error using ImageDataGenerator,flow_from_dataframe where y

I am trying to train a model to learn to generate bounding boxes. To that end I have created a dataframe of the form show below. The values in the xmin,ymin, xmax, ymax are integers

                                       filepaths labels  xmin  ymin  xmax  ymax
0  C:\Temp\whales\test_images\000110707af0ba.jpg  whale    25    81   183   118
1  C:\Temp\whales\test_images\0006287ec424cb.jpg  whale    65   154   114   176
2  C:\Temp\whales\test_images\000809ecb2ccad.jpg  whale    77   118   156   144
3  C:\Temp\whales\test_images\00098d1376dab2.jpg  whale     9    61   220   176
4  C:\Temp\whales\test_images\000b8d89c738bd.jpg  whale     3    12   223   222

The values in xmin, ymin, xmax, ymax are integers. I then try to create a train generator from the data frame with

train_gen=gen.flow_from_dataframe(train_df,x_col='filepaths', ycol=['xmin','ymin', 'xmax','ymax'],                              
                                  target_size=img_size,color_mode='rgb',
                                  class_mode='multi_output', batch_size=batch_size, shuffle=True, 
                                  seed=123)

Executing this code throws an error shown below

TypeError: If class_mode="multi_output", y_col must be a list. Received str.

I have read all the similar questions but found no solution. Also read documentation in detail but have not solved he problem. Looks to me like y_col is a list as the documentation specifies. I also tried using above code with class_mode='raw'. That throws an error

KeyError: 'class'

I am using tensorflow 2.4.0 and python 3.7. Any help would be most appreciated.

CodePudding user response：

Yeah just figured out that you should be passing y_col and not ycol. Here is a working example:

import tensorflow as tf
import pandas as pd


train_df = pd.DataFrame(
    data = {
        'filepaths': ['/content/result_image0.png', '/content/result_image1.png', '/content/result_image2.png'],
        'labels': ['whale', 'whale', 'whale'],
        'xmin': [25, 65, 77],
        'ymin': [81, 154, 118],
        'xmax': [183, 114, 156],
        'ymax': [118, 176, 144]
    }
)
img_gen = tf.keras.preprocessing.image.ImageDataGenerator(rescale=1./255)
columns = ['xmin','ymin', 'xmax','ymax']
train_gen=img_gen.flow_from_dataframe(train_df,x_col='filepaths', y_col = columns,                              
                                  target_size=(100, 100), color_mode='rgb',
                                  class_mode='multi_output', batch_size=2, shuffle=True, 
                                  seed=123)

Tested with class_mode 'multi_output' and 'raw'.