{ "cells": [ { "cell_type": "code", "execution_count": 2, "id": "537ea5d0-1d6c-423e-9417-171b70a76c66", "metadata": {}, "outputs": [], "source": [ "import os\n", "import pandas as pd\n", "\n", "path = '//192.168.11.63/data/DATASETS/Energomash/915_learning'\n", "pd_columns = ['file_name']\n", "df = pd.DataFrame(columns=pd_columns)\n", "\n", "p = 0\n", "for i in os.walk(path):\n", " p+=1\n", " if p != 1:\n", " for j in i[2]:\n", " row = pd.DataFrame({pd_columns[0]: [str(str(i[0]) + '\\\\' + str(j)).replace('\\\\', '/')]})\n", " df = pd.concat([df, row], ignore_index=True)\n", "\n", "df.to_csv(path + '\\dataset.csv', index=False)" ] }, { "cell_type": "code", "execution_count": null, "id": "8f6e1ff8", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.6" } }, "nbformat": 4, "nbformat_minor": 5 }