flow_from_dataframe.py

# ImageDataGenerator flow_from_dataframe

df_train = pd.read_csv(home_path + r'/emergency_train.csv')
df_train['emergency_or_not'] = df_train['emergency_or_not'].astype('str') # requires target in string format

train_generator_df = datagen.flow_from_dataframe(dataframe=df_train, 
                                              directory=home_path+'/images/',
                                              x_col="image_names", 
                                              y_col="emergency_or_not", 
                                              class_mode="binary", 
                                              target_size=(200, 200), 
                                              batch_size=1,
                                              rescale=1.0/255,
                                              seed=2020)
# plotting images
fig, ax = plt.subplots(nrows=1, ncols=4, figsize=(15,15))

for i in range(4):

  # convert to unsigned integers for plotting
  image = next(train_generator_df)[0].astype('uint8')

  # changing size from (1, 200, 200, 3) to (200, 200, 3) for plotting the image
  image = np.squeeze(image)

  # plot raw pixel data
  ax[i].imshow(image)
  ax[i].axis('off')