{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"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 in \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 \"../input/\" directory.\n# For example, running this (by clicking run or pressing Shift+Enter) will list the files in the input directory\n\nimport os\nprint(os.listdir(\"../input\"))\n\n# Any results you write to the current directory are saved as output.","execution_count":null,"outputs":[]},{"metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","trusted":true},"cell_type":"code","source":"pd.read_csv(\"../input/sample_submission.csv\").head()\n","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"images = os.listdir(\"../input/test\")\nimages[:100]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import matplotlib.pyplot as plt\nimport matplotlib.image as mpimg\nimport cv2\n\n\n#read the first jpg file\nimg = cv2.imread('../input/test/b4c3b52a8723d431.jpg',0)\n#img = cv2.imread('../input/test/b4c3b52a8723d431.jpg')\n\n#check the array of the first jpg file\nimg","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"#view the array as an image\nplt.imshow(img)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"x= '../input/test/'\nmyList = [ x + i for i in images[:100]]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"for i in myList:\n    plt.imshow( cv2.imread(i) ) \n    plt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"image_filenames = os.listdir(\"../input/test/\")\n\nimport random\nfor i in range(10):\n    index = random.randrange(len(image_filenames))\n    path = \"../input/test/\" + \"/\" + image_filenames[index]\n    src_img = cv2.imread(path)\n    fig=plt.figure(figsize=(18, 16), dpi= 80, facecolor='w', edgecolor='k')\n    plt.imshow(cv2.cvtColor(src_img, cv2.COLOR_BGR2RGB))\n    plt.show()","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"},"language_info":{"name":"python","version":"3.6.4","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":1}