006-Data-Augmentation-Fashion.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "VTEGN4bfZheT"
   },
   "source": [
    "# Data Augementation - Fashion MNIST"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 34,
     "output_extras": [
      {
       "item_id": 1
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     ]
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 2572,
     "status": "ok",
     "timestamp": 1521300228267,
     "user": {
      "displayName": "Amit Kapoor",
      "photoUrl": "//lh4.googleusercontent.com/-D2AEUHCgcx8/AAAAAAAAAAI/AAAAAAAAAoY/0HFe1PWxMvQ/s50-c-k-no/photo.jpg",
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    "id": "JGQqwCPRZheX",
    "outputId": "5946c5b4-c22b-4cd0-c30a-1377e3d0140d"
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   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "import keras\n",
    "import tensorflow as tf\n",
    "import matplotlib.pyplot as plt\n",
    "% matplotlib inline\n",
    "import vis\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get Data "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-labels-idx1-ubyte.gz\n",
      "32768/29515 [=================================] - 0s 2us/step\n",
      "Downloading data from http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/train-images-idx3-ubyte.gz\n",
      "26427392/26421880 [==============================] - 5s 0us/step\n",
      "Downloading data from http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-labels-idx1-ubyte.gz\n",
      "8192/5148 [===============================================] - 0s 0us/step\n",
      "Downloading data from http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/t10k-images-idx3-ubyte.gz\n",
      "4423680/4422102 [==============================] - 6s 1us/step\n"
     ]
    }
   ],
   "source": [
    "from keras.datasets import fashion_mnist\n",
    "(x_train, y_train), (x_test, y_test) = fashion_mnist.load_data()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels = vis.fashion_mnist_label()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Step 1: Prepare the images and labels**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "id": "h9TfoY-OZhel"
   },
   "outputs": [],
   "source": [
    "# Reshape data for convlution network\n",
    "x_train_conv = x_train.reshape(x_train.shape[0], 28, 28, 1)\n",
    "x_test_conv = x_test.reshape(x_test.shape[0], 28, 28, 1)\n",
    "input_shape = (28, 28, 1)\n",
    "\n",
    "# Convert from 'uint8' to 'float32' and normalise the data to (0,1) \n",
    "x_train_conv =  x_train_conv.astype(\"float32\") / 255\n",
    "x_test_conv = x_test_conv.astype(\"float32\") / 255\n",
    "\n",
    "# convert class vectors to binary class matrices\n",
    "y_train_class = keras.utils.to_categorical(y_train, 10)\n",
    "y_test_class = keras.utils.to_categorical(y_test, 10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Augmentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras.preprocessing.image import ImageDataGenerator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# this will do preprocessing and realtime data augmentation\n",
    "datagen = ImageDataGenerator(\n",
    "    featurewise_center=False,  # set input mean to 0 over the dataset\n",
    "    samplewise_center=False,  # set each sample mean to 0\n",
    "    featurewise_std_normalization=False,  # divide inputs by std of the dataset\n",
    "    samplewise_std_normalization=False,  # divide each input by its std\n",
    "    rotation_range=25,  # randomly rotate images in the range (degrees, 0 to 180)\n",
    "    width_shift_range=0.1,  # randomly shift images horizontally (fraction of total width)\n",
    "    height_shift_range=0.1,  # randomly shift images vertically (fraction of total height)\n",
    "    horizontal_flip=False,  # randomly flip images\n",
    "    vertical_flip=False)  # randomly flip images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Set up the generator\n",
    "datagen.fit(x_train_conv)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us see the image augmentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(1, 28, 28, 1)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train_conv[:1].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "datagen.fit(x_train_conv[:1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "samples = datagen.flow(x_train_conv[:1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
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",
      "text/plain": [
       "<VegaLite 2 object>\n",
       "\n",
       "If you see this message, it means the renderer has not been properly enabled\n",
       "for the frontend that you are using. For more information, see\n",
       "https://altair-viz.github.io/user_guide/troubleshooting.html\n"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vis.imshow(x_train_conv[:1].squeeze())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "range(0, 3)"
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "range(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.vegalite.v2+json": {
       "$schema": "https://vega.github.io/schema/vega-lite/v2.4.3.json",
       "config": {
        "view": {
         "height": 300,
         "width": 400
        }
       },
       "hconcat": [
        {
         "data": {
          "values": [
           {
            "h": 0,
            "value": 0,
            "w": 0
           },
           {
            "h": 1,
            "value": 0,
            "w": 0
           },
           {
            "h": 2,
            "value": 0,
            "w": 0
           },
           {
            "h": 3,
            "value": 0,
            "w": 0
           },
           {
            "h": 4,
            "value": 0,
            "w": 0
           },
           {
            "h": 5,
            "value": 0,
            "w": 0
           },
           {
            "h": 6,
            "value": 0,
            "w": 0
           },
           {
            "h": 7,
            "value": 0,
            "w": 0
           },
           {
            "h": 8,
            "value": 0,
            "w": 0
           },
           {
            "h": 9,
            "value": 0,
            "w": 0
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",
      "text/plain": [
       "<VegaLite 2 object>\n",
       "\n",
       "If you see this message, it means the renderer has not been properly enabled\n",
       "for the frontend that you are using. For more information, see\n",
       "https://altair-viz.github.io/user_guide/troubleshooting.html\n"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "image = []\n",
    "for i in range(3):\n",
    "    img = samples.next()\n",
    "    img = img.squeeze()\n",
    "    image.append(vis.imshow(img))\n",
    "image[0] | image[1] | image[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "4tBPvzcCZher"
   },
   "source": [
    "**Step 2: Build a CNN Model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "id": "r9pjXQCeZhet"
   },
   "outputs": [],
   "source": [
    "from keras.models import Sequential\n",
    "from keras.layers import Conv2D, MaxPooling2D, Dropout, Flatten, Dense"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "id": "ashEa0JgZhez"
   },
   "outputs": [],
   "source": [
    "cnn = Sequential()\n",
    "cnn.add(Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=(28,28,1)))\n",
    "cnn.add(MaxPooling2D(pool_size=(2, 2)))\n",
    "cnn.add(Conv2D(64, kernel_size=(3, 3), activation='relu'))\n",
    "cnn.add(MaxPooling2D(pool_size=(2, 2)))\n",
    "cnn.add(Dropout(0.25))\n",
    "cnn.add(Conv2D(128, kernel_size=(3, 3), activation='relu'))\n",
    "cnn.add(Dropout(0.25))\n",
    "cnn.add(Flatten())\n",
    "cnn.add(Dense(128, activation='relu'))\n",
    "cnn.add(Dropout(0.25))\n",
    "cnn.add(Dense(10, activation='softmax'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 510,
     "output_extras": [
      {
       "item_id": 1
      }
     ]
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 935,
     "status": "ok",
     "timestamp": 1521297709045,
     "user": {
      "displayName": "Amit Kapoor",
      "photoUrl": "//lh4.googleusercontent.com/-D2AEUHCgcx8/AAAAAAAAAAI/AAAAAAAAAoY/0HFe1PWxMvQ/s50-c-k-no/photo.jpg",
      "userId": "115841624057400778059"
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     "user_tz": -330
    },
    "id": "fA1RAzF0Zhe5",
    "outputId": "32471482-71ab-4a36-fe94-08712d8fcc96"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_4 (Conv2D)            (None, 26, 26, 32)        320       \n",
      "_________________________________________________________________\n",
      "max_pooling2d_3 (MaxPooling2 (None, 13, 13, 32)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_5 (Conv2D)            (None, 11, 11, 64)        18496     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_4 (MaxPooling2 (None, 5, 5, 64)          0         \n",
      "_________________________________________________________________\n",
      "dropout_4 (Dropout)          (None, 5, 5, 64)          0         \n",
      "_________________________________________________________________\n",
      "conv2d_6 (Conv2D)            (None, 3, 3, 128)         73856     \n",
      "_________________________________________________________________\n",
      "dropout_5 (Dropout)          (None, 3, 3, 128)         0         \n",
      "_________________________________________________________________\n",
      "flatten_2 (Flatten)          (None, 1152)              0         \n",
      "_________________________________________________________________\n",
      "dense_3 (Dense)              (None, 128)               147584    \n",
      "_________________________________________________________________\n",
      "dropout_6 (Dropout)          (None, 128)               0         \n",
      "_________________________________________________________________\n",
      "dense_4 (Dense)              (None, 10)                1290      \n",
      "=================================================================\n",
      "Total params: 241,546\n",
      "Trainable params: 241,546\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "cnn.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Step 3: Compile the Model and Fit**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "id": "hPGTcN3WZhfO"
   },
   "outputs": [],
   "source": [
    "cnn.compile(loss='categorical_crossentropy', optimizer=\"adam\", metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n",
      "1875/1875 [==============================] - 106s 57ms/step - loss: 0.7674 - acc: 0.7090 - val_loss: 0.5192 - val_acc: 0.8016\n",
      "Epoch 2/5\n",
      "1875/1875 [==============================] - 106s 56ms/step - loss: 0.5600 - acc: 0.7865 - val_loss: 0.4407 - val_acc: 0.8306\n",
      "Epoch 3/5\n",
      "1875/1875 [==============================] - 144s 77ms/step - loss: 0.5035 - acc: 0.8083 - val_loss: 0.3897 - val_acc: 0.8584\n",
      "Epoch 4/5\n",
      "1875/1875 [==============================] - 172s 92ms/step - loss: 0.4646 - acc: 0.8260 - val_loss: 0.3812 - val_acc: 0.8600\n",
      "Epoch 5/5\n",
      "1875/1875 [==============================] - 193s 103ms/step - loss: 0.4420 - acc: 0.8354 - val_loss: 0.3550 - val_acc: 0.8705\n"
     ]
    }
   ],
   "source": [
    "# fits the model on batches with real-time data augmentation:\n",
    "history = cnn.fit_generator(datagen.flow(x_train_conv, y_train_class, batch_size=32), \n",
    "                             validation_data=(x_test_conv, y_test_class), use_multiprocessing=True,\n",
    "                     steps_per_epoch=len(x_train_conv) / 32, epochs=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Step 4: Check the performance of the model**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 377,
     "output_extras": [
      {
       "item_id": 1
      }
     ]
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1343,
     "status": "ok",
     "timestamp": 1521297971102,
     "user": {
      "displayName": "Amit Kapoor",
      "photoUrl": "//lh4.googleusercontent.com/-D2AEUHCgcx8/AAAAAAAAAAI/AAAAAAAAAoY/0HFe1PWxMvQ/s50-c-k-no/photo.jpg",
      "userId": "115841624057400778059"
     },
     "user_tz": -330
    },
    "id": "jWNH9RV1Zhgn",
    "outputId": "c21ca629-8d68-40b4-aebd-7c778904b832"
   },
   "outputs": [
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",
      "text/plain": [
       "<VegaLite 2 object>\n",
       "\n",
       "If you see this message, it means the renderer has not been properly enabled\n",
       "for the frontend that you are using. For more information, see\n",
       "https://altair-viz.github.io/user_guide/troubleshooting.html\n"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vis.metrics(history.history)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 51,
     "output_extras": [
      {
       "item_id": 1
      }
     ]
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 1837,
     "status": "ok",
     "timestamp": 1521297989943,
     "user": {
      "displayName": "Amit Kapoor",
      "photoUrl": "//lh4.googleusercontent.com/-D2AEUHCgcx8/AAAAAAAAAAI/AAAAAAAAAoY/0HFe1PWxMvQ/s50-c-k-no/photo.jpg",
      "userId": "115841624057400778059"
     },
     "user_tz": -330
    },
    "id": "1kYojZ0QZhgv",
    "outputId": "85194a0a-6b41-405a-ece4-0b46ef7b7f4b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10000/10000 [==============================] - 9s 931us/step\n",
      "Test loss: 0.35502173528671266\n",
      "Test accuracy: 0.8705\n"
     ]
    }
   ],
   "source": [
    "score = cnn.evaluate(x_test_conv, y_test_class)\n",
    "print('Test loss:', score[0])\n",
    "print('Test accuracy:', score[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     },
     "base_uri": "https://localhost:8080/",
     "height": 68,
     "output_extras": [
      {
       "item_id": 67
      }
     ]
    },
    "colab_type": "code",
    "executionInfo": {
     "elapsed": 24216,
     "status": "ok",
     "timestamp": 1521301117139,
     "user": {
      "displayName": "Amit Kapoor",
      "photoUrl": "//lh4.googleusercontent.com/-D2AEUHCgcx8/AAAAAAAAAAI/AAAAAAAAAoY/0HFe1PWxMvQ/s50-c-k-no/photo.jpg",
      "userId": "115841624057400778059"
     },
     "user_tz": -330
    },
    "id": "S_TAmT3dZhiR",
    "outputId": "ce0edf2e-1b6e-4667-b347-76d668c1e1d7"
   },
   "source": [
    "**Step 5: Make & Visualise the Prediction**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "colab": {
     "autoexec": {
      "startup": false,
      "wait_interval": 0
     }
    },
    "colab_type": "code",
    "id": "qOJk0ncjcBoa"
   },
   "outputs": [],
   "source": [
    "predict_classes_cnn = cnn.predict_classes(x_test_conv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
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       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>50</td>\n",
       "      <td>0</td>\n",
       "      <td>944</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "col_0    0    1    2    3    4    5    6    7    8    9\n",
       "row_0                                                  \n",
       "0      870    0   14   45    8    1   55    0    7    0\n",
       "1        2  977    0   13    3    0    3    0    2    0\n",
       "2       18    0  821    7   66    0   87    0    1    0\n",
       "3       26   13    6  873   40    0   41    0    1    0\n",
       "4        1    1   79   29  779    0  108    0    3    0\n",
       "5        0    0    0    0    0  981    0   15    0    4\n",
       "6      211    0  102   34   95    0  539    0   19    0\n",
       "7        0    0    0    0    0   32    0  948    0   20\n",
       "8        2    0    8    5    4    3    3    2  973    0\n",
       "9        1    0    0    0    0    5    0   50    0  944"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.crosstab(y_test, predict_classes_cnn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "proba_cnn = cnn.predict_proba(x_test_conv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "i = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
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",
      "text/plain": [
       "<VegaLite 2 object>\n",
       "\n",
       "If you see this message, it means the renderer has not been properly enabled\n",
       "for the frontend that you are using. For more information, see\n",
       "https://altair-viz.github.io/user_guide/troubleshooting.html\n"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vis.imshow(x_test[i], labels[y_test[i]]) | vis.predict(proba_cnn[i], y_test[i], labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "default_view": {},
   "name": "04-Transfer-Learning.ipynb",
   "provenance": [],
   "version": "0.3.2",
   "views": {}
  },
  "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": "3.6.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}