{"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\n# import os\n# for 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":"import cv2","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"!ls /kaggle/input/save-cut-mix-image-box/wheat_cutmix","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import matplotlib.pyplot as plt\n\nimg = cv2.imread('/kaggle/input/save-cut-mix-image-box/wheat_cutmix/image_100_1.jpg')\nboxes = np.load('/kaggle/input/save-cut-mix-image-box/wheat_cutmix/box_100_1.npy')\nfig, ax = plt.subplots(1, figsize=(8, 8))\nfor box in boxes:\n        cv2.rectangle(img,\n                  (int(box[1]), int(box[2])),\n                  (int(box[3]), int(box[4])),\n                  220, 3)\n\nax.imshow(img)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"img = cv2.imread('/kaggle/input/save-cut-mix-image-box/wheat_cutmix/image_100_2.jpg')\nboxes = np.load('/kaggle/input/save-cut-mix-image-box/wheat_cutmix/box_100_2.npy')\nfig, ax = plt.subplots(1, figsize=(8, 8))\nfor box in boxes:\n        cv2.rectangle(img,\n                  (int(box[1]), int(box[2])),\n                  (int(box[3]), int(box[4])),\n                  220, 3)\n\nax.imshow(img)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"img = cv2.imread('/kaggle/input/save-cut-mix-image-box/wheat_cutmix/image_100_3.jpg')\nboxes = np.load('/kaggle/input/save-cut-mix-image-box/wheat_cutmix/box_100_3.npy')\nfig, ax = plt.subplots(1, figsize=(8, 8))\nfor box in boxes:\n        cv2.rectangle(img,\n                  (int(box[1]), int(box[2])),\n                  (int(box[3]), int(box[4])),\n                  220, 3)\n\nax.imshow(img)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"img = cv2.imread('/kaggle/input/save-cut-mix-image-box/wheat_cutmix/image_100_5.jpg')\nboxes = np.load('/kaggle/input/save-cut-mix-image-box/wheat_cutmix/box_100_5.npy')\nfig, ax = plt.subplots(1, figsize=(8, 8))\nfor box in boxes:\n        cv2.rectangle(img,\n                  (int(box[1]), int(box[2])),\n                  (int(box[3]), int(box[4])),\n                  220, 3)\n\nax.imshow(img)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"img = cv2.imread('/kaggle/input/save-cut-mix-image-box/wheat_cutmix/image_100_6.jpg')\nboxes = np.load('/kaggle/input/save-cut-mix-image-box/wheat_cutmix/box_100_6.npy')\nfig, ax = plt.subplots(1, figsize=(8, 8))\nfor box in boxes:\n        cv2.rectangle(img,\n                  (int(box[1]), int(box[2])),\n                  (int(box[3]), int(box[4])),\n                  220, 3)\n\nax.imshow(img)\nplt.show()","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}