{"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\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 5GB 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","execution_count":null,"outputs":[]},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"data = pd.read_csv('../input/global-wheat-detection/train.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"bbox = data['bbox']","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"col0 = []\ncol1 = []\ncol2 = []\ncol3 = []\n\nfor i in range(len(bbox)):\n    res_bb = bbox[i].strip('][').split(', ')\n    for j in range(len(res_bb)):\n        res_bb[j] = float(res_bb[j])\n        \n        if j == 0:\n            col0.append(res_bb[j])\n        elif j == 1:\n            col1.append(res_bb[j])\n        elif j == 2:\n            col2.append(res_bb[j])\n        elif j == 3:\n            col3.append(res_bb[j])\n        else:\n            print(\"Hoooo\")","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"print(col0[0],col3[0], col1[0], col2[0])","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"from sklearn.preprocessing import LabelEncoder\nlb = LabelEncoder()\ndata['source'] = lb.fit_transform(data['source'])\nsource = data['source']\nset(source)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data.drop([\"bbox\", 'source'], axis=1, inplace=True)\ndata['class'] = source\ndata['xmin'] = col0\ndata['ymin'] = col1\ndata['xmax'] = col2\ndata['ymax'] = col3","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data = data.rename(columns={'image_id':'filename'})","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"data.to_csv(\"./finaldata.csv\", index=None)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"d = pd.read_csv('./finaldata.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"d.head()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"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":4,"nbformat_minor":4}