Data Augmentation + Dán nhãn cho ảnh

#chuẩn bị các tập generator cho train và test
image_generator = ImageDataGenerator(dtype='float32',
                                     horizontal_flip=True,
                                     vertical_flip=True,
                                     rotation_range=20,
                                     width_shift_range=0.2,
                                     height_shift_range=0.2,
                                     data_format='channels_last',
                                     fill_mode='nearest',
                                     shear_range=0.2
                                     )

train_generator= image_generator.flow_from_dataframe(dataframe=train_1,
                                       directory='../input/siim-isic-melanoma-classification/jpeg/train',
                                       x_col= 'image_name',
                                       y_col='benign_malignant',
                                       color_mode='rgb',
                                       class_mode='binary', #this will return one_hot encode labels
                                       target_size=(256,256),
                                       seed=42,
                                       batch_size=16,
                                       shuffle=True,
                                       interpolation='nearest'
                                       )

validation_generator= image_generator.flow_from_dataframe(dataframe=validation_1,
                                       directory='../input/siim-isic-melanoma-classification/jpeg/train',
                                       x_col= 'image_name',
                                       y_col='benign_malignant',
                                       color_mode='rgb',
                                       class_mode='binary',
                                       target_size=(256,256),
                                       batch_size=16,
                                       seed=42,
                                       shuffle=True,
                                       interpolation='nearest'
                                       )
#tập test:
image_generator_1 = ImageDataGenerator(rescale=1/255.,
                                     dtype='float16'
                                     )

test_generator= image_generator_1.flow_from_dataframe(test_raw,
                                                    directory='../input/siim-isic-melanoma-classification/test',
                                                    x_col='image_name',
                                                    class_mode=None,
                                                    color_mode='rgb',
                                                    target_size=(256,256),
                                                    batch_size=32,
                                                    seed=42,
                                                    shuffle= False,
                                                    interpolation='nearest'