深度学习常用程式码

之前没整理程式码的习惯
经常想到某些程式码
就要翻以前写的
觉得有点浪费时间

之后有用到就贴上来 慢慢更新
然后我会打一些关键字
方便自己用Ctrl + F 搜寻

#kaggle提交 csv存档df.to_csv('submission.csv',index=False)

from sklearn.model_selection import GroupKFold#5折 kfold 交叉验证#df.id id:要5折的项目gkf  = GroupKFold(n_splits = 5)df['fold'] = -1for fold, (train_idx, val_idx) in enumerate(gkf.split(df, groups = df.id.tolist())):    df.loc[val_idx, 'fold'] = fold

import pylab as plt#show图片 pltimg = plt.imread('path')plt.imshow(img)

from kaggle_datasets import KaggleDatasets#TPU上传资料集COMPETITION_NAME = "name"GCS_DS_PATH = KaggleDatasets().get_gcs_path(COMPETITION_NAME)

import cv2#resizeimg = cv2.imread('path')img = cv2.resize(img, (600, 600), interpolation=cv2.INTER_CUBIC)cv2.imwrite('path', img)

# 重新排序indexdf.reset_index(drop=True)