{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"none","dataSources":[{"sourceId":3362,"databundleVersionId":31148,"sourceType":"competition"}],"dockerImageVersionId":30918,"isInternetEnabled":true,"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","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import os \n\ndata_dir = '/kaggle/input/dogs-vs-cats'\nprint(os.listdir(data_dir))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-02-27T01:12:51.268285Z","iopub.execute_input":"2025-02-27T01:12:51.268729Z","iopub.status.idle":"2025-02-27T01:12:51.275591Z","shell.execute_reply.started":"2025-02-27T01:12:51.268692Z","shell.execute_reply":"2025-02-27T01:12:51.274607Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"!unzip -qq /kaggle/input/dogs-vs-cats/train.zip","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-02-27T01:15:31.958829Z","iopub.execute_input":"2025-02-27T01:15:31.959214Z","iopub.status.idle":"2025-02-27T01:15:42.962257Z","shell.execute_reply.started":"2025-02-27T01:15:31.959183Z","shell.execute_reply":"2025-02-27T01:15:42.960916Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import matplotlib.pyplot as plt\nfrom PIL import Image\nplt.figure(figsize = (15,15))\n\nimage =  os.listdir('/kaggle/working/train')\n\nfor i in range(36):\n    plt.subplot(6,6,i+1)\n    img = Image.open(os.path.join('/kaggle/working/train',image[i]))\n    plt.imshow(img)\n    plt.axis('off')\n    plt.title(f\"Image {i+1}\")\nplt.tight_layout()\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-02-27T01:40:35.350613Z","iopub.execute_input":"2025-02-27T01:40:35.351023Z","iopub.status.idle":"2025-02-27T01:40:39.443928Z","shell.execute_reply.started":"2025-02-27T01:40:35.350990Z","shell.execute_reply":"2025-02-27T01:40:39.442425Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"original_dir = pathlib.Path('train')\nnew_base_dir = pathlib.Path('cats_vs_dogs_small')\n\ndef make_subset(subset_name, start_index, end_index):\n    for category in ('cat', 'dog'):\n        dir = new_base_dir / subset_name / category\n        os.makedirs(dir, exist_ok = True)\n        fnames = [f\"{category}.{i}.jpg\" for i in range(start_index, end_index)]\n        for fname in fnames:\n            shutil.copyfile(src = original_dir/fname, dst = dir / fname)\n\nmake_subset(\"train\", start_index = 0, end_index = 1000)\nmake_subset(\"validation\", start_index = 1000, end_index = 1500)\nmake_subset(\"test\", start_index = 1500, end_index = 2500)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-02-27T02:11:02.409618Z","iopub.execute_input":"2025-02-27T02:11:02.410042Z","iopub.status.idle":"2025-02-27T02:11:03.432421Z","shell.execute_reply.started":"2025-02-27T02:11:02.410013Z","shell.execute_reply":"2025-02-27T02:11:03.431242Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null}]}