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BlazerYoo/mnist.ipynb

Created February 18, 2021 15:48
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mnist.ipynb
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "mnist.ipynb",
"provenance": [],
"collapsed_sections": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
}
},
"cells": [
{
"cell_type": "code",
"metadata": {
"id": "bD6rSX4VGWqh"
},
"source": [
"import tensorflow as tf\r\n",
"(x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data()"
],
"execution_count": 3,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 300
},
"id": "pBdccr5LoWu8",
"outputId": "17d2a03f-cc3d-41e8-dae9-a5aa1c476ceb"
},
"source": [
"import matplotlib.pyplot as plt\r\n",
"%matplotlib inline\r\n",
"image_index = 7777\r\n",
"print(y_train[image_index])\r\n",
"plt.imshow(x_train[image_index], cmap='Greys')"
],
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"text": [
"8\n"
],
"name": "stdout"
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<matplotlib.image.AxesImage at 0x7f40683ca518>"
]
},
"metadata": {
"tags": []
},
"execution_count": 4
},
{
"output_type": "display_data",
"data": {
"image/png": 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kJvV2rQbeom+TtDW79DT7tUv01ZDXjY/LAkFwgg4IgrADQRB2IAjCDgRB2IEgCDsQBGEHgvh/9T5QU2WpHjQAAAAASUVORK5CYII=\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "x6y5jmRNotD9",
"outputId": "85f9f1c4-4f6e-4bae-9e26-43f7ebc98f61"
},
"source": [
"x_train.shape"
],
"execution_count": 5,
"outputs": [
{
"output_type": "execute_result",
"data": {
"text/plain": [
"(60000, 28, 28)"
]
},
"metadata": {
"tags": []
},
"execution_count": 5
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "nOBbG1ORouWU",
"outputId": "0c5d4556-3362-44a7-9eaa-9c02ff18f53e"
},
"source": [
"x_train = x_train.reshape(x_train.shape[0], 28, 28, 1)\r\n",
"x_test = x_test.reshape(x_test.shape[0], 28, 28, 1)\r\n",
"input_shape = (28, 28, 1)\r\n",
"x_train = x_train.astype('float32')\r\n",
"x_test = x_test.astype('float32')\r\n",
"x_train /= 255\r\n",
"x_test /= 255\r\n",
"print('x_train shape:', x_train.shape)\r\n",
"print('Number of images in x_train', x_train.shape[0])\r\n",
"print('Number of images in x_test', x_test.shape[0])"
],
"execution_count": 6,
"outputs": [
{
"output_type": "stream",
"text": [
"x_train shape: (60000, 28, 28, 1)\n",
"Number of images in x_train 60000\n",
"Number of images in x_test 10000\n"
],
"name": "stdout"
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "Ru9wxXQBovp9"
},
"source": [
"from tensorflow.keras.models import Sequential\r\n",
"from tensorflow.keras.layers import Dense, Conv2D, Dropout, Flatten, MaxPooling2D\r\n",
"model = Sequential()\r\n",
"model.add(Conv2D(28, kernel_size=(3,3), input_shape=input_shape))\r\n",
"model.add(MaxPooling2D(pool_size=(2, 2)))\r\n",
"model.add(Flatten())\r\n",
"model.add(Dropout(0.2))\r\n",
"model.add(Dense(10,activation=tf.nn.softmax))"
],
"execution_count": 7,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "4_bTxwG4oxtT",
"outputId": "3c971ff8-7765-49b3-8ab2-96e2607221ef"
},
"source": [
"model.compile(optimizer='adam', \r\n",
" loss='sparse_categorical_crossentropy', \r\n",
" metrics=['accuracy'])\r\n",
"model.fit(x=x_train,y=y_train, epochs=10)"
],
"execution_count": 8,
"outputs": [
{
"output_type": "stream",
"text": [
"Epoch 1/10\n",
"1875/1875 [==============================] - 30s 16ms/step - loss: 0.3693 - accuracy: 0.8886\n",
"Epoch 2/10\n",
"1875/1875 [==============================] - 29s 15ms/step - loss: 0.0858 - accuracy: 0.9742\n",
"Epoch 3/10\n",
"1875/1875 [==============================] - 29s 15ms/step - loss: 0.0570 - accuracy: 0.9825\n",
"Epoch 4/10\n",
"1875/1875 [==============================] - 29s 16ms/step - loss: 0.0436 - accuracy: 0.9864\n",
"Epoch 5/10\n",
"1875/1875 [==============================] - 29s 15ms/step - loss: 0.0322 - accuracy: 0.9901\n",
"Epoch 6/10\n",
"1875/1875 [==============================] - 30s 16ms/step - loss: 0.0276 - accuracy: 0.9910\n",
"Epoch 7/10\n",
"1875/1875 [==============================] - 30s 16ms/step - loss: 0.0234 - accuracy: 0.9921\n",
"Epoch 8/10\n",
"1875/1875 [==============================] - 29s 16ms/step - loss: 0.0195 - accuracy: 0.9933\n",
"Epoch 9/10\n",
"1875/1875 [==============================] - 29s 16ms/step - loss: 0.0175 - accuracy: 0.9943\n",
"Epoch 10/10\n",
"1875/1875 [==============================] - 29s 16ms/step - loss: 0.0161 - accuracy: 0.9943\n"
],
"name": "stdout"
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"<tensorflow.python.keras.callbacks.History at 0x7f406907df60>"
]
},
"metadata": {
"tags": []
},
"execution_count": 8
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "mgys-1dwozIf",
"outputId": "c59aa2d4-baf0-408b-9028-fd527fabb77c"
},
"source": [
"model.evaluate(x_test, y_test)"
],
"execution_count": 9,
"outputs": [
{
"output_type": "stream",
"text": [
"313/313 [==============================] - 2s 6ms/step - loss: 0.0595 - accuracy: 0.9848\n"
],
"name": "stdout"
},
{
"output_type": "execute_result",
"data": {
"text/plain": [
"[0.059479277580976486, 0.9847999811172485]"
]
},
"metadata": {
"tags": []
},
"execution_count": 9
}
]
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 282
},
"id": "XCPmt9g-o1SB",
"outputId": "893d585d-c8b7-4cdb-e964-aeb27cf428be"
},
"source": [
"image_index = 4444\r\n",
"plt.imshow(x_test[image_index].reshape(28, 28),cmap='Greys')\r\n",
"pred = model.predict(x_test[image_index].reshape(1, 28, 28, 1))\r\n",
"print(pred.argmax())"
],
"execution_count": 10,
"outputs": [
{
"output_type": "stream",
"text": [
"9\n"
],
"name": "stdout"
},
{
"output_type": "display_data",
"data": {
"image/png": "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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"tags": [],
"needs_background": "light"
}
}
]
},
{
"cell_type": "code",
"metadata": {
"id": "PRQ_BS5XpGD1"
},
"source": [
"model.save('model.h5')"
],
"execution_count": 11,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "-UGh1oo-qcNB",
"outputId": "37e38d39-bdbe-48f3-c195-47b209586657"
},
"source": [
"!pip install tensorflowjs\r\n",
"!tensorflowjs_converter --input_format keras '/content/model.h5' '/content/model'"
],
"execution_count": 16,
"outputs": [
{
"output_type": "stream",
"text": [
"Requirement already satisfied: tensorflowjs in /usr/local/lib/python3.6/dist-packages (3.1.0)\n",
"Requirement already satisfied: six<2,>=1.12.0 in /usr/local/lib/python3.6/dist-packages (from tensorflowjs) (1.15.0)\n",
"Requirement already satisfied: tensorflow<3,>=2.1.0 in /usr/local/lib/python3.6/dist-packages (from tensorflowjs) (2.4.1)\n",
"Requirement already satisfied: tensorflow-hub<0.10,>=0.7.0 in /usr/local/lib/python3.6/dist-packages (from tensorflowjs) (0.9.0)\n",
"Requirement already satisfied: h5py<3,>=2.8.0 in /usr/local/lib/python3.6/dist-packages (from tensorflowjs) (2.10.0)\n",
"Requirement already satisfied: keras-preprocessing~=1.1.2 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.1.2)\n",
"Requirement already satisfied: gast==0.3.3 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (0.3.3)\n",
"Requirement already satisfied: opt-einsum~=3.3.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (3.3.0)\n",
"Requirement already satisfied: tensorflow-estimator<2.5.0,>=2.4.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (2.4.0)\n",
"Requirement already satisfied: wheel~=0.35 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (0.36.2)\n",
"Requirement already satisfied: grpcio~=1.32.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.32.0)\n",
"Requirement already satisfied: flatbuffers~=1.12.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.12)\n",
"Requirement already satisfied: astunparse~=1.6.3 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.6.3)\n",
"Requirement already satisfied: absl-py~=0.10 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (0.10.0)\n",
"Requirement already satisfied: typing-extensions~=3.7.4 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (3.7.4.3)\n",
"Requirement already satisfied: termcolor~=1.1.0 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.1.0)\n",
"Requirement already satisfied: numpy~=1.19.2 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.19.5)\n",
"Requirement already satisfied: wrapt~=1.12.1 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (1.12.1)\n",
"Requirement already satisfied: tensorboard~=2.4 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (2.4.1)\n",
"Requirement already satisfied: protobuf>=3.9.2 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (3.12.4)\n",
"Requirement already satisfied: google-pasta~=0.2 in /usr/local/lib/python3.6/dist-packages (from tensorflow<3,>=2.1.0->tensorflowjs) (0.2.0)\n",
"Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.6/dist-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (1.0.1)\n",
"Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in /usr/local/lib/python3.6/dist-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (1.8.0)\n",
"Requirement already satisfied: google-auth<2,>=1.6.3 in /usr/local/lib/python3.6/dist-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (1.25.0)\n",
"Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.6/dist-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (3.3.3)\n",
"Requirement already satisfied: requests<3,>=2.21.0 in /usr/local/lib/python3.6/dist-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (2.23.0)\n",
"Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /usr/local/lib/python3.6/dist-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (0.4.2)\n",
"Requirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.6/dist-packages (from tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (53.0.0)\n",
"Requirement already satisfied: cachetools<5.0,>=2.0.0 in /usr/local/lib/python3.6/dist-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (4.2.1)\n",
"Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.6/dist-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (0.2.8)\n",
"Requirement already satisfied: rsa<5,>=3.1.4; python_version >= \"3.6\" in /usr/local/lib/python3.6/dist-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (4.7)\n",
"Requirement already satisfied: importlib-metadata; python_version < \"3.8\" in /usr/local/lib/python3.6/dist-packages (from markdown>=2.6.8->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (3.4.0)\n",
"Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (3.0.4)\n",
"Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (1.24.3)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (2020.12.5)\n",
"Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests<3,>=2.21.0->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (2.10)\n",
"Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.6/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (1.3.0)\n",
"Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.6/dist-packages (from pyasn1-modules>=0.2.1->google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (0.4.8)\n",
"Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.6/dist-packages (from importlib-metadata; python_version < \"3.8\"->markdown>=2.6.8->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (3.4.0)\n",
"Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.6/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard~=2.4->tensorflow<3,>=2.1.0->tensorflowjs) (3.1.0)\n",
"2021-02-18 15:06:43.971844: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.10.1\n"
],
"name": "stdout"
}
]
}
]
}
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