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import argparse | |
from tools.utils import * | |
import os | |
from tqdm import tqdm | |
from glob import glob | |
import time | |
import numpy as np | |
from net import generator | |
os.environ["CUDA_VISIBLE_DEVICES"] = "-1" | |
def stats_graph(graph): | |
flops = tf.profiler.profile(graph, options=tf.profiler.ProfileOptionBuilder.float_operation()) | |
# params = tf.profiler.profile(graph, options=tf.profiler.ProfileOptionBuilder.trainable_variables_parameter()) | |
print('FLOPs: {}'.format(flops.total_float_ops)) | |
g_sess = None | |
test_generated = None | |
test_real = None | |
def test(checkpoint_dir, style_name, test_file, if_adjust_brightness, img_size=[256,256]): | |
global g_sess | |
global test_generated | |
global test_real | |
# tf.reset_default_graph() | |
result_dir = 'results/'+style_name | |
check_folder(result_dir) | |
if g_sess is None: | |
test_real = tf.placeholder(tf.float32, [1, None, None, 3], name='test') | |
with tf.variable_scope("generator", reuse=False): | |
test_generated = generator.G_net(test_real).fake | |
saver = tf.train.Saver() | |
gpu_options = tf.GPUOptions(allow_growth=True) | |
g_sess = tf.Session(config=tf.ConfigProto(allow_soft_placement=True, gpu_options=gpu_options)) | |
# load model | |
ckpt = tf.train.get_checkpoint_state(checkpoint_dir) # checkpoint file information | |
if ckpt and ckpt.model_checkpoint_path: | |
ckpt_name = os.path.basename(ckpt.model_checkpoint_path) # first line | |
saver.restore(sess, os.path.join(checkpoint_dir, ckpt_name)) | |
print(" [*] Success to read {}".format(os.path.join(checkpoint_dir, ckpt_name))) | |
else: | |
print(" [*] Failed to find a checkpoint") | |
return | |
# stats_graph(tf.get_default_graph()) | |
begin = time.time() | |
# print('Processing image: ' + sample_file) | |
sample_image = np.asarray(load_test_data(test_file, img_size)) | |
image_path = os.path.join(result_dir,'{0}'.format(os.path.basename(test_file))) | |
fake_img = g_sess.run(test_generated, feed_dict = {test_real : sample_image}) | |
if if_adjust_brightness: | |
save_images(fake_img, image_path, test_file) | |
else: | |
save_images(fake_img, image_path, None) | |
end = time.time() | |
print(f'test-time: {end-begin} s') | |
return image_path | |