{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2021-07-26T16:54:56.975799Z","iopub.execute_input":"2021-07-26T16:54:56.976519Z","iopub.status.idle":"2021-07-26T16:54:56.992163Z","shell.execute_reply.started":"2021-07-26T16:54:56.976393Z","shell.execute_reply":"2021-07-26T16:54:56.990824Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"from keras import layers\nfrom keras import models\nimport matplotlib.pyplot as plt\nfrom keras import optimizers\nfrom keras.preprocessing.image import ImageDataGenerator","metadata":{"execution":{"iopub.status.busy":"2021-07-26T16:54:59.576692Z","iopub.execute_input":"2021-07-26T16:54:59.577204Z","iopub.status.idle":"2021-07-26T16:55:05.988081Z","shell.execute_reply.started":"2021-07-26T16:54:59.577161Z","shell.execute_reply":"2021-07-26T16:55:05.986981Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import os\nprint(os.listdir('../input'))","metadata":{"execution":{"iopub.status.busy":"2021-07-26T16:58:07.96297Z","iopub.execute_input":"2021-07-26T16:58:07.96334Z","iopub.status.idle":"2021-07-26T16:58:07.968623Z","shell.execute_reply.started":"2021-07-26T16:58:07.96331Z","shell.execute_reply":"2021-07-26T16:58:07.967525Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_dir            = '../input/train'\nvalidation_dir               = '../input/test'","metadata":{"execution":{"iopub.status.busy":"2021-07-26T16:59:11.978777Z","iopub.execute_input":"2021-07-26T16:59:11.979139Z","iopub.status.idle":"2021-07-26T16:59:11.983759Z","shell.execute_reply.started":"2021-07-26T16:59:11.979112Z","shell.execute_reply":"2021-07-26T16:59:11.982413Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"model = models.Sequential()\nmodel.add(layers.Conv2D(32, (3, 3), activation='relu', input_shape=(150, 150, 3)))\nmodel.add(layers.MaxPool2D((2, 2)))\n\nmodel.add(layers.Conv2D(64, (3, 3), activation='relu'))\nmodel.add(layers.MaxPool2D((2, 2)))\n\nmodel.add(layers.Conv2D(128, (3, 3), activation='relu'))\nmodel.add(layers.MaxPool2D((2, 2)))\n\nmodel.add(layers.Conv2D(128, (3, 3), activation='relu'))\nmodel.add(layers.MaxPool2D((2, 2)))\n\nmodel.add(layers.Flatten())\nmodel.add(layers.Dropout(0.5))\nmodel.add(layers.Dense(512, activation='relu'))\nmodel.add(layers.Dense(1, activation='sigmoid'))\n\nmodel.compile(loss='binary_crossentropy', optimizer=optimizers.RMSprop(lr=1e-4), metrics=['acc'])\n","metadata":{"execution":{"iopub.status.busy":"2021-07-26T17:11:30.992867Z","iopub.execute_input":"2021-07-26T17:11:30.993347Z","iopub.status.idle":"2021-07-26T17:11:31.234703Z","shell.execute_reply.started":"2021-07-26T17:11:30.993317Z","shell.execute_reply":"2021-07-26T17:11:31.233802Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_datagen = ImageDataGenerator(rescale=1./255,)\ntest_datagen = ImageDataGenerator(rescale=1./255)","metadata":{"execution":{"iopub.status.busy":"2021-07-26T17:11:38.471642Z","iopub.execute_input":"2021-07-26T17:11:38.471983Z","iopub.status.idle":"2021-07-26T17:11:38.477465Z","shell.execute_reply.started":"2021-07-26T17:11:38.471954Z","shell.execute_reply":"2021-07-26T17:11:38.47601Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_generator = train_datagen.flow(\n    train_dir,\n    batch_size=50)\n\nvalidation_generator = test_datagen.flow(\n    validation_dir,\n    batch_size=50)","metadata":{"execution":{"iopub.status.busy":"2021-07-26T17:12:58.480317Z","iopub.execute_input":"2021-07-26T17:12:58.48089Z","iopub.status.idle":"2021-07-26T17:12:58.520707Z","shell.execute_reply.started":"2021-07-26T17:12:58.480854Z","shell.execute_reply":"2021-07-26T17:12:58.518769Z"},"trusted":true},"execution_count":null,"outputs":[]}]}