ip_address = row[0] folder_name = row[1] 详解
时间: 2024-05-23 10:10:47 浏览: 3
这段代码将从一个数据行中读取两个值并将它们存储到变量ip_address和folder_name中。具体来说,row[0]表示该行中的第一个元素(通常是一个IP地址),它将被赋值给变量ip_address。同样,row[1]表示该行中的第二个元素(通常是一个文件夹名称),它将被赋值给变量folder_name。这是一种常见的使用Python处理CSV文件的方法。
相关问题
为每句代码做注释:for class_name in class_names: current_class_data_path = os.path.join(src_data_folder, class_name) current_all_data = os.listdir(current_class_data_path) current_data_length = len(current_all_data) current_data_index_list = list(range(current_data_length)) random.shuffle(current_data_index_list) train_folder = os.path.join(os.path.join(target_data_folder, 'train'), class_name) val_folder = os.path.join(os.path.join(target_data_folder, 'val'), class_name) test_folder = os.path.join(os.path.join(target_data_folder, 'test'), class_name) train_stop_flag = current_data_length * train_scale val_stop_flag = current_data_length * (train_scale + val_scale) current_idx = 0 train_num = 0 val_num = 0 test_num = 0 for i in current_data_index_list: src_img_path = os.path.join(current_class_data_path, current_all_data[i]) if current_idx <= train_stop_flag: copy2(src_img_path, train_folder) train_num = train_num + 1 elif (current_idx > train_stop_flag) and (current_idx <= val_stop_flag): copy2(src_img_path, val_folder) val_num = val_num + 1 else: copy2(src_img_path, test_folder) # print("{}复制到了{}".format(src_img_path, test_folder)) test_num = test_num + 1 current_idx = current_idx + 1
# 循环遍历每个类别的文件夹
for class_name in class_names:
# 拼接当前类别的数据路径
current_class_data_path = os.path.join(src_data_folder, class_name)
# 获取当前类别的所有数据文件名
current_all_data = os.listdir(current_class_data_path)
# 获取当前类别的数据数量
current_data_length = len(current_all_data)
# 生成当前类别数据的索引列表
current_data_index_list = list(range(current_data_length))
# 随机打乱当前类别数据的索引列表
random.shuffle(current_data_index_list)
# 拼接训练集、验证集、测试集的路径
train_folder = os.path.join(os.path.join(target_data_folder, 'train'), class_name)
val_folder = os.path.join(os.path.join(target_data_folder, 'val'), class_name)
test_folder = os.path.join(os.path.join(target_data_folder, 'test'), class_name)
# 计算训练集、验证集、测试集在当前类别中的截止点
train_stop_flag = current_data_length * train_scale
val_stop_flag = current_data_length * (train_scale + val_scale)
# 初始化当前类别的数据索引、训练集数量、验证集数量、测试集数量
current_idx = 0
train_num = 0
val_num = 0
test_num = 0
# 循环遍历当前类别的数据索引列表,将数据复制到对应的训练集、验证集、测试集文件夹中
for i in current_data_index_list:
src_img_path = os.path.join(current_class_data_path, current_all_data[i])
# 如果当前索引在训练集截止点之前,则将数据复制到训练集
if current_idx <= train_stop_flag:
copy2(src_img_path, train_folder)
train_num = train_num + 1
# 如果当前索引在训练集截止点和验证集截止点之间,则将数据复制到验证集
elif (current_idx > train_stop_flag) and (current_idx <= val_stop_flag):
copy2(src_img_path, val_folder)
val_num = val_num + 1
# 如果当前索引在验证集截止点之后,则将数据复制到测试集
else:
copy2(src_img_path, test_folder)
# 打印当前数据的拷贝信息
# print("{}复制到了{}".format(src_img_path, test_folder))
test_num = test_num + 1
# 更新当前类别的数据索引和数量统计信息
current_idx = current_idx + 1
# 导入 ArcPy 模块 import arcpy # 获取输入参数 input_layer = arcpy.GetParameterAsText(0) field_name = arcpy.GetParameterAsText(1) field_value = arcpy.GetParameterAsText(2) output_folder = arcpy.GetParameterAsText(3) # 定义筛选条件 where_clause = "{} = '{}'".format(arcpy.AddFieldDelimiters(input_layer, field_name), field_value) # 使用游标进行筛选并导出要素图层 with arcpy.da.SearchCursor(input_layer, ["OID@", "SHAPE@"], where_clause) as cursor: for row in cursor: output_name = "feature_{}.shp".format(row[0]) output_path = output_folder + "\\" + output_name arcpy.CopyFeatures_management(row[1], output_path)运行错误:Traceback (most recent call last): File "D:\多对一空间连接\批量删除小面积.py", line 13, in <module> NameError: name 'where_clause' is not defined 执行(删除小面)失败。请改正代码
看起来出错的原因是 `where_clause` 变量在定义之前被调用了。你可以将 `where_clause` 的定义放在获取输入参数之后,如下所示:
```python
import arcpy
# 获取输入参数
input_layer = arcpy.GetParameterAsText(0)
field_name = arcpy.GetParameterAsText(1)
field_value = arcpy.GetParameterAsText(2)
output_folder = arcpy.GetParameterAsText(3)
# 定义筛选条件
where_clause = "{} = '{}'".format(arcpy.AddFieldDelimiters(input_layer, field_name), field_value)
# 使用游标进行筛选并导出要素图层
with arcpy.da.SearchCursor(input_layer, ["OID@", "SHAPE@"], where_clause) as cursor:
for row in cursor:
output_name = "feature_{}.shp".format(row[0])
output_path = output_folder + "\\" + output_name
arcpy.CopyFeatures_management(row[1], output_path)
```
这样应该就能够正常运行了。
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