def run_style_transfer(content_img, style_img, input_img, num_epoches=300):
print('Building the style transfer model...')
model, style_loss_list, content_loss_list = get_style_model_and_loss(
style_img, content_img)
input_param, optimizer = get_input_param_optimier(input_img)
print('Optimizing...')
epoch = [0]
while epoch[0] < num_epoches:
def clousure():
input_param.data.clamp_(0, 1)
model(input_param)
style_score = 0
content_score = 0
optimizer.zero_grad()
for sl in style_loss_list:
style_score += sl.backward()
for cl in content_loss_list:
content_score += cl.backward()
epoch[0] += 1
if epoch[0] % 50 == 0:
print('run {}'.format(epoch))
print('Style Loss: {:.4f} Content Loss: {:.4f}'.format(
style_score.data[0], content_score.data[0]))
print()
return style_score + content_score
optimizer.step(clousure)
input_param.data.clamp_(0, 1)
return input_param.data
def run_style_transfer(content_img, style_img, input_img, num_epoches=300):
print('Building the style transfer model..')
model, style_loss_list, content_loss_list = get_style_model_and_loss(
style_img, content_img)
input_param, optimizer = get_input_param_optimier(input_img)
print('Opimizing...')
epoch = [0]
while epoch[0] < num_epoches:
def closure():
input_param.data.clamp_(0, 1)
model(input_param)
style_score = 0
content_score = 0
optimizer.zero_grad()
for sl in style_loss_list:
style_score += sl.backward()
for cl in content_loss_list:
content_score += cl.backward()
epoch[0] += 1
if epoch[0] % 50 == 0:
print('run {}'.format(epoch))
print('Style Loss: {:.4f} Content Loss: {:.4f}'.format(
style_score.data[0], content_score.data[0]))
print()
return style_score + content_score
optimizer.step(closure)
input_param.data.clamp_(0, 1)
return input_param.data