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test_model.py
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test_model.py
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from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
# os.environ['CUDA_VISIBLE_DEVICES'] = '0'
print('pid: {} GPU: {}'.format(os.getpid(), os.environ['CUDA_VISIBLE_DEVICES']))
import tensorflow as tf
import numpy as np
import cv2
from generate_data import gen_data
def main():
meta_file = './models2/model0/model.meta'
ckpt_file = './models2/model0/model.ckpt-0'
# test_list = './data/300w_image_list.txt'
image_size = 112
image_files = 'data/test_data/list.txt'
out_dir = 'result'
if not os.path.exists(out_dir):
os.mkdir(out_dir)
with tf.Graph().as_default():
with tf.Session() as sess:
print('Loading feature extraction model.')
saver = tf.train.import_meta_graph(meta_file)
saver.restore(tf.get_default_session(), ckpt_file)
graph = tf.get_default_graph()
images_placeholder = graph.get_tensor_by_name('image_batch:0')
phase_train_placeholder = graph.get_tensor_by_name('phase_train:0')
landmark_L1 = graph.get_tensor_by_name('landmark_L1:0')
landmark_L2 = graph.get_tensor_by_name('landmark_L2:0')
landmark_L3 = graph.get_tensor_by_name('landmark_L3:0')
landmark_L4 = graph.get_tensor_by_name('landmark_L4:0')
landmark_L5 = graph.get_tensor_by_name('landmark_L5:0')
landmark_total = [landmark_L1, landmark_L2, landmark_L3, landmark_L4, landmark_L5]
file_list, train_landmarks, train_attributes, train_euler_angles = gen_data(image_files)
print(file_list)
for file in file_list:
filename = os.path.split(file)[-1]
image = cv2.imread(file)
# image = cv2.resize(image, (image_size, image_size))
input = cv2.cvtColor(image.copy(), cv2.COLOR_BGR2RGB)
input = cv2.resize(input, (image_size, image_size))
input = input.astype(np.float32)/256.0
input = np.expand_dims(input, 0)
print(input.shape)
feed_dict = {
images_placeholder: input,
phase_train_placeholder: False
}
pre_landmarks = sess.run(landmark_total, feed_dict=feed_dict)
print(pre_landmarks)
pre_landmark = pre_landmarks[0]
h, w, _ = image.shape
pre_landmark = pre_landmark.reshape(-1, 2) * [h, w]
for (x, y) in pre_landmark.astype(np.int32):
cv2.circle(image, (x, y), 1, (0, 0, 255))
cv2.imshow('0', image)
cv2.waitKey(0)
cv2.imwrite(os.path.join(out_dir, filename), image)
if __name__ == '__main__':
main()