entrenar o vas a testear.\n",
    "#Y en nuestro caso es la de entrenar, por eso usamos \"k.learning_phase()\"\n",
    "\n",
    "#Copia de la variable x en la variable adv, es solo para poder salvaguardar la original.\n",
    "adv=np.copy(x)\n",
    "\n",
    "#--------------------------------------------------------------------------------------\n",
    "#Esto sección es para definir los valores límite de cuanto puede modificar y no, nuestros valores para llegar al resultado de imagen adversaria.\n",
    "perturbacion=0.01\n",
    "\n",
    "max_pert = x+0.01\n",
    "min_pert = x-0.01\n",
    "#--------------------------------------------------------------------------------------\n",
    "\n",
    "#Variable de coste\n",
    "cost=0.0\n",
    "\n",
    "#Bucle iterativo\n",
    "while cost<0.95:\n",
    "    #Ya que nuestra función Keras, le hemos dicho antes que nos devuelva dos salidas, [grad, loss], es que tenemos:\n",
    "    gr, cost = optimize_gradient([adv, 0])\n",
    "    \n",
    "    #Aquí le sumamos a nuestra imagen, las variaciones que tiene que sufrir.\n",
    "    adv += gr\n",
    "    \n",
    "    #--------------------------------------------------------------------------------------\n",
    "    #Ahora, con los valroes limites establecidos, hacemos:\n",
    "    adv = np.clip(adv, min_pert, max_pert)\n",
    "    adv = np.clip(adv, -1, 1) #Esto es para asegurarnos de que siempre esté dentro de los valores que pueda procesar el modelo.\n",
    "    #--------------------------------------------------------------------------------------\n",
    "    \n",
    "    #Vamos viendo como se comporta nuestra función de coste y si va aumentando:\n",
    "    print(\"Costo objetivo o target cost: \", cost)\n",
    "\n",
    "#Guaramos una copia del resultado, el cual es un tensor.\n",
    "hacked = np.copy(adv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "adv = ((adv/2)+0.5)*255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(adv[0].astype(np.uint8)) #Aquí convertimos los números de la matriz en valores enteros.\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Esto es solo para mantener el resultado anterior:\n",
    "#plt.imshow(adv[0].astype(np.uint8)) #Aquí convertimos los números de la matriz en valores enteros.\n",
    "#plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "from PIL import Image\n",
    "\n",
    "img_generada=Image.fromarray(adv[0].astype(np.uint8))\n",
    "\n",
    "img_generada.save(\"./Recursos/IA Notebook #2/Robot_Kuka_hacked.png\")"
   ]
  }
 ],
 "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": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}