8-2.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VsZV03UD5Qb5"
      },
      "source": [
        "# 합성곱 신경망을 사용한 이미지 분류"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MiG7uEQF5QcA"
      },
      "source": [
        "<table align=\"left\">\n",
        "  <td>\n",
        "    <a target=\"_blank\" href=\"https://colab.research.google.com/github/rickiepark/hg-mldl/blob/master/8-2.ipynb\"><img src=\"https://www.tensorflow.org/images/colab_logo_32px.png\" />구글 코랩에서 실행하기</a>\n",
        "  </td>\n",
        "</table>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "pS9ZuQWfCeHe"
      },
      "outputs": [],
      "source": [
        "# 실행마다 동일한 결과를 얻기 위해 케라스에 랜덤 시드를 사용하고 텐서플로 연산을 결정적으로 만듭니다.\n",
        "import tensorflow as tf\n",
        "\n",
        "tf.keras.utils.set_random_seed(42)\n",
        "tf.config.experimental.enable_op_determinism()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fQSb0wK85QcA"
      },
      "source": [
        "## 패션 MNIST 데이터 불러오기"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "BGJBttQs5QcA",
        "outputId": "da0921b4-d6bc-4adb-8160-957589a84dba",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-labels-idx1-ubyte.gz\n",
            "29515/29515 [==============================] - 0s 0us/step\n",
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/train-images-idx3-ubyte.gz\n",
            "26421880/26421880 [==============================] - 0s 0us/step\n",
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-labels-idx1-ubyte.gz\n",
            "5148/5148 [==============================] - 0s 0us/step\n",
            "Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/t10k-images-idx3-ubyte.gz\n",
            "4422102/4422102 [==============================] - 0s 0us/step\n"
          ]
        }
      ],
      "source": [
        "from tensorflow import keras\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "(train_input, train_target), (test_input, test_target) = \\\n",
        "    keras.datasets.fashion_mnist.load_data()\n",
        "\n",
        "train_scaled = train_input.reshape(-1, 28, 28, 1) / 255.0\n",
        "\n",
        "train_scaled, val_scaled, train_target, val_target = train_test_split(\n",
        "    train_scaled, train_target, test_size=0.2, random_state=42)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Y4m7l2115QcB"
      },
      "source": [
        "## 합성곱 신경망 만들기"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "wubmkM6q5QcB"
      },
      "outputs": [],
      "source": [
        "model = keras.Sequential()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "fcuXinil5QcB"
      },
      "outputs": [],
      "source": [
        "model.add(keras.layers.Conv2D(32, kernel_size=3, activation='relu',\n",
        "                              padding='same', input_shape=(28,28,1)))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "ddZAIUwJ5QcB"
      },
      "outputs": [],
      "source": [
        "model.add(keras.layers.MaxPooling2D(2))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "6NbO08605QcC"
      },
      "outputs": [],
      "source": [
        "model.add(keras.layers.Conv2D(64, kernel_size=(3,3), activation='relu',\n",
        "                              padding='same'))\n",
        "model.add(keras.layers.MaxPooling2D(2))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "sxlx0yyS5QcC"
      },
      "outputs": [],
      "source": [
        "model.add(keras.layers.Flatten())\n",
        "model.add(keras.layers.Dense(100, activation='relu'))\n",
        "model.add(keras.layers.Dropout(0.4))\n",
        "model.add(keras.layers.Dense(10, activation='softmax'))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1CFKlE-B5QcC",
        "outputId": "ef8fc701-45e2-4e80-b3c5-300f4e393fd4"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d (Conv2D)             (None, 28, 28, 32)        320       \n",
            "                                                                 \n",
            " max_pooling2d (MaxPooling2  (None, 14, 14, 32)        0         \n",
            " D)                                                              \n",
            "                                                                 \n",
            " conv2d_1 (Conv2D)           (None, 14, 14, 64)        18496     \n",
            "                                                                 \n",
            " max_pooling2d_1 (MaxPoolin  (None, 7, 7, 64)          0         \n",
            " g2D)                                                            \n",
            "                                                                 \n",
            " flatten (Flatten)           (None, 3136)              0         \n",
            "                                                                 \n",
            " dense (Dense)               (None, 100)               313700    \n",
            "                                                                 \n",
            " dropout (Dropout)           (None, 100)               0         \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 10)                1010      \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 333526 (1.27 MB)\n",
            "Trainable params: 333526 (1.27 MB)\n",
            "Non-trainable params: 0 (0.00 Byte)\n",
            "_________________________________________________________________\n"
          ]
        }
      ],
      "source": [
        "model.summary()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 856
        },
        "id": "uO2xZfrF5QcD",
        "outputId": "f286500f-3aee-4147-a0ed-ad4c354a4493"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "keras.utils.plot_model(model)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 976
        },
        "id": "FQTWlPbY5QcD",
        "outputId": "5b0ac8e3-bfb7-4230-fb98-b7b0acedcb73"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "keras.utils.plot_model(model, show_shapes=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7sO3by845QcE"
      },
      "source": [
        "## 모델 컴파일과 훈련"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Msys0HQp5QcE",
        "outputId": "f3d9dd4d-f62a-43e6-d72e-6dbf8a7f2cb9"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/20\n",
            "1500/1500 [==============================] - 25s 5ms/step - loss: 0.5091 - accuracy: 0.8178 - val_loss: 0.3178 - val_accuracy: 0.8823\n",
            "Epoch 2/20\n",
            "  26/1500 [..............................] - ETA: 6s - loss: 0.3565 - accuracy: 0.8702"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py:3079: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n",
            "  saving_api.save_model(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1500/1500 [==============================] - 8s 6ms/step - loss: 0.3382 - accuracy: 0.8775 - val_loss: 0.2747 - val_accuracy: 0.8964\n",
            "Epoch 3/20\n",
            "1500/1500 [==============================] - 8s 5ms/step - loss: 0.2927 - accuracy: 0.8945 - val_loss: 0.2451 - val_accuracy: 0.9101\n",
            "Epoch 4/20\n",
            "1500/1500 [==============================] - 8s 5ms/step - loss: 0.2583 - accuracy: 0.9064 - val_loss: 0.2343 - val_accuracy: 0.9131\n",
            "Epoch 5/20\n",
            "1500/1500 [==============================] - 7s 5ms/step - loss: 0.2358 - accuracy: 0.9134 - val_loss: 0.2234 - val_accuracy: 0.9160\n",
            "Epoch 6/20\n",
            "1500/1500 [==============================] - 8s 5ms/step - loss: 0.2151 - accuracy: 0.9211 - val_loss: 0.2149 - val_accuracy: 0.9220\n",
            "Epoch 7/20\n",
            "1500/1500 [==============================] - 9s 6ms/step - loss: 0.1982 - accuracy: 0.9268 - val_loss: 0.2145 - val_accuracy: 0.9202\n",
            "Epoch 8/20\n",
            "1500/1500 [==============================] - 7s 4ms/step - loss: 0.1810 - accuracy: 0.9336 - val_loss: 0.2196 - val_accuracy: 0.9222\n",
            "Epoch 9/20\n",
            "1500/1500 [==============================] - 9s 6ms/step - loss: 0.1693 - accuracy: 0.9366 - val_loss: 0.2149 - val_accuracy: 0.9233\n"
          ]
        }
      ],
      "source": [
        "model.compile(optimizer='adam', loss='sparse_categorical_crossentropy',\n",
        "              metrics='accuracy')\n",
        "\n",
        "checkpoint_cb = keras.callbacks.ModelCheckpoint('best-cnn-model.h5',\n",
        "                                                save_best_only=True)\n",
        "early_stopping_cb = keras.callbacks.EarlyStopping(patience=2,\n",
        "                                                  restore_best_weights=True)\n",
        "\n",
        "history = model.fit(train_scaled, train_target, epochs=20,\n",
        "                    validation_data=(val_scaled, val_target),\n",
        "                    callbacks=[checkpoint_cb, early_stopping_cb])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "Q9ZA46lb5QcE"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "1JaC-KDn5QcF",
        "outputId": "5f00b69b-ff82-4471-cfc8-5168fa1ddad1"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.plot(history.history['loss'])\n",
        "plt.plot(history.history['val_loss'])\n",
        "plt.xlabel('epoch')\n",
        "plt.ylabel('loss')\n",
        "plt.legend(['train', 'val'])\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "W3pWBHLK5QcF",
        "outputId": "5b7bf7c8-30d9-4f54-8e0c-cfe6341e3657"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "375/375 [==============================] - 1s 3ms/step - loss: 0.2145 - accuracy: 0.9202\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.21453545987606049, 0.9201666712760925]"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "model.evaluate(val_scaled, val_target)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "a9wUbDQL5QcG",
        "outputId": "3fe07796-1468-4e77-9111-b3cac2692c64"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAaAAAAGdCAYAAABU0qcqAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAAAhOElEQVR4nO3de3BU5f3H8c/mtgkh2RhCbhIwXBQrl45U0hRFLCkQZywIrdc/wDpQbXCK1Oqko6L2NxPFjqXaFKYzCnUqoM4IVNqhoyBhbAMOKKVUmwEmFSgkaGqyuZAL2fP7gyHtaoA8D7v7JOH9mtkZsnu+Od+cPNkPJ3v2G5/neZ4AAIixONcNAAAuTwQQAMAJAggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACcSXDfwZaFQSCdOnFBaWpp8Pp/rdgAAhjzPU3Nzs/Lz8xUXd/7znH4XQCdOnFBBQYHrNgAAl+jYsWMaMWLEeR/vdwGUlpYm6Wzj6enpjrsBAJgKBoMqKCjoeT4/n6gFUGVlpZ5//nnV1dVp8uTJeumllzR16tSL1p37tVt6ejoBBAAD2MVeRonKRQivv/66li9frhUrVujDDz/U5MmTNXv2bJ06dSoauwMADEBRCaAXXnhBixcv1n333aevfe1rWrNmjYYMGaJXXnklGrsDAAxAEQ+gzs5O7du3TyUlJf/dSVycSkpKVF1d/ZXtOzo6FAwGw24AgMEv4gH0+eefq7u7Wzk5OWH35+TkqK6u7ivbV1RUKBAI9Ny4Ag4ALg/O34haXl6upqamntuxY8dctwQAiIGIXwWXlZWl+Ph41dfXh91fX1+v3Nzcr2zv9/vl9/sj3QYAoJ+L+BlQUlKSpkyZou3bt/fcFwqFtH37dhUXF0d6dwCAASoq7wNavny5Fi5cqG984xuaOnWqVq1apdbWVt13333R2B0AYACKSgDdeeed+uyzz/Tkk0+qrq5OX//617Vt27avXJgAALh8+TzP81w38b+CwaACgYCampqYhAAAA1Bfn8edXwUHALg8EUAAACcIIACAEwQQAMAJAggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACcIIACAEwQQAMCJqEzDBs4nFArFpCYhIXZL+6GHHjKuyc7ONq4ZNmyYcU1HR4dxjSTdcccdxjVXXnmlcY3NLGSfz2dcg/6JMyAAgBMEEADACQIIAOAEAQQAcIIAAgA4QQABAJwggAAAThBAAAAnCCAAgBMEEADACQIIAOAEAQQAcIIAAgA4wTTsGLGZ+mujv08KtjkONpOt//3vfxvXSNL3vvc945rnn3/euObGG280rrHR2NhoVffrX//auMbm2I0fP964xmY6uu3PRX//eRroOAMCADhBAAEAnCCAAABOEEAAACcIIACAEwQQAMAJAggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACd8XqymZPZRMBhUIBBQU1OT0tPTXbcz4Nh8O22XQFyc+f9fbAZJ2uxn/vz5xjWS9PjjjxvXXH/99Vb7Gmwee+wx45rnnnsuCp1EzmAcImzzNZn219fncc6AAABOEEAAACcIIACAEwQQAMAJAggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACcIIACAEwQQAMCJBNcNILJiOdTQhs1g0e7ubuOawsJC4xpp8A0WbWtrs6obMmSIcc3YsWONa/7+978b10ycONG45syZM8Y1kpSQEJunyFjOhO5PzxGcAQEAnCCAAABORDyAnnrqKfl8vrDb+PHjI70bAMAAF5VfcF533XV69913/7uTGP0eFQAwcEQlGRISEpSbmxuNTw0AGCSi8hrQoUOHlJ+fr9GjR+vee+/V0aNHz7ttR0eHgsFg2A0AMPhFPICKioq0bt06bdu2TatXr1Ztba1uuukmNTc397p9RUWFAoFAz62goCDSLQEA+qGIB1Bpaam+//3va9KkSZo9e7b+9Kc/qbGxUW+88Uav25eXl6upqannduzYsUi3BADoh6J+dUBGRoauvvpqHT58uNfH/X6//H5/tNsAAPQzUX8fUEtLi44cOaK8vLxo7woAMIBEPIAeeeQRVVVV6V//+pf++te/6vbbb1d8fLzuvvvuSO8KADCARfxXcMePH9fdd9+thoYGDR8+XDfeeKN2796t4cOHR3pXAIABLOIBtHHjxkh/ysuWzYBCm0GDtsMJbQY82rwp+cSJE8Y1tsMnYyUUCsVkP7F8fbW4uNi4prq62rjGZhipzUBbKXZvorf5GYzlANNoYRYcAMAJAggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACcIIACAEwQQAMAJAggA4AQBBABwggACADgRm0l7sGI7JDRW4uJi8/+XrVu3GtckJSVFoZPIidWxi+XAynHjxhnX/OpXvzKuWbx4sXHNYPyjl/39+aEvOAMCADhBAAEAnCCAAABOEEAAACcIIACAEwQQAMAJAggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACcIIACAE5f1NGzbScGhUCgmNYmJicY1Nl+T7XGI1UTnLVu2GNdMmzYtCp30rru727jG5tjZfJ9s1p0kJSSYPzXYTJxOTU01rmlvbzeuSU5ONq4ZrGKxXvu6VjkDAgA4QQABAJwggAAAThBAAAAnCCAAgBMEEADACQIIAOAEAQQAcIIAAgA4QQABAJwggAAAThBAAAAnBs0wUptBjT6fz2pf8fHxMamxYfM12R6HWPnb3/5mXPOLX/wiCp30rj9/b2M1MNaWzWDR48ePG9eMHTvWuGawisV67eta7d+rEwAwaBFAAAAnCCAAgBMEEADACQIIAOAEAQQAcIIAAgA4QQABAJwggAAAThBAAAAnCCAAgBMEEADAiUEzjDSWAzVffvnlmOzniiuuMK4JhULGNbbHLicnx7imsbHRuCY3N9e4pq6uzrhGkvx+f8z2Zcrme2s7jNRmTSQlJRnXfPrpp8Y1W7duNa751re+ZVwj2Q3C7ejoMK7JyMgwrsnMzDSukaSjR48a14wbN85o+9bW1j5txxkQAMAJAggA4IRxAO3atUu33Xab8vPz5fP5tHnz5rDHPc/Tk08+qby8PKWkpKikpESHDh2KVL8AgEHCOIBaW1s1efJkVVZW9vr4ypUr9eKLL2rNmjXas2ePUlNTNXv2bKs/PAUAGLyML0IoLS1VaWlpr495nqdVq1bp8ccf19y5cyVJr776qnJycrR582bdddddl9YtAGDQiOhrQLW1taqrq1NJSUnPfYFAQEVFRaquru61pqOjQ8FgMOwGABj8IhpA5y5H/fLluTk5Oee9VLWiokKBQKDnVlBQEMmWAAD9lPOr4MrLy9XU1NRzO3bsmOuWAAAxENEAOveGwfr6+rD76+vrz/tmQr/fr/T09LAbAGDwi2gAFRYWKjc3V9u3b++5LxgMas+ePSouLo7krgAAA5zxVXAtLS06fPhwz8e1tbXav3+/MjMzNXLkSC1btkz/93//p3HjxqmwsFBPPPGE8vPzNW/evEj2DQAY4IwDaO/evbrlllt6Pl6+fLkkaeHChVq3bp0effRRtba2asmSJWpsbNSNN96obdu2KTk5OXJdAwAGPJ/neZ7rJv5XMBhUIBBQQ0OD0etBCQnmc1Xb2tqMayTpjjvuMK6xGVBoE9rx8fHGNf/5z3+MayQpNTXVuCY7Ozsm+7HV0NBgXGPzve3s7DSuieUw0pSUFOMam0GzNuvB5me9q6vLuEay+9mwGeRqM4x06NChxjWS1N3dbVzzwx/+0Gj71tZWfec731FTU9MFn8edXwUHALg8EUAAACcIIACAEwQQAMAJAggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACcIIACAEwQQAMAJAggA4IT5WNkYSUhIsJp6a8L2T0T84Ac/MK75/e9/b1xjO+3W1LXXXmtV19TUZFxjMzk6LS3NuMZ2yLvNdGabKdVnzpwxrrGZYmx7HGymaLe3txvX2KyHQCBgXNPS0mJcI0l5eXnGNXV1dcY1Nj/rts8PNj+3pn9QNBgM9mk7zoAAAE4QQAAAJwggAIATBBAAwAkCCADgBAEEAHCCAAIAOEEAAQCcIIAAAE4QQAAAJwggAIATBBAAwIl+O4zU1CeffGJc88wzz1jta82aNcY15eXlxjVTp041runs7DSusRlOKNkNxxwyZIhxTVJSknHNqVOnjGsk6fTp08Y1KSkpxjU2g3bj4+ONa2wGhEp231ubtWczyHX48OHGNfX19cY1kt33trW11bjGZo3bDLSV7PqLFs6AAABOEEAAACcIIACAEwQQAMAJAggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACcIIACAEwQQAMCJQTOMdNGiRcY1H3zwgdW+NmzYYFzT1dVlXBMXZ/7/A5uhhh0dHcY1kt1AzYaGBuOaxsZG4xqbgZWS5HmeVZ2pxMRE4xqb9WA7sNKmzmawaHNzs3HNP/7xD+Oa9PR04xopdj+3NuvOZjitJKWmplrVRQNnQAAAJwggAIATBBAAwAkCCADgBAEEAHCCAAIAOEEAAQCcIIAAAE4QQAAAJwggAIATBBAAwAkCCADgxKAZRmozsLKioiLyjZxHd3d3TGpshpHaitUAxfb2duOaWA7htOmvpaXFuMZm2Kctm33ZDKdNTk42ronlsbNZ452dncY1p0+fNq6xXeM2xzxaOAMCADhBAAEAnDAOoF27dum2225Tfn6+fD6fNm/eHPb4okWL5PP5wm5z5syJVL8AgEHCOIBaW1s1efJkVVZWnnebOXPm6OTJkz03mz/gBgAY3IxfNSwtLVVpaekFt/H7/crNzbVuCgAw+EXlNaCdO3cqOztb11xzjR588MEL/hnmjo4OBYPBsBsAYPCLeADNmTNHr776qrZv367nnntOVVVVKi0tPe8lxRUVFQoEAj23goKCSLcEAOiHIv4+oLvuuqvn3xMnTtSkSZM0ZswY7dy5UzNnzvzK9uXl5Vq+fHnPx8FgkBACgMtA1C/DHj16tLKysnT48OFeH/f7/UpPTw+7AQAGv6gH0PHjx9XQ0KC8vLxo7woAMIAY/wqupaUl7GymtrZW+/fvV2ZmpjIzM/X0009rwYIFys3N1ZEjR/Too49q7Nixmj17dkQbBwAMbMYBtHfvXt1yyy09H597/WbhwoVavXq1Dhw4oN/97ndqbGxUfn6+Zs2apZ///Ofy+/2R6xoAMOAZB9CMGTMuOKDvz3/+8yU1dM6+ffs0dOjQPm//xRdfGO9j2bJlxjW2bIYatra2GtfYvIZm05tkN0DRZmBlamqqcY3t5fxxcbGZTmUzlNXn80Whk97ZDLq0GcJpU2Pzn1mbtSpJKSkpxjWJiYnGNTaDh20FAoGY7etimAUHAHCCAAIAOEEAAQCcIIAAAE4QQAAAJwggAIATBBAAwAkCCADgBAEEAHCCAAIAOEEAAQCcIIAAAE4QQAAAJyL+J7kj5f3331dycnKft29ubjbeh8nnv1Q2E2jb29uNa2ymOdtOWbaZ4GvTn820btup1jb7itUkY5spy11dXVb7spmGbbOOYvU12a6HUChkVWfKZip4W1ub1b6uvvpqq7po4AwIAOAEAQQAcIIAAgA4QQABAJwggAAAThBAAAAnCCAAgBMEEADACQIIAOAEAQQAcIIAAgA4QQABAJzot8NIjx8/rqSkpD5vX1paGsVuLt2QIUOMa2wGFNpISIjdMojVcEfb/dgOZjVlM1DTZj3Yfj22wztNxWrQrO16sOnPRnx8vHFNY2Oj1b5Gjx5tVRcNnAEBAJwggAAAThBAAAAnCCAAgBMEEADACQIIAOAEAQQAcIIAAgA4QQABAJwggAAAThBAAAAnCCAAgBP9dhhpd3e3uru7+7x9RkZG9JqJAJthpDaDEE0GuJ5z+vRp4xopdoM7bY6D7fDJ/jyEM1aDXG0Nxq/pzJkzxjU2P4Pt7e3GNTYDbSXpqquusqqLBs6AAABOEEAAACcIIACAEwQQAMAJAggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACcIIACAEwQQAMCJfjuMND09XX6/33UbETNu3Djjmk8++cS4Jjk52bimra3NuEayGyRpM8DUZCjtOTaDMSW7rylWx8GmxvY42Ay6tBnkattfrPZjc8wTEsyfVm2OdyAQMK6RpOHDh1vVRQNnQAAAJwggAIATRgFUUVGhG264QWlpacrOzta8efNUU1MTtk17e7vKyso0bNgwDR06VAsWLFB9fX1EmwYADHxGAVRVVaWysjLt3r1b77zzjrq6ujRr1iy1trb2bPPwww/r7bff1ptvvqmqqiqdOHFC8+fPj3jjAICBzejVsm3btoV9vG7dOmVnZ2vfvn2aPn26mpqa9PLLL2v9+vX69re/LUlau3atrr32Wu3evVvf/OY3I9c5AGBAu6TXgJqamiRJmZmZkqR9+/apq6tLJSUlPduMHz9eI0eOVHV1da+fo6OjQ8FgMOwGABj8rAMoFApp2bJlmjZtmiZMmCBJqqurU1JSkjIyMsK2zcnJUV1dXa+fp6KiQoFAoOdWUFBg2xIAYACxDqCysjIdPHhQGzduvKQGysvL1dTU1HM7duzYJX0+AMDAYPVG1KVLl2rr1q3atWuXRowY0XN/bm6uOjs71djYGHYWVF9fr9zc3F4/l9/vH1RvOAUA9I3RGZDneVq6dKk2bdqkHTt2qLCwMOzxKVOmKDExUdu3b++5r6amRkePHlVxcXFkOgYADApGZ0BlZWVav369tmzZorS0tJ7XdQKBgFJSUhQIBHT//fdr+fLlyszMVHp6uh566CEVFxdzBRwAIIxRAK1evVqSNGPGjLD7165dq0WLFkmSfvnLXyouLk4LFixQR0eHZs+erd/85jcRaRYAMHgYBVBfBvolJyersrJSlZWV1k1J0s0336zU1NQ+b19RUXFJ+4u2/32trK/+8Ic/GNd8+T8HfdHe3m5cI9kN4bQZChkfH29cY9ObZNefzRBOGzZDLs+cOROFTnoXq8Gitt9bG7H63tp8TTY/F9LZq5L7C2bBAQCcIIAAAE4QQAAAJwggAIATBBAAwAkCCADgBAEEAHCCAAIAOEEAAQCcIIAAAE4QQAAAJwggAIATBBAAwAmrv4gaC7fccovS09P7vP369euN92EzbVqSvvvd7xrXLF682Ljmt7/9rXFNd3e3cY3P5zOukaTTp0/HZF82U6A7OjqMa2z3lZSUZFwTqynVNutBkhITE41rbL4mm/UQqxrJbo1fccUVxjU263X06NHGNf0NZ0AAACcIIACAEwQQAMAJAggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACcIIACAEwQQAMAJAggA4ES/HUZq6pVXXjGuWbVqldW+qqqqjGt27NhhXGMzSLKlpcW4pr293bhGshtYGR8fb1xjM6gxOTnZuEaSurq6jGs6OzuNawKBgHGNTW+2x8Hma/L7/cY1nufFpMZ2GKnNeg2FQsY1Nt/brKws45r+hjMgAIATBBAAwAkCCADgBAEEAHCCAAIAOEEAAQCcIIAAAE4QQAAAJwggAIATBBAAwAkCCADgBAEEAHBi0AwjtZGTk2NV9+yzzxrX2AwWHTlypHHNwYMHjWtOnTplXCPZDQm1GZZqM9wxKSnJuEaSUlJSjGts1pHNsYvVsE9JSkgwf2qwGdxp05/NerB15syZmNQ0NDQY1xQWFhrX2DL9PvV1e86AAABOEEAAACcIIACAEwQQAMAJAggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACcIIACAEwQQAMCJfjuMNBQKGQ0djIszz9L6+nrjGkkaMWKEcc2YMWOMa2yGO2ZnZxvXDBkyxLhGkhITE41rbAZqNjc3G9c0NTUZ10jSqFGjjGs2bNhgXLNx40bjmkAgYFxjO5TV5/MZ19gMME1NTTWuSU9Pj8l+JLvjYDNY9NZbbzWumTt3rnFNf8MZEADACQIIAOCEUQBVVFTohhtuUFpamrKzszVv3jzV1NSEbTNjxgz5fL6w2wMPPBDRpgEAA59RAFVVVamsrEy7d+/WO++8o66uLs2aNUutra1h2y1evFgnT57sua1cuTKiTQMABj6jVw23bdsW9vG6deuUnZ2tffv2afr06T33DxkyRLm5uZHpEAAwKF3Sa0DnrjTKzMwMu/+1115TVlaWJkyYoPLycrW1tZ33c3R0dCgYDIbdAACDn/Vl2KFQSMuWLdO0adM0YcKEnvvvuecejRo1Svn5+Tpw4IAee+wx1dTU6K233ur181RUVOjpp5+2bQMAMEBZB1BZWZkOHjyo999/P+z+JUuW9Px74sSJysvL08yZM3XkyJFe3wtTXl6u5cuX93wcDAZVUFBg2xYAYICwCqClS5dq69at2rVr10XflFlUVCRJOnz4cK8B5Pf7rd6cCAAY2IwCyPM8PfTQQ9q0aZN27typwsLCi9bs379fkpSXl2fVIABgcDIKoLKyMq1fv15btmxRWlqa6urqJJ0dEZKSkqIjR45o/fr1uvXWWzVs2DAdOHBADz/8sKZPn65JkyZF5QsAAAxMRgG0evVqSWffbPq/1q5dq0WLFikpKUnvvvuuVq1apdbWVhUUFGjBggV6/PHHI9YwAGBwMP4V3IUUFBSoqqrqkhoCAFwefN7FUiXGgsGgAoGAvvjiC6OptzbTsD/77DPjGknavHmzcc3p06eNa1paWoxrTpw4YVzz+eefG9dIUmNjo3GNzXGwuUjFZpK4JH388cfGNX/84x+Na/73rQtALNk85ZtOBT/3PN7U1HTB53GGkQIAnCCAAABOEEAAACcIIACAEwQQAMAJAggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACcIIACAE/12GOnFhtgBAPonhpECAPo1AggA4AQBBABwggACADhBAAEAnCCAAABOEEAAACcIIACAEwQQAMAJAggA4AQBBABwIsF1A192bjRdMBh03AkAwMa55++LjRrtdwHU3NwsSSooKHDcCQDgUjQ3NysQCJz38X43DTsUCunEiRNKS0uTz+cLeywYDKqgoEDHjh27rCdlcxzO4jicxXE4i+NwVn84Dp7nqbm5Wfn5+YqLO/8rPf3uDCguLk4jRoy44Dbp6emX9QI7h+NwFsfhLI7DWRyHs1wfhwud+ZzDRQgAACcIIACAEwMqgPx+v1asWCG/3++6Fac4DmdxHM7iOJzFcThrIB2HfncRAgDg8jCgzoAAAIMHAQQAcIIAAgA4QQABAJwYMAFUWVmpq666SsnJySoqKtIHH3zguqWYe+qpp+Tz+cJu48ePd91W1O3atUu33Xab8vPz5fP5tHnz5rDHPc/Tk08+qby8PKWkpKikpESHDh1y02wUXew4LFq06CvrY86cOW6ajZKKigrdcMMNSktLU3Z2tubNm6eampqwbdrb21VWVqZhw4Zp6NChWrBggerr6x11HB19OQ4zZsz4ynp44IEHHHXcuwERQK+//rqWL1+uFStW6MMPP9TkyZM1e/ZsnTp1ynVrMXfdddfp5MmTPbf333/fdUtR19raqsmTJ6uysrLXx1euXKkXX3xRa9as0Z49e5SamqrZs2ervb09xp1G18WOgyTNmTMnbH1s2LAhhh1GX1VVlcrKyrR7926988476urq0qxZs9Ta2tqzzcMPP6y3335bb775pqqqqnTixAnNnz/fYdeR15fjIEmLFy8OWw8rV6501PF5eAPA1KlTvbKysp6Pu7u7vfz8fK+iosJhV7G3YsUKb/Lkya7bcEqSt2nTpp6PQ6GQl5ub6z3//PM99zU2Nnp+v9/bsGGDgw5j48vHwfM8b+HChd7cuXOd9OPKqVOnPEleVVWV53lnv/eJiYnem2++2bPNJ5984knyqqurXbUZdV8+Dp7neTfffLP34x//2F1TfdDvz4A6Ozu1b98+lZSU9NwXFxenkpISVVdXO+zMjUOHDik/P1+jR4/Wvffeq6NHj7puyana2lrV1dWFrY9AIKCioqLLcn3s3LlT2dnZuuaaa/Tggw+qoaHBdUtR1dTUJEnKzMyUJO3bt09dXV1h62H8+PEaOXLkoF4PXz4O57z22mvKysrShAkTVF5erra2NhftnVe/G0b6ZZ9//rm6u7uVk5MTdn9OTo7++c9/OurKjaKiIq1bt07XXHONTp48qaefflo33XSTDh48qLS0NNftOVFXVydJva6Pc49dLubMmaP58+ersLBQR44c0c9+9jOVlpaqurpa8fHxrtuLuFAopGXLlmnatGmaMGGCpLPrISkpSRkZGWHbDub10NtxkKR77rlHo0aNUn5+vg4cOKDHHntMNTU1euuttxx2G67fBxD+q7S0tOffkyZNUlFRkUaNGqU33nhD999/v8PO0B/cddddPf+eOHGiJk2apDFjxmjnzp2aOXOmw86io6ysTAcPHrwsXge9kPMdhyVLlvT8e+LEicrLy9PMmTN15MgRjRkzJtZt9qrf/wouKytL8fHxX7mKpb6+Xrm5uY666h8yMjJ09dVX6/Dhw65bcebcGmB9fNXo0aOVlZU1KNfH0qVLtXXrVr333nthf74lNzdXnZ2damxsDNt+sK6H8x2H3hQVFUlSv1oP/T6AkpKSNGXKFG3fvr3nvlAopO3bt6u4uNhhZ+61tLToyJEjysvLc92KM4WFhcrNzQ1bH8FgUHv27Lns18fx48fV0NAwqNaH53launSpNm3apB07dqiwsDDs8SlTpigxMTFsPdTU1Ojo0aODaj1c7Dj0Zv/+/ZLUv9aD66sg+mLjxo2e3+/31q1b53388cfekiVLvIyMDK+urs51azH1k5/8xNu5c6dXW1vr/eUvf/FKSkq8rKws79SpU65bi6rm5mbvo48+8j766CNPkvfCCy94H330kffpp596nud5zz77rJeRkeFt2bLFO3DggDd37lyvsLDQO336tOPOI+tCx6G5udl75JFHvOrqaq+2ttZ79913veuvv94bN26c197e7rr1iHnwwQe9QCDg7dy50zt58mTPra2trWebBx54wBs5cqS3Y8cOb+/evV5xcbFXXFzssOvIu9hxOHz4sPfMM894e/fu9Wpra70tW7Z4o0eP9qZPn+6483ADIoA8z/Neeuklb+TIkV5SUpI3depUb/fu3a5birk777zTy8vL85KSkrwrr7zSu/POO73Dhw+7bivq3nvvPU/SV24LFy70PO/spdhPPPGEl5OT4/n9fm/mzJleTU2N26aj4ELHoa2tzZs1a5Y3fPhwLzEx0Rs1apS3ePHiQfeftN6+fkne2rVre7Y5ffq096Mf/ci74oorvCFDhni33367d/LkSXdNR8HFjsPRo0e96dOne5mZmZ7f7/fGjh3r/fSnP/WamprcNv4l/DkGAIAT/f41IADA4EQAAQCcIIAAAE4QQAAAJwggAIATBBAAwAkCCADgBAEEAHCCAAIAOEEAAQCcIIAAAE4QQAAAJ/4fZ6sScRDNdBsAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.imshow(val_scaled[0].reshape(28, 28), cmap='gray_r')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nRe6TDpw5QcG",
        "outputId": "2ec206ef-3b79-420e-f5df-346de91b83e5",
        "scrolled": true
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 115ms/step\n",
            "[[3.3830289e-14 1.6479672e-22 2.1887265e-18 1.7189894e-15 6.0608955e-14\n",
            "  2.9962747e-12 7.4386124e-13 8.6856405e-14 1.0000000e+00 1.9710426e-14]]\n"
          ]
        }
      ],
      "source": [
        "preds = model.predict(val_scaled[0:1])\n",
        "print(preds)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "bOBfv6De5QcG",
        "outputId": "7efd111d-e8cd-4bdd-9c75-06f07f1f19fe"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ],
      "source": [
        "plt.bar(range(1, 11), preds[0])\n",
        "plt.xlabel('class')\n",
        "plt.ylabel('prob.')\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "917fZGHu5QcG"
      },
      "outputs": [],
      "source": [
        "classes = ['티셔츠', '바지', '스웨터', '드레스', '코트',\n",
        "           '샌달', '셔츠', '스니커즈', '가방', '앵클 부츠']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "h1JqgKgk5QcH",
        "outputId": "9fbd4cb4-c340-4095-a398-145273a2b33d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "가방\n"
          ]
        }
      ],
      "source": [
        "import numpy as np\n",
        "print(classes[np.argmax(preds)])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "id": "G2ihSV-l5QcH"
      },
      "outputs": [],
      "source": [
        "test_scaled = test_input.reshape(-1, 28, 28, 1) / 255.0"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1AHKDd2U5QcH",
        "outputId": "7df04851-db94-47d9-cf55-e35f46d3d026"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "313/313 [==============================] - 1s 4ms/step - loss: 0.2394 - accuracy: 0.9141\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.23940542340278625, 0.9140999913215637]"
            ]
          },
          "metadata": {},
          "execution_count": 21
        }
      ],
      "source": [
        "model.evaluate(test_scaled, test_target)"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "8-2.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "default:Python",
      "language": "python",
      "name": "conda-env-default-py"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.9.10"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}