使用flow_from_dataframe，什么是正确的“值"?为y_col [英] Using flow_from_dataframe what is the correct "value" for y_col

问题描述

我正在用熊猫读取一个csv文件，并给出存储在colname

I am reading in a csv file with pandas, and give the column names stored in colname

colnames=['file', 'label'] 
# Read data from file 
data = pd.read_csv('./Hand_Annotations_2.csv',names=colnames, header=None)
# Preview the first 5 lines of the loaded data 
data.head()

然后，我使用ImageDataGenerator()和flow_fromdataframe()来获取批量数据

Then, I use ImageDataGenerator() and flow_fromdataframe() to get batches of data

train_generator=datagen.flow_from_dataframe(dataframe=data,
                                            directory=None, 
                                            x_col=colnames[0], 
                                            y_col=colnames[1],
                                            class_indices=IDmap,
                                            class_mode="categorical", target_size=(224,224), batch_size=32)

但是我得到一个错误，如下:

But I get an error, as below:

TypeError:如果class_mode ="categorical"，则y_col ="label"列值 必须为字符串，列表或元组.

TypeError: If class_mode="categorical", y_col="label" column values must be type string, list or tuple.

但是我的y_col是一个字符串.如果我只输入"label"，则会收到相同的错误.它似乎也可以与x_col一起使用.

But my y_col is a string. I get the same error if I just enter "label". It also seems to work with x_col.

有人可以指出我的错误吗?

Can someone point me to my mistake?

谢谢

解决方案

读取具有dtype的csv，例如str:

read csv with dtype e.g. str:

data = pd.read_csv('./Hand_Annotations_2.csv',dtype=str,names=colnames, header=None)

推荐答案

您可以检查github中的代码以查看其实际检查内容，特别是

You can check the code in github for what it is actually being checked, specially here. Keras preprocessing is checking that all the values have allowed types (str, list or tuple), so the check is failing, you have to check that all values of the y_col column have the right type.

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