使用tf 2.3.0拆分数据集Cats_vs_dogs以进行训练和val

import tensorflow as tf
import os
import random

dataset_path = 'path/to/dataset/Cats_vs_dogs'
train_val_split_ratio = 0.8  # 训练集和验证集的比例

# 获取所有图像文件的路径
image_paths = []
for root, dirs, files in os.walk(dataset_path):
    for file in files:
        if file.endswith('.jpg'):
            image_paths.append(os.path.join(root, file))

# 随机化数据集
random.shuffle(image_paths)

split_point = int(len(image_paths) * train_val_split_ratio)

train_dataset = image_paths[:split_point]
val_dataset = image_paths[split_point:]

# 创建训练集的tf.data.Dataset对象
train_data = tf.data.Dataset.from_tensor_slices(train_dataset)

# 创建验证集的tf.data.Dataset对象
val_data = tf.data.Dataset.from_tensor_slices(val_dataset)