{"cells":[{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import ast\nimport numpy as np\nimport pandas as pd\nimport cv2\nimport matplotlib.pyplot as plt\n%matplotlib inline\n\nctr = pd.read_csv('../input/ranzcr-clip-lung-contours/RANZCR_CLiP_lung_contours.csv')\ntrain = pd.read_csv('../input/ranzcr-clip-catheter-line-classification/train.csv')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def plot_xray(StudyInstanceUID):\n    img = cv2.imread('../input/ranzcr-clip-catheter-line-classification/train/'+StudyInstanceUID+'.jpg',-1)\n    ctr_left = ast.literal_eval(ctr.loc[ctr.StudyInstanceUID==StudyInstanceUID,'left_lung_contour'].values[0])\n    ctr_right = ast.literal_eval(ctr.loc[ctr.StudyInstanceUID==StudyInstanceUID,'right_lung_contour'].values[0])\n    img = cv2.drawContours(img, np.array([[np.array(x) for x in ctr_left]]), 0, (255), 5)\n    img = cv2.drawContours(img, np.array([[np.array(x) for x in ctr_right]]), 0, (255), 5)\n    plt.figure(figsize=(8,8))\n    plt.imshow(img,'gray')","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"for i in range(10):\n    plot_xray(ctr.StudyInstanceUID[i])","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}