{"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":"#%% IMPORTING LIBRARIES \n\nimport os\nimport glob\nimport shutil\nimport json\nimport keras\nimport itertools\nimport numpy as np\nimport pandas as pd\nimport seaborn as sns\nimport tensorflow as tf\nfrom PIL import Image\nimport matplotlib.pyplot as plt\nfrom collections import Counter\n\n# Defining the working directories\n\nwork_dir = '../input/cassava-leaf-disease-classification/'\nos.listdir(work_dir) \ntrain_path = '/kaggle/input/cassava-leaf-disease-classification/train_images'","metadata":{"_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","papermill":{"duration":6.513219,"end_time":"2021-02-14T01:45:26.697672","exception":false,"start_time":"2021-02-14T01:45:20.184453","status":"completed"},"tags":[],"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Evaluating the model\n\nimport keras\n\n#final_model1 = keras.models.load_model('../input/leafclasseffnet/Cassava_best_modelEffNetB4v5.h5')\nfinal_model2 = keras.models.load_model('../input/cassava3/Cassava_best_modelEffNetB3x.h5')","metadata":{"papermill":{"duration":8.652263,"end_time":"2021-02-14T01:45:35.35542","exception":false,"start_time":"2021-02-14T01:45:26.703157","status":"completed"},"tags":[],"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Predictions on the test set","metadata":{"papermill":{"duration":0.004725,"end_time":"2021-02-14T01:45:35.365276","exception":false,"start_time":"2021-02-14T01:45:35.360551","status":"completed"},"tags":[]}},{"cell_type":"code","source":"TEST_DIR = '../input/cassava-leaf-disease-classification/test_images/'\ntest_images = os.listdir(TEST_DIR)\npredictions = []\nIMG_SIZE = 380\nIMG_SIZE1 = 300\nsize = (IMG_SIZE,IMG_SIZE)\nsize1= (IMG_SIZE1,IMG_SIZE1)\nfor image in test_images:\n    '''\n    img = Image.open(TEST_DIR + image)\n    img = img.resize(size)\n    img = np.expand_dims(img, axis=0)\n    prediction1 = final_model1.predict(img)\n    print(prediction1)\n    '''\n    img1 = Image.open(TEST_DIR + image)\n    img1 = img1.resize(size1)\n    img1 = np.expand_dims(img1, axis=0)\n    prediction2 = final_model2.predict(img1)\n    print(prediction2)\n    #result = prediction1 + prediction2\n    #print(result)\n    #predictions.extend(result.argmax(axis = 1))\n    predictions.extend(prediction2.argmax(axis = 1))","metadata":{"papermill":{"duration":3.094648,"end_time":"2021-02-14T01:45:38.464921","exception":false,"start_time":"2021-02-14T01:45:35.370273","status":"completed"},"tags":[],"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"predictions","metadata":{"papermill":{"duration":0.01789,"end_time":"2021-02-14T01:45:38.488778","exception":false,"start_time":"2021-02-14T01:45:38.470888","status":"completed"},"tags":[],"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"# Creating the CSV for final submission\n\nsub = pd.DataFrame({'image_id': test_images, 'label': predictions})\ndisplay(sub)\nsub.to_csv('submission.csv', index = False)\n","metadata":{"papermill":{"duration":0.043533,"end_time":"2021-02-14T01:45:38.538449","exception":false,"start_time":"2021-02-14T01:45:38.494916","status":"completed"},"tags":[],"trusted":true},"execution_count":null,"outputs":[]}]}