{"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 os, sys\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport cv2\nfrom sklearn.model_selection import train_test_split\n\nimport warnings\nwarnings.filterwarnings(\"ignore\")\nIMG_SIZE = 512\nNUM_CLASSES = 5\nSEED = 77\nTRAIN_NUM = 1000 # use 1000 when you just want to explore new idea, use -1 for full train\n\ndf_train = pd.read_csv('../input/aptos2019-blindness-detection/train.csv')\ndf_test = pd.read_csv('../input/aptos2019-blindness-detection/test.csv')\ntrain_y = df_train['diagnosis']\n","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_kg_hide-output":true,"execution":{"iopub.status.busy":"2021-11-16T04:58:31.094506Z","iopub.execute_input":"2021-11-16T04:58:31.095083Z","iopub.status.idle":"2021-11-16T04:58:32.356941Z","shell.execute_reply.started":"2021-11-16T04:58:31.095046Z","shell.execute_reply":"2021-11-16T04:58:32.355979Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"%%time\nfig = plt.figure(figsize=(25, 16))\n# display 10 images from each class\nfor class_id in sorted(train_y.unique()):\n    for i, (idx, row) in enumerate(df_train.loc[train_y == class_id].sample(5, random_state=SEED).iterrows()):\n        ax = fig.add_subplot(5, 5, class_id * 5 + i + 1, xticks=[], yticks=[])\n        path=f\"../input/train_images/{row['id_code']}.png\"\n        image = cv2.imread(path)\n        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n        image = cv2.resize(image, (IMG_SIZE, IMG_SIZE))\n\n        plt.imshow(image)\n        ax.set_title('Label: %d-%d-%s' % (class_id, idx, row['id_code']) )","metadata":{"execution":{"iopub.status.busy":"2021-11-16T04:58:34.671777Z","iopub.execute_input":"2021-11-16T04:58:34.672302Z","iopub.status.idle":"2021-11-16T04:58:34.794628Z","shell.execute_reply.started":"2021-11-16T04:58:34.672261Z","shell.execute_reply":"2021-11-16T04:58:34.793932Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{"execution":{"iopub.status.busy":"2021-11-16T04:45:18.953687Z","iopub.execute_input":"2021-11-16T04:45:18.954987Z","iopub.status.idle":"2021-11-16T04:45:18.977618Z","shell.execute_reply.started":"2021-11-16T04:45:18.954921Z","shell.execute_reply":"2021-11-16T04:45:18.976687Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}