{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\nimport seaborn as sns\n%matplotlib inline\n\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import confusion_matrix\nimport itertools\n\nfrom keras.utils.np_utils import to_categorical # convert to one-hot-encoding\nfrom keras.models import Sequential\nfrom keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPool2D\nfrom keras.optimizers import RMSprop\nfrom keras.preprocessing.image import ImageDataGenerator\nfrom keras.callbacks import ReduceLROnPlateau","execution_count":null,"outputs":[]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"# Display 10 images\nDATA_DIR = \"../input/train/train\"\nfor file_name in os.listdir(DATA_DIR)[0:10]:\n    img_array = cv2.imread(os.path.join(DATA_DIR, file_name))\n    plt.imshow(img_array)\n    plt.show()\n    print(file_name.split('.')[0])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"ae2111b8d05f353c08c9f25f6ea41a3a6a7d108d"},"cell_type":"code","source":"#create data\nDATA_DIR = \"../input/train/train\"\nIMG_SIZE = 28\ndef create_data():\n    x = []\n    y = []\n    for file_name in os.listdir(DATA_DIR):\n        img_array = cv2.imread(os.path.join(DATA_DIR, file_name))\n        new_array = cv2.resize(img_array, (IMG_SIZE, IMG_SIZE))\n        x.append(new_array)\n        if file_name.split('.')[0] == 'cat':\n            y.append(0)\n        else:\n            y.append(1)\n    return x, y","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"42938b65a47822079787fab2489a73f1e24c1606"},"cell_type":"code","source":"import random\nx, y = create_data()\nx = np.array(x)\ny = np.array(y)\nprint(x.shape)\nprint(y.shape)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"fec9ba014de76ee9a4b6137f8f3107c1df0de664"},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true,"_uuid":"4ae36614d69e363c7fe79676dbdf1d275b963de3"},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.6","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}