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@ecjang
Created March 23, 2018 04:48
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03. Images
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 이미지 분류"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"<img width=\"50%\" align=\"left\" src=\"https://github.com/pinkmaguro/machine-learning-with-keras/raw/3e546d8b86f4b4279824d35ad22ecd554b1d734f/img/cifar-10_labels.png\">"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"from keras import datasets\n",
"from keras.utils import np_utils"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"(train_X, train_Y), (test_X, test_Y) = datasets.cifar10.load_data()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"type: <class 'numpy.ndarray'>, len: 50000, \n",
"type: <class 'numpy.ndarray'>, len: 10000, \n"
]
}
],
"source": [
"# train_X, Y : 5만개의 ndarray\n",
"print(\"type: {}, len: {}, \".format(type(train_X), len(train_X)) )\n",
"# test_X, Y : 1만개의 ndarray\n",
"print(\"type: {}, len: {}, \".format(type(test_X), len(test_X)) )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 이미지 확인"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"import matplotlib.pyplot as plt"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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P7XKXjK8yS/xWKMrxosLi25V0JRyhxzA6Pibq7Ng1TspzLG6n0nIsfdnL7ibl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\nYbvzS1LPk2S6Spdei8dBFfJcZPN0Od6stirH6USMrmdmQW7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PUmiZZDkW6EMciqm1JTFH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\nQgghJEP40EUIIYQQQgghGfL/ATL0sFoUeNSlAAAAAElFTkSuQmCC\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x15abb978>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# train_X 이미지 확인\n",
"fig = plt.figure()\n",
"plt.subplots_adjust(left=0.1, right=2, top=1.3, bottom=0.1)\n",
"for i in range(9):\n",
" i += 1\n",
" num = '25' + str(i)\n",
" num = int(num)\n",
" ax = fig.add_subplot(num)\n",
" plt.title(\"train_X[{}] / train_Y[{}]: {}\".format(i, i, train_Y[i]) )\n",
" plt.imshow(train_X[i])\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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8vqfWMkJIP67NuQtDPL5WRBKeii8hSk4kS/KY2VZLfCxNpTz37yQ/95xIQJIO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\nQlLm/wMl0gAlbsDmNwAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x17ea20f0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# test_X 이미지 확인\n",
"fig = plt.figure()\n",
"plt.subplots_adjust(left=0.1, right=2, top=1.3, bottom=0.1)\n",
"for i in range(9):\n",
" i += 1\n",
" num = '25' + str(i)\n",
" num = int(num)\n",
" ax = fig.add_subplot(num)\n",
" plt.title(\"test_X[{}] / test_Y[{}]: {}\".format(i, i, test_Y[i]) )\n",
" plt.imshow(test_X[i])\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(50000, 32, 32, 3)\n",
"(50000, 1)\n",
"(10000, 32, 32, 3)\n",
"(10000, 1)\n"
]
}
],
"source": [
"print(train_X.shape) # train_X: 5만개의 32x32x3의 3차원 배열.\n",
"print(train_Y.shape) # train_Y: 5만개의 1차원 배열.\n",
"print(test_X.shape) # test_X: 1만개의 32x32x3의 3차원 배열.\n",
"print(test_Y.shape) # test_Y: 1만개의 1차원 배열."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Shape of X: (50000, 32, 32, 3)\n",
"Shape of Y: (50000, 1)\n",
"X[0] : [[[ 59 62 63]\n",
" [ 43 46 45]\n",
" [ 50 48 43]\n",
" [ 68 54 42]\n",
" [ 98 73 52]\n",
" [119 91 63]\n",
" [139 107 75]\n",
" [145 110 80]\n",
" [149 117 89]\n",
" [149 120 93]\n",
" [131 103 77]\n",
" [125 99 76]\n",
" [142 115 91]\n",
" [144 112 86]\n",
" [137 105 79]\n",
" [129 97 71]\n",
" [137 106 79]\n",
" [134 106 76]\n",
" [124 97 64]\n",
" [139 113 78]\n",
" [139 112 75]\n",
" [133 105 69]\n",
" [136 105 74]\n",
" [139 108 77]\n",
" [152 120 89]\n",
" [163 131 100]\n",
" [168 136 108]\n",
" [159 129 102]\n",
" [158 130 104]\n",
" [158 132 108]\n",
" [152 125 102]\n",
" [148 124 103]]]\n",
"Y[0] : [6]\n"
]
}
],
"source": [
"def show_data(X, Y):\n",
" print('Shape of X: {}'.format(X.shape))\n",
" print('Shape of Y: {}'.format(Y.shape))\n",
" print('X[0] : ', X[0][:1])\n",
" print('Y[0] : ', Y[0])\n",
"show_data(train_X, train_Y)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- 32x32픽셀의 5만개의 이미지 데이터가 있고, RGB 각각의 명암이 0~255사이의 정수로 표현.\n",
"- 타켓 데이터(Y)는 하나의 정수값으로 이미지 종류의 레이블을 저장한 데이터."
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=uint8)"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Y가 몇 개의 분류값을 갖는지 알아봄.\n",
"import numpy as np\n",
"np.unique(train_Y)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 기능 정의"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"def prepare_classification_data(train_data, test_data):\n",
" train_X, train_Y = train_data\n",
" test_X, test_Y = test_data\n",
" \n",
" #Onde-hot Encoding\n",
" train_Y = np_utils.to_categorical(train_Y) # Converts a class vector (integers) to binary class matrix.\n",
" test_Y = np_utils.to_categorical(test_Y)\n",
" \n",
" # Reshaping Input Data\n",
" m, W, H, C = train_X.shape\n",
" train_X = train_X.reshape(-1, W*H*C) # Returns an array containing the same data with a new shape.\n",
" test_X = test_X.reshape(-1, W*H*C)\n",
" \n",
" #Normalization\n",
" from sklearn.preprocessing import StandardScaler\n",
" scaler = StandardScaler().fit(test_X)\n",
" train_X = scaler.transform(train_X)\n",
" test_X = scaler.transform(test_X)\n",
" \n",
" return (train_X, train_Y), (test_X, test_Y)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"train_X Before : [59 62 63] (50000, 32, 32, 3)\n",
"test_X Before : [158 112 49] (10000, 32, 32, 3)\n",
"train_X After : [ 59 62 63 ... 123 92 72] (50000, 3072)\n",
"test_X After : [158 112 49 ... 21 67 110] (10000, 3072)\n",
"StandardScaler : StandardScaler(copy=True, with_mean=True, with_std=True)\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\ProgramData\\Anaconda3\\envs\\py35\\lib\\site-packages\\sklearn\\utils\\validation.py:444: DataConversionWarning: Data with input dtype uint8 was converted to float64 by StandardScaler.\n",
" warnings.warn(msg, DataConversionWarning)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"fit : StandardScaler(copy=True, with_mean=True, with_std=True)\n",
"train_X before transform : [ 59 62 63 ... 123 92 72] (50000, 3072)\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\ProgramData\\Anaconda3\\envs\\py35\\lib\\site-packages\\sklearn\\utils\\validation.py:444: DataConversionWarning: Data with input dtype uint8 was converted to float64 by StandardScaler.\n",
" warnings.warn(msg, DataConversionWarning)\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"train_X after transform : [-0.97553309 -1.01870231 -0.87145718 ... -0.05492909 -0.5482677\n",
" -0.6598775 ] (50000, 3072)\n",
"min max : -1.9773609525655402 2.2897929419383085\n",
"test_X before transform : [158 112 49 ... 21 67 110] (10000, 3072)\n",
"test_X after transform : [ 0.37453661 -0.3308194 -1.04617293 ... -1.63392961 -0.95137489\n",
" -0.08113244] (10000, 3072)\n",
"min max : -1.772813576129294 2.4967032865169516\n"
]
}
],
"source": [
"# 디버깅\n",
"train_data, test_data = datasets.cifar10.load_data()\n",
"\n",
"#Onde-hot Encoding\n",
"train_Y = np_utils.to_categorical(train_Y) # Converts a class vector (integers) to binary class matrix.\n",
"test_Y = np_utils.to_categorical(test_Y)\n",
"\n",
"# Reshaping Input Data\n",
"m, W, H, C = train_X.shape\n",
"print('train_X Before : ', train_X[0][0][0], train_X.shape)\n",
"print('test_X Before : ', test_X[0][0][0], test_X.shape)\n",
"train_X = train_X.reshape(-1, W*H*C) # Returns an array containing the same data with a new shape.\n",
"test_X = test_X.reshape(-1, W*H*C)\n",
"print('train_X After : ', train_X[0], train_X.shape)\n",
"print('test_X After : ', test_X[0], test_X.shape)\n",
"\n",
"#Normalization\n",
"from sklearn.preprocessing import StandardScaler\n",
"scaler = StandardScaler() # Standardize features by removing the mean and scaling to unit variance\n",
"print('StandardScaler : ', scaler)\n",
"\n",
"scaler = scaler.fit(test_X) # Compute the mean and std to be used for later scaling.\n",
"print('fit : ', scaler)\n",
"\n",
"print('train_X before transform : ', train_X[0], train_X.shape)\n",
"train_X = scaler.transform(train_X) # Perform standardization by centering and scaling\n",
"print('train_X after transform : ', train_X[0], train_X.shape)\n",
"print('min max : ', min(train_X[0]), max(train_X[0]))\n",
"\n",
"print('test_X before transform : ', test_X[0], test_X.shape)\n",
"test_X = scaler.transform(test_X)\n",
"print('test_X after transform : ', test_X[0], test_X.shape)\n",
"print('min max : ', min(test_X[0]), max(test_X[0]))"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<class 'tuple'> [59 62 63]\n",
"<class 'tuple'> [158 112 49]\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"C:\\ProgramData\\Anaconda3\\envs\\py35\\lib\\site-packages\\sklearn\\utils\\validation.py:444: DataConversionWarning: Data with input dtype uint8 was converted to float64 by StandardScaler.\n",
" warnings.warn(msg, DataConversionWarning)\n"
]
}
],
"source": [
"train_data, test_data = datasets.cifar10.load_data()\n",
"print(type(train_data), train_data[0][0][0][0])\n",
"print(type(test_data), test_data[0][0][0][0])\n",
"\n",
"(train_X, train_Y), (test_X, test_Y) = prepare_classification_data(train_data, test_data)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(array([-0.97553309, -1.01870231, -0.87145718, ..., -0.05492909,\n",
" -0.5482677 , -0.6598775 ]),\n",
" array([0., 0., 0., 0., 0., 0., 1., 0., 0., 0.]))"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# 처음 임포트 할 때는 ndarray인데 여기서는 arrary로 변함.\n",
"train_X[0], train_Y[0]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 신경망 클래스 만들기"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"from keras.models import Sequential\n",
"from keras.layers import Dense"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"class DNN(Sequential):\n",
" def __init__(self, input_size, output_size, *num_hidden_nodes):\n",
" super().__init__()\n",
" num_nodes = (*num_hidden_nodes, output_size)\n",
" \n",
" for idx, num_node in enumerate(num_nodes):\n",
" activation = 'relu'\n",
" if idx == 0:\n",
" self.add(Dense(num_node, activation=activation, input_shape=(input_size,)))\n",
" else:\n",
" if idx == len(num_nodes) - 1:\n",
" activation = 'softmax'\n",
" self.add(Dense(output_size, activation=activation))\n",
" \n",
" self.compile(loss = 'categorical_crossentropy', \n",
" optimizer = 'adam',\n",
" metrics = ['accuracy'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 신경망 훈련"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Train on 40000 samples, validate on 10000 samples\n",
"Epoch 1/10\n",
"40000/40000 [==============================] - 16s 404us/step - loss: 2.1015 - acc: 0.3792 - val_loss: 1.8382 - val_acc: 0.4132\n",
"Epoch 2/10\n",
"40000/40000 [==============================] - 14s 359us/step - loss: 1.5489 - acc: 0.4804 - val_loss: 1.6899 - val_acc: 0.4454\n",
"Epoch 3/10\n",
"40000/40000 [==============================] - 15s 383us/step - loss: 1.3810 - acc: 0.5235 - val_loss: 1.5373 - val_acc: 0.4696\n",
"Epoch 4/10\n",
"40000/40000 [==============================] - 23s 566us/step - loss: 1.3062 - acc: 0.5492 - val_loss: 1.5559 - val_acc: 0.4795\n",
"Epoch 5/10\n",
"40000/40000 [==============================] - 16s 392us/step - loss: 1.2476 - acc: 0.5690 - val_loss: 1.5347 - val_acc: 0.4840\n",
"Epoch 6/10\n",
"40000/40000 [==============================] - 15s 387us/step - loss: 1.1939 - acc: 0.5888 - val_loss: 1.5080 - val_acc: 0.4994\n",
"Epoch 7/10\n",
"40000/40000 [==============================] - 18s 448us/step - loss: 1.1550 - acc: 0.5994 - val_loss: 1.5536 - val_acc: 0.4935\n",
"Epoch 8/10\n",
"40000/40000 [==============================] - 20s 511us/step - loss: 1.1119 - acc: 0.6146 - val_loss: 1.5278 - val_acc: 0.4973\n",
"Epoch 9/10\n",
"40000/40000 [==============================] - 15s 380us/step - loss: 1.0672 - acc: 0.6309 - val_loss: 1.5822 - val_acc: 0.4966\n",
"Epoch 10/10\n",
"40000/40000 [==============================] - 15s 381us/step - loss: 1.0263 - acc: 0.6473 - val_loss: 1.5809 - val_acc: 0.5070\n"
]
}
],
"source": [
"model2 = DNN(train_X.shape[1], train_Y.shape[1], 256)\n",
"hitory2 = model2.fit(train_X, train_Y, epochs=10, batch_size=100, validation_split=0.2)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- 테스트 결과 정확도가 0.49가 나옴. 히든 레이어를 추가."
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Train on 40000 samples, validate on 10000 samples\n",
"Epoch 1/10\n",
"40000/40000 [==============================] - 31s 774us/step - loss: 2.2857 - acc: 0.3752 - val_loss: 1.9426 - val_acc: 0.3994\n",
"Epoch 2/10\n",
"40000/40000 [==============================] - 31s 782us/step - loss: 1.5475 - acc: 0.4843 - val_loss: 1.5674 - val_acc: 0.4678\n",
"Epoch 3/10\n",
"40000/40000 [==============================] - 30s 742us/step - loss: 1.3727 - acc: 0.5298 - val_loss: 1.6166 - val_acc: 0.4723\n",
"Epoch 4/10\n",
"40000/40000 [==============================] - 29s 729us/step - loss: 1.3032 - acc: 0.5504 - val_loss: 1.5278 - val_acc: 0.4892\n",
"Epoch 5/10\n",
"40000/40000 [==============================] - 26s 653us/step - loss: 1.2506 - acc: 0.5729 - val_loss: 1.6195 - val_acc: 0.4734\n",
"Epoch 6/10\n",
"40000/40000 [==============================] - 27s 673us/step - loss: 1.2073 - acc: 0.5855 - val_loss: 1.5827 - val_acc: 0.4916\n",
"Epoch 7/10\n",
"40000/40000 [==============================] - 25s 614us/step - loss: 1.1678 - acc: 0.6019 - val_loss: 1.7362 - val_acc: 0.4694\n",
"Epoch 8/10\n",
"40000/40000 [==============================] - 24s 601us/step - loss: 1.1369 - acc: 0.6138 - val_loss: 1.6481 - val_acc: 0.4894\n",
"Epoch 9/10\n",
"40000/40000 [==============================] - 25s 613us/step - loss: 1.0718 - acc: 0.6313 - val_loss: 1.6618 - val_acc: 0.5026\n",
"Epoch 10/10\n",
"40000/40000 [==============================] - 26s 653us/step - loss: 1.0251 - acc: 0.6521 - val_loss: 1.7195 - val_acc: 0.4921\n"
]
}
],
"source": [
"model = DNN(train_X.shape[1], train_Y.shape[1], 512)\n",
"history = model.fit(train_X, train_Y, epochs=10, batch_size=100, validation_split=0.2)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10000/10000 [==============================] - 3s 262us/step\n"
]
},
{
"data": {
"text/plain": [
"[1.7366566375732422, 0.4874]"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Computes the loss on some input data, batch by batch.\n",
"model.evaluate(test_X, test_Y)"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10000/10000 [==============================] - 2s 234us/step\n"
]
}
],
"source": [
"# Generate class predictions for the input samples.\n",
"predicted_Y = model.predict_classes(test_X) "
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [],
"source": [
"# Returns the indices of the maximum values along an axis.\n",
"target_Y = np.argmax(test_Y, axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([ True, True, False, False, False, True, True, True, True,\n",
" True])"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"match = predicted_Y == target_Y\n",
"match[:10]"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.4874"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# get Mean : model.evaluate(test_X, test_Y)의 결과값 0.4874와 유사하다는 걸 알 수 있다.\n",
"sum(match) / len(match)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [],
"source": [
"wrong_label = np.where(match==False)"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"ename": "ValueError",
"evalue": "cannot reshape array of size 15747072 into shape (32,32,3)",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-27-03a505356572>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mshow\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mtest_X\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mwrong_label\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m32\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m32\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;31mValueError\u001b[0m: cannot reshape array of size 15747072 into shape (32,32,3)"
]
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"plt.show(test_X[wrong_label[0]].reshape(32, 32, 3))"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3072"
]
},
"execution_count": 29,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(test_X[1])"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([[1.42459082, 1.36137256, 1.27505056],\n",
" [1.39523197, 1.33108784, 1.24736035],\n",
" [1.39524328, 1.33092908, 1.24754579],\n",
" [1.3919652 , 1.32773802, 1.24357264],\n",
" [1.38906802, 1.32505174, 1.2418087 ],\n",
" [1.38275937, 1.31857344, 1.23759365],\n",
" [1.37842177, 1.31655606, 1.23560444],\n",
" [1.36875849, 1.30971712, 1.23025463],\n",
" [1.36312671, 1.30590832, 1.22727466],\n",
" [1.35619457, 1.29946908, 1.22227862],\n",
" [1.36351431, 1.30818199, 1.23107345],\n",
" [1.35833969, 1.30512483, 1.22989358],\n",
" [1.35864695, 1.30641856, 1.23166239],\n",
" [1.36180537, 1.30984913, 1.23426878],\n",
" [1.36007 , 1.30831252, 1.23219871],\n",
" [1.36026142, 1.2946724 , 1.23248467],\n",
" [1.3594431 , 1.27918208, 1.23033379],\n",
" [1.34353149, 1.27751965, 1.22925864],\n",
" [1.33043844, 1.30678935, 1.22939011],\n",
" [1.32129821, 1.31156571, 1.22034856],\n",
" [1.35314984, 1.29940436, 1.2475983 ],\n",
" [1.36182545, 1.29078344, 1.25235357],\n",
" [1.36472333, 1.30559855, 1.22762339],\n",
" [1.3815988 , 1.32289405, 1.20464369],\n",
" [1.37418907, 1.32694267, 1.21948192],\n",
" [1.39729295, 1.33224328, 1.24590816],\n",
" [1.39248234, 1.32578982, 1.23872667],\n",
" [1.39797876, 1.33031136, 1.24310867],\n",
" [1.40130789, 1.33375678, 1.24588834],\n",
" [1.4223361 , 1.35381973, 1.26270249],\n",
" [1.43065394, 1.36047729, 1.26883491],\n",
" [1.40939802, 1.33946755, 1.25063227]])"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# 1차원으로 정렬된 벼열을 다시 32x32x3 3차원 배열로 바꿈.\n",
"test_X[1].reshape(32,32,3)[0]"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(32, 32)"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test_X[1].reshape(32,32,3).sum(axis=2).shape"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"# 원래의 test 인덱스를 받아오기 위해 새로 변수를 생성.\n",
"(train_X, train_Y), (test_origin_X, test2_origin_Y) = datasets.cifar10.load_data()"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([8])"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"test2_origin_Y[2]"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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f+emzx0+pvpPRBeqfcoedc18533UxjLNhfmr0AuanRi9ARK8AsOCc+975rothnA3z0/PH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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x19eabc88>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# test_X 이미지 확인 : train으로 훈련된 모델을 사용하여 test 이미지를 확인.\n",
"fig = plt.figure()\n",
"plt.subplots_adjust(left=0.1, right=2, top=1.3, bottom=0.1)\n",
"for i in range(9):\n",
" i += 1\n",
" num = int('25' + str(i))\n",
" ax = fig.add_subplot(num) # Add a subplot\n",
" plt.title(\"test_X[{}] / test_Y[{}]: {}\".format(i, i, test2_origin_Y[i]) )\n",
" plt.imshow(test_X[i].reshape(32,32,3).sum(axis=2))\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"8\n",
"[0. 0. 0. 0. 0. 0. 0. 0. 1. 0.]\n"
]
}
],
"source": [
"print(predicted_Y[1]) # 첫번째 이미지의 예측값\n",
"print(test_Y[1]) # 첫번째 이미지의 정답과 일치."
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {},
"outputs": [],
"source": [
"from collections import defaultdict"
]
},
{
"cell_type": "code",
"execution_count": 100,
"metadata": {},
"outputs": [],
"source": [
"# 라벨에 따라 분류\n",
"def classify_by_label(target_Y, predicted_Y):\n",
" n_classes = len(np.unique(target_Y)) # tartget_Y의 유니크한 값들, 즉 인덱스 번호만 추출.\n",
" index_for_classes = [defaultdict(list) for _ in range(n_classes)]\n",
" for idx, (target_y, predicted_y) in enumerate(zip(target_Y, predicted_Y)):\n",
" if target_y == predicted_y:\n",
" key = 'correct'\n",
" else:\n",
" key = 'wrong'\n",
" index_for_classes[target_y][key].append(idx)\n",
" return index_for_classes"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1. n_classes: 10\n",
" 2. type: index_for_classes : <class 'list'>\n",
" 3. value: index_for_classes : [defaultdict(<class 'list'>, {}), defaultdict(<class 'list'>, {}), defaultdict(<class 'list'>, {})]\n",
" 4. value: target_Y : [3 8 8 ... 5 1 7] 10000\n",
" 5. value: predicted_Y : [3 8 8 ... 5 1 7] 10000\n",
" 6. ket_count : {'wrong': 5126, 'correct': 4874}\n"
]
}
],
"source": [
"# 디버깅\n",
"n_classes = len(np.unique(target_Y)) # tartget_Y의 유니크한 값들, 즉 인덱스 번호만 추출하고 길이를 계산.\n",
"print(\"1. n_classes: \", n_classes)\n",
"\n",
"# defaultdict(default_factory[, ...]) --> dict with default factory\n",
"# 여기건 10개의 빈 리스트를 생성.\n",
"index_for_classes = [defaultdict(list) for _ in range(n_classes)]\n",
"print(\" 2. type: index_for_classes : \", type(index_for_classes) )\n",
"print(\" 3. value: index_for_classes : \", index_for_classes[:3] )\n",
"\n",
"# target_Y, predicted_Y 둘다 인덱스 번호를 나타냄.\n",
"print(\" 4. value: target_Y : \", target_Y, len(target_Y) )\n",
"print(\" 5. value: predicted_Y : \", target_Y, len(predicted_Y) )\n",
"\n",
"ket_count = {'correct':0 , 'wrong':0 } # 일치, 불일치 카운트 용 \n",
"\n",
"for idx, (target_y, predicted_y) in enumerate(zip(target_Y, predicted_Y)):\n",
" if target_y == predicted_y:\n",
" key = 'correct'\n",
" ket_count['correct'] += 1\n",
" else:\n",
" key = 'wrong'\n",
" ket_count['wrong'] += 1\n",
" \n",
" index_for_classes[target_y][key].append(idx)\n",
"\n",
"print(' 6. ket_count : ', ket_count)"
]
},
{
"cell_type": "code",
"execution_count": 101,
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
"index_for_classes = classify_by_label(target_Y, predicted_Y)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 훈련 결과 출력"
]
},
{
"cell_type": "code",
"execution_count": 106,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 : [10, 27, 44, 74, 90, 97, 111, 116, 125, 169]\n",
"1 : [6, 9, 81, 82, 104, 122, 131, 134, 204, 231]\n",
"2 : [67, 75, 84, 113, 135, 138, 156, 160, 183, 248]\n",
"3 : [0, 8, 68, 77, 103, 143, 187, 205, 245, 251]\n",
"4 : [26, 32, 36, 94, 100, 110, 159, 223, 365, 370]\n",
"5 : [24, 141, 155, 178, 181, 200, 230, 250, 262, 321]\n",
"6 : [5, 7, 29, 30, 41, 43, 49, 62, 64, 71]\n",
"7 : [13, 48, 56, 99, 109, 177, 194, 208, 216, 220]\n",
"8 : [1, 18, 54, 55, 72, 73, 79, 80, 88, 92]\n",
"9 : [11, 23, 28, 34, 38, 45, 50, 76, 89, 133]\n"
]
}
],
"source": [
"# 인덱스 번호별로 맞은 것들만 10개씩 출력.\n",
"for i in range(10):\n",
" print(i,': ',index_for_classes[i]['correct'][:10])"
]
},
{
"cell_type": "code",
"execution_count": 162,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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ZPWSbLLCgGg7kyJRWrisZEbwqbFJEofrYlsjzyZLcXVFXiraWOOhCS5ROE5FU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\n+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ltFTgKNAS7DeIWFTd507T+S7ZXFF5Dt2GcPJT6nfQEAMMQKOyHLIkG1Ic5brpK0eQJe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\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1a2ea4a8>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# 맞은 것들을 출력.\n",
"fig = plt.figure()\n",
"plt.subplots_adjust(left=0.1, right=2.2, top=1.5, bottom=0.1)\n",
"i = 0\n",
"for image_idx in index_for_classes[3]['correct'][:9]:\n",
" i += 1\n",
" num = int('25' + str(i))\n",
" ax = fig.add_subplot(num) # Add a subplot\n",
" plt.title(\"test_X[{}] / test_Y[{}]: {}\".format(image_idx, image_idx, test2_origin_Y[image_idx]))\n",
" plt.imshow(test_X[image_idx].reshape(32,32,3).sum(axis=2))\n",
"\n",
"plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### 틀린 것들 출력"
]
},
{
"cell_type": "code",
"execution_count": 149,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0 : [3, 21, 52, 98, 153, 154, 192, 206, 215, 237]\n",
"1 : [37, 66, 105, 114, 161, 193, 201, 241, 246, 261]\n",
"2 : [25, 35, 65, 70, 86, 118, 123, 129, 147, 149]\n",
"3 : [46, 53, 61, 63, 78, 91, 106, 115, 121, 127]\n",
"4 : [22, 40, 58, 117, 130, 165, 167, 188, 211, 227]\n",
"5 : [12, 16, 31, 33, 39, 42, 85, 101, 128, 148]\n",
"6 : [4, 19, 59, 95, 112, 140, 142, 152, 221, 226]\n",
"7 : [17, 20, 57, 60, 69, 83, 87, 119, 137, 145]\n",
"8 : [2, 15, 51, 124, 126, 132, 144, 150, 164, 191]\n",
"9 : [14, 47, 139, 151, 157, 171, 172, 209, 213, 247]\n"
]
}
],
"source": [
"# 인덱스 번호별로 틀린 것들만 10개씩 출력.\n",
"for i in range(10):\n",
" print(i,': ',index_for_classes[i]['wrong'][:10])"
]
},
{
"cell_type": "code",
"execution_count": 161,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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/N84oVnMhuxfxj6YfjWwxROS1InKbiNzWCNK+a2EYpx3L9vexsbV9Zcow1pGO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\nfBLHSTF02wAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x2d2cd320>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# 틀린 것들을 출력.\n",
"fig = plt.figure()\n",
"plt.subplots_adjust(left=0.1, right=2.2, top=1.5, bottom=0.1)\n",
"i = 0\n",
"for image_idx in index_for_classes[3]['wrong'][:9]:\n",
" i += 1\n",
" num = int('25' + str(i))\n",
" ax = fig.add_subplot(num) # Add a subplot\n",
" plt.title(\"{} / predicted: {} / label: {}\".format(\n",
" image_idx, \n",
" predicted_Y[image_idx],\n",
" test2_origin_Y[image_idx]\n",
" ))\n",
" plt.imshow(test_X[image_idx].reshape(32,32,3).sum(axis=2))\n",
"\n",
"plt.show()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "python3.5",
"language": "python",
"name": "python3.5"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.5.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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