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before_proc.py
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before_proc.py
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# -*- coding: utf-8 -*-
# 前処理、
from keras.preprocessing.image import ImageDataGenerator, array_to_img, img_to_array, load_img
datagen = ImageDataGenerator(
rotation_range=40,
width_shift_range=0.2,
height_shift_range=0.2,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True,
fill_mode='nearest')
img = load_img('data_in/train/bird/tori_11.jpg') # this is a PIL image
x = img_to_array(img) # this is a Numpy array with shape (3, 150, 150)
x = x.reshape((1,) + x.shape) # this is a Numpy array with shape (1, 3, 150, 150)
# the .flow() command below generates batches of randomly transformed images
# and saves the results to the `preview/` directory
# preview, jpeg, cat
img_num = 20
i = 0
for batch in datagen.flow(x, batch_size=1,
save_to_dir='preview', save_prefix='tori', save_format='jpg'):
i += 1
if i > img_num:
break # otherwise the generator would loop indefinitely