分割分类数据集_同时分类和分割多任务数据集-优快云博客

本文链接：https://blog.youkuaiyun.com/monk96/article/details/131726033

该Python代码用于将指定文件夹下的图像按比例划分为训练集和验证集。它首先定义了各个情感类别的文件夹路径，然后计算出验证集所需的图片数量。接着，它打乱图片列表并将图片移动到新建的train和val文件夹中，分别对应训练和验证集。

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分割分类数据集

# -*-coding: utf-8 -*-
import os
import random
import shutil

# 定义各个文件夹的路径
parent_folder = "./"
a_folder = os.path.join(parent_folder, "angry")
b_folder = os.path.join(parent_folder, "happy")
c_folder = os.path.join(parent_folder, "relaxed")
d_folder = os.path.join(parent_folder, "sad")

# 计算每个文件夹中要划分为验证集的图片数量
val_ratio = 0.1
a_val_size = int(val_ratio * len(os.listdir(a_folder)))
b_val_size = int(val_ratio * len(os.listdir(b_folder)))
c_val_size = int(val_ratio * len(os.listdir(c_folder))) 
d_val_size = int(val_ratio * len(os.listdir(d_folder)))

# 分别对每个文件夹进行处理，将图片移动到 train/ 和 val/ 目录中
train_folder = os.path.join(parent_folder, "train")
val_folder = os.path.join(parent_folder, "val")
os.makedirs(train_folder, exist_ok=True)
os.makedirs(val_folder, exist_ok=True)
for folder in [a_folder, b_folder, c_folder, d_folder]:
    filenames = os.listdir(folder)
    random.shuffle(filenames)  # 打乱文件顺序
    val_filenames = set(filenames[:a_val_size])
    train_filenames = set(filenames[a_val_size:])

    # 移动文件到 train/ 或 val/ 目录中的子文件夹中
    for filename in train_filenames:
        src_path = os.path.join(folder, filename)
        print(train_folder)
        os.makedirs(os.path.join(train_folder, os.path.basename(folder)), exist_ok = True)
        dst_path = os.path.join(train_folder, os.path.basename(folder), filename)
        shutil.copy(src_path, dst_path)
    for filename in val_filenames:
        src_path = os.path.join(folder, filename)
        os.makedirs(os.path.join(train_folder, os.path.basename(folder)), exist_ok = True)
        dst_path = os.path.join(val_folder, os.path.basename(folder), filename)
        shutil.copy(src_path, dst_path)