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54 lines
2.3 KiB
54 lines
2.3 KiB
import os
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import csv
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import shutil
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import pandas as pd
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def index_label(photo_folder, csv_name):
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# 读取照片数据文件夹
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photo_files = os.listdir(photo_folder)
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# 提取数字作为索引
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indexes = [int(os.path.splitext(file)[0]) for file in photo_files]
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# 打开原始CSV文件和新的CSV文件
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csv_file = 'data/emotion.csv'
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new_csv_file = 'data/'+csv_name+'.csv'
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with open(csv_file, 'r') as file:
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reader = csv.reader(file)
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data = list(reader)
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# 添加索引列
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header = ['索引', '标签']
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result = [header] + [[index, data[index][0]] + data[index][1:] for index in indexes if index < len(data)]
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# 将结果保存为新的CSV文件
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# new_csv_file = '新的CSV文件路径'
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with open(new_csv_file, 'w', newline='') as file:
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writer = csv.writer(file)
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writer.writerows(result)
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def image_classification(photo_folder, csv_name):
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# 读取包含索引和标签的数据文件
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# 定义要删除的文件夹路径
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target_folder = 'data_classification/' + csv_name # 目标文件夹路径
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# 遍历文件夹中的文件并删除
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for filename in os.listdir(target_folder):
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file_path = os.path.join(target_folder, filename)
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try:
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if os.path.isfile(file_path) or os.path.islink(file_path):
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os.unlink(file_path) # 删除文件
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elif os.path.isdir(file_path):
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shutil.rmtree(file_path) # 递归删除文件夹及其内容
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except Exception as e:
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print(f'无法删除文件：{file_path}')
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new_csv_file = 'data/' + csv_name + '.csv'
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df = pd.read_csv(new_csv_file, encoding='GBK')
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# 设置原始文件夹路径和目标文件夹路径
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# 遍历 DataFrame
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for index, row in df.iterrows():
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file_index = row['索引'] # 索引对应的列名
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file_label = row['标签'] # 标签对应的列名
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source_file = os.path.join(photo_folder, f'{file_index}.jpg') # 原始文件路径
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target_folder_label = os.path.join(target_folder, str(file_label)) # 目标文件夹路径
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# 创建对应标签的目标文件夹（如果不存在）
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os.makedirs(target_folder_label, exist_ok=True)
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# 复制文件到目标文件夹
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shutil.copy(source_file, target_folder_label) |