from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from Dataset import Dataset
from GazeGAN import Gaze_GAN
from config.train_options import TrainOptions
opt = TrainOptions().parse()
os.environ['CUDA_VISIBLE_DEVICES'] = str(opt.gpu_id)
if __name__ == "__main__":
dataset = Dataset(opt)
gaze_gan = Gaze_GAN(dataset, opt)
gaze_gan.build_model()
gaze_gan.train()
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import os
from Dataset import Dataset
from GazeGAN import Gaze_GAN
from config.test_options import TestOptions
opt = TestOptions().parse()
os.environ['CUDA_VISIBLE_DEVICES'] = str(opt.gpu_id)
if __name__ == "__main__":
dataset = Dataset(opt)
gaze_gan = Gaze_GAN(dataset, opt)
gaze_gan.build_test_model()
gaze_gan.test()
import os
from Dataset import Dataset
from config import Config
from GazeGAN import Gaze_GAN
if __name__ == "__main__":
config = Config()
print config.exp_name
if config.CUDA:
os.environ['CUDA_VISIBLE_DEVICES'] = str(config.gpu_id)
dataset = Dataset(config)
gaze_gan = Gaze_GAN(dataset, config)
gaze_gan._init_inception()
gaze_gan.build_model()
if config.is_training:
gaze_gan.train()
else:
gaze_gan.test()
# ###output_data = gaze_gan.test_webcam(input_data)
img = cv2.imread('dataset/CustomData/IMG/0040a.jpg')
# while(1):
# cv2.imshow('IMG', img)
# if cv2.waitKey(1) & 0xFF == ord('q'):
# break
input_data = (img, 92, 107, 175, 103)
cap.release()
cv2.destroyAllWindows()
## RUN TEST
dataset = Dataset(opt)
gaze_gan = Gaze_GAN(dataset, opt)
gaze_gan.build_test_model()
return_output = gaze_gan.test_webcam(input_data)
final_output = (return_output + 1.0)
print(final_output)
final_output = final_output * 127.5
final_output = np.array(final_output, dtype=np.uint8)
print(final_output)
while (1):
cv2.imshow('IMG', final_output)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
import os
import time
from Dataset import Dataset
from GazeGAN import Gaze_GAN
from OpenVinoGazeCorrection import openVinoGazeGan
from config.train_options import TrainOptions
opt = TrainOptions().parse()
os.environ['CUDA_VISIBLE_DEVICES'] = str(opt.gpu_id)
if __name__ == "__main__":
dataset = Dataset(opt)
start_time = time.time()
gaze_gan = Gaze_GAN(dataset, opt)
gaze_gan.build_test_model()
gaze_gan.test(freeze_model=False,
flag_save_images=True,
custom_dataset=True,
num_custom_images=10)
print(
"\n \n OUTER Time elapsed in GazeGan inference using TF of 3451 images = ",
time.time() - start_time)
start_time = time.time()
openVinoGazeGan.main(dataset,
opt,
save_images=True,
custom_dataset=True,
num_custom_images=10)
print("\n \n OUTER Time elapsed in OV inference of 3451 images = ",