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rendering_example_dev.py
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from utils import *
from rendering_ops import *
import tensorflow as tf
import numpy as np
import time
VERTEX_NUM = 53215
def main(_):
batch_size = 16
output_size = 224
texture_size = [192, 224]
mDim = 8
vertexNum = VERTEX_NUM
channel_num = 3
data = np.load('sample_data.npz')
gpu_options = tf.GPUOptions(visible_device_list ="0", allow_growth = True)
with tf.Session(config=tf.ConfigProto(allow_soft_placement=True, log_device_placement=False, gpu_options=gpu_options)) as sess:
""" Graph """
m_ph = tf.placeholder(tf.float32, [batch_size, mDim])
shape_ph = tf.placeholder(tf.float32, [batch_size, vertexNum*3])
texture_ph = tf.placeholder(tf.float32, [batch_size]+texture_size +[channel_num])
image_ph = tf.placeholder(tf.float32, [batch_size, output_size, output_size, channel_num])
'''
normal_v1 = DEPRECATED_compute_normalf(m_ph, shape_ph, output_size=output_size)
normal_v2 = NEW_compute_normalf(m_ph, shape_ph, output_size=output_size)
s_land1, s_land2 = sess.run( [normal_v1, normal_v2], feed_dict={ shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print('s_land1')
print(s_land1.shape)
print(s_land1[10,0:3,100:103])
print('s_land2')
print(s_land2.shape)
print(s_land2[10,0:3,100:103])
'''
#images_v1, foreground_mask_v1 = DEPRECATED_warp_texture(texture_ph, m_ph, shape_ph, output_size = output_size)
images, foreground_mask = warp_texture(texture_ph, m_ph, shape_ph, output_size = output_size)
#s_time = time.time()
#for i in range(1):
# s_img_v1 = sess.run( images_v1, feed_dict={ texture_ph: data['sample_texture'], shape_ph:data['sample_shape'], m_ph:data['sample_m']})
#print("Time landmark v1: %f" % (time.time() - s_time))
#save_images(s_img_v1, [4, -1], './rendered_img_v1.png')
s_time = time.time()
for i in range(1):
s_img = sess.run( images, feed_dict={ texture_ph: data['sample_texture'], shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print("Time landmark v2: %f" % (time.time() - s_time))
save_images(s_img, [4, -1], './rendered_img.png')
#save_images(data['sample_texture'], [4, -1], './texture.png')
'''
upwarped_texture, texture_mask = unwarp_texture(image_ph, m_ph, shape_ph, output_size=output_size)
s_texture, s_mask = sess.run( [upwarped_texture, texture_mask], feed_dict={ image_ph: s_img, shape_ph:data['sample_shape'], m_ph:data['sample_m']})
save_images(s_mask, [4, -1], './texture_pred_mask.png')
save_images(s_texture, [4, -1], './texture_pred.png')
'''
'''
land1_x, land1_y = _DEPRECATED_compute_landmarks(m_ph, shape_ph, output_size=224)
land2_x, land2_y = compute_landmarks(m_ph, shape_ph, output_size=224)
s_land1, s_land2 = sess.run( [land1_y, land2_y], feed_dict={ shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print('s_land1')
print(s_land1.shape)
print(s_land1[10,0:5])
print('s_land2')
print(s_land2.shape)
print(s_land2[10,0:5])
'''
'''
s_time = time.time()
for i in range(100):
sess.run( [land1_x, land1_y], feed_dict={ shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print("Time landmark v1: %f" % (time.time() - s_time))
s_time = time.time()
for i in range(100):
sess.run( [land2_x, land2_y], feed_dict={ shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print("Time landmark v2: %f" % (time.time() - s_time))
s_time = time.time()
for i in range(100):
sess.run( [land1_x, land1_y], feed_dict={ shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print("Time landmark v1: %f" % (time.time() - s_time))
s_time = time.time()
for i in range(100):
sess.run( [land2_x, land2_y], feed_dict={ shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print("Time landmark v2: %f" % (time.time() - s_time))
s_time = time.time()
for i in range(100):
sess.run( [land1_x, land1_y], feed_dict={ shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print("Time landmark v1: %f" % (time.time() - s_time))
s_time = time.time()
for i in range(100):
sess.run( [land2_x, land2_y], feed_dict={ shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print("Time landmark v2: %f" % (time.time() - s_time))
s_time = time.time()
for i in range(100):
sess.run( [land1_x, land1_y], feed_dict={ shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print("Time landmark v1: %f" % (time.time() - s_time))
s_time = time.time()
for i in range(100):
sess.run( [land2_x, land2_y], feed_dict={ shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print("Time landmark v2: %f" % (time.time() - s_time))
s_time = time.time()
for i in range(1000):
sess.run( [land1_x, land1_y], feed_dict={ shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print("Time landmark v1: %f" % (time.time() - s_time))
s_time = time.time()
for i in range(1000):
sess.run( [land2_x, land2_y], feed_dict={ shape_ph:data['sample_shape'], m_ph:data['sample_m']})
print("Time landmark v2: %f" % (time.time() - s_time))
'''
if __name__ == '__main__':
tf.app.run()