In [1]:
import tensorflow as tf
from nets import nets_factory
from preprocessing import preprocessing_factory
import reader
import model
import time
import os
import numpy as np
height = 0
width = 0
with open('./camera.jpg', 'rb') as img:
with tf.Session().as_default() as sess:
#if FLAGS.image_file.lower().endswith('png'):
# image = sess.run(tf.image.decode_png(img.read()))
#else:
image = sess.run(tf.image.decode_jpeg(img.read()))
height = image.shape[0]
width = image.shape[1]
tf.logging.info('Image size: %dx%d' % (width, height))
In [3]:
with tf.Graph().as_default():
with tf.Session().as_default() as sess:
image_preprocessing_fn, _ = preprocessing_factory.get_preprocessing(
'vgg_19',
is_training=False)
image = reader.get_image('./camera.jpg', height, width, image_preprocessing_fn)
image = tf.expand_dims(image, 0)
generated = model.net(image, training=False)
generated = tf.squeeze(generated, [0])
saver = tf.train.Saver(tf.global_variables())
sess.run([tf.global_variables_initializer(), tf.local_variables_initializer()])
#FLAGS.model_file = os.path.abspath(FLAGS.model_file)
saver.restore(sess, './denoised_starry.ckpt-done')
start_time = time.time()
generated = sess.run(generated)
generated = tf.cast(generated, tf.uint8)
end_time = time.time()
tf.logging.info('Elapsed time: %fs' % (end_time - start_time))
generated_file = 'generated/camerafangao.jpg'
if os.path.exists('generated') is False:
os.makedirs('generated')
with open(generated_file, 'wb') as img:
img.write(sess.run(tf.image.encode_jpeg(generated)))
tf.logging.info('Done. Please check %s.' % generated_file)
In [3]:
%matplotlib inline
import cv2
from matplotlib import pyplot as plt
img = cv2.imread('generated/fangao.jpg')
plt.imshow(img)
Out[3]:
In [ ]: