| 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 |
