{"cells":[{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"import numpy as np\nimport pandas as pd\nimport os\nfrom fastai.vision import *\nfrom fastai.metrics import error_rate\nfrom pathlib import Path\nfrom PIL  import ImageFile\n\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\nfrom fastai import *\nfrom fastai.vision import *\nfrom fastai.vision.gan import *\nfrom fastai.vision.all import *\nimport torch\nfrom pathlib import Path\nimport pickle","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"Path('/kaggle/working/resnet50').mkdir(exist_ok=True, parents=True)\n!cp ../input/weights2/resnet50.pkl /kaggle/working/resnet50/resnet50.pkl\n\n\npkl_file = open(r\"/kaggle/working/resnet50/resnet50.pkl\", \"rb\")\nmodel = pickle.load(pkl_file)\n\n\ntest_image_path = \"../input/cassava-leaf-disease-classification/test_images/\"\ntest_images = os.listdir(test_image_path)\n\n\npreds = []\nfor image_name in test_images:\n    prediction=model.predict(test_image_path  + image_name)\n    preds.append(prediction[0])  \n    \nsub = pd.DataFrame({\"image_id\": test_images, \"label\": preds})\nsub.to_csv(\"submission.csv\", index=False)  ","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}