| import numpy as np | |
| from keras.models import * | |
| from keras.layers import * | |
| from keras.applications.vgg16 import VGG16 | |
| from keras.preprocessing.image import ImageDataGenerator | |
| from keras.optimizers import * | |
| from keras.callbacks import ModelCheckpoint | |
| import cv2 | |
| def train_generator(batch_size=32): | |
| data_gen_args = dict(featurewise_center=True, | |
| rotation_range=90., | |
| width_shift_range=0.1, | |
| height_shift_range=0.1, | |
| fill_mode="constant", | |
| cval=255, | |
| horizontal_flip=True, | |
| vertical_flip=True, | |
| zoom_range=0.2) | |
| image_datagen = ImageDataGenerator(**data_gen_args) | |
| mask_datagen = ImageDataGenerator(**data_gen_args) | |
| seed = 1 | |
| image_generator = image_datagen.flow_fr |