{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.12.13","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[],"dockerImageVersionId":28755,"isInternetEnabled":false,"language":"python","sourceType":"notebook","isGpuEnabled":false}},"nbformat_minor":4,"nbformat":4,"cells":[{"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 20GB 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\n\n# Use the kagglehub client library to attach Kaggle resources like competitions, datasets, and models to your session\n# Learn more about kagglehub: https://github.com/Kaggle/kagglehub/blob/main/README.md\n\nimport kagglehub\n# kagglehub.dataset_download('<owner>/<dataset-slug>')","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import os\nimport warnings\nwarnings.filterwarnings(\"ignore\")\n\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n\nfrom PIL import Image\n\nimport tensorflow as tf\nfrom tensorflow.keras.preprocessing.image import ImageDataGenerator\n\nfrom tensorflow.keras.applications import EfficientNetB0, MobileNetV2\nfrom tensorflow.keras.applications.efficientnet import preprocess_input as efficientnet_preprocess\nfrom tensorflow.keras.applications.efficientnet import decode_predictions\nfrom tensorflow.keras.applications.mobilenet_v2 import preprocess_input as mobilenet_preprocess\n\nfrom tensorflow.keras.models import Sequential\nfrom tensorflow.keras.layers import GlobalAveragePooling2D, Dense, Dropout\nfrom tensorflow.keras.callbacks import EarlyStopping, ReduceLROnPlateau\n\nfrom sklearn.model_selection import train_test_split\n\nprint(\"TensorFlow version:\", tf.__version__)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2026-07-24T07:05:28.806264Z","iopub.execute_input":"2026-07-24T07:05:28.806973Z","iopub.status.idle":"2026-07-24T07:05:47.278356Z","shell.execute_reply.started":"2026-07-24T07:05:28.806894Z","shell.execute_reply":"2026-07-24T07:05:47.277398Z"}},"outputs":[{"name":"stdout","text":"TensorFlow version: 2.20.0\n","output_type":"stream"}],"execution_count":2},{"cell_type":"code","source":"image_dirs = []\n\nfor dirname, _, filenames in os.walk(\"/kaggle/input\"):\n    image_files = [\n        f for f in filenames\n        if f.lower().endswith((\".jpg\", \".jpeg\", \".png\"))\n    ]\n    \n    if len(image_files) > 0:\n        image_dirs.append((dirname, len(image_files)))\n\nprint(\"Found image folders:\")\nfor folder, count in image_dirs:\n    print(folder, \":\", count, \"images\")\n\n# 画像が一番多いフォルダをデータセットフォルダとして使う\nDATASET_DIRECTORY = sorted(image_dirs, key=lambda x: x[1], reverse=True)[0][0]\n\nprint(\"\\nSelected dataset path:\")\nprint(DATASET_DIRECTORY)\n\nfile_list = os.listdir(DATASET_DIRECTORY)\nprint(\"\\nNumber of files:\", len(file_list))","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]}