{"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":"import cv2\nimport numpy as np\nimport pandas as pd\n\nimport matplotlib.pyplot as plt\n\nimport os\nimport random\nimport gc","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"import zipfile\nwith zipfile.ZipFile(\"../input/dogs-vs-cats-redux-kernels-edition/\"+\"train.zip\",\"r\") as z:\n    z.extractall(\".\")","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"with zipfile.ZipFile(\"../input/dogs-vs-cats-redux-kernels-edition/\"+\"test.zip\",\"r\") as z:\n    z.extractall(\".\")","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"train_dir = '../input/dogs-vs-cats-redux-kernels-edition/train'\ntest_dir = '../input/dogs-vs-cats-redux-kernels-edition/test'\n\ntrain_dogs = ['../input/dogs-vs-cats-redux-kernels-edition/train/{}'.format(i) for i in os.listdir(train_dir) if 'dog' in i]  #get dog images\ntrain_cats = ['../input/dogs-vs-cats-redux-kernels-edition/train/{}'.format(i) for i in os.listdir(train_dir) if 'cat' in i]  #get cat images\n\ntest_imgs = ['../input/dogs-vs-cats-redux-kernels-edition/test/{}'.format(i) for i in os.listdir(test_dir)] #get test images\n\ntrain_imgs = train_dogs[:2000] + train_cats[:2000]  # slice the dataset and use 2000 in each class\nrandom.shuffle(train_imgs)  # shuffle it randomly\n\n#Clear list that are useless\ndel train_dogs\ndel train_cats\ngc.collect()   #collect garbage to save memory","metadata":{"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"trusted":true},"execution_count":null,"outputs":[]}]}