def evaluate(args):
content_image = utils.tensor_load_rgbimage(args.content_image,
size=args.content_size,
keep_asp=True)
content_image = content_image.unsqueeze(0)
style = utils.tensor_load_rgbimage(args.style_image, size=args.style_size)
style = style.unsqueeze(0)
style = utils.preprocess_batch(style)
style_model = Net(ngf=args.ngf)
style_model.load_state_dict(torch.load(args.model), False)
if args.cuda:
style_model.cuda()
content_image = content_image.cuda()
style = style.cuda()
style_v = Variable(style)
content_image = Variable(utils.preprocess_batch(content_image))
style_model.setTarget(style_v)
output = style_model(content_image)
output = utils.color_match(output, style_v)
utils.tensor_save_bgrimage(output.data[0], args.output_image, args.cuda)
def color_map(frame: np.array,
start_x: int = 0,
start_y: int = 0) -> Dict[str, float]:
"""
Creates a color mapping for the passed frame
"""
m = dict()
for r, row in enumerate(frame):
for c, col in enumerate(row):
key = f"{c + start_x}|{r + start_y}"
if key in m:
raise Exception(f"Duplicate key {key}")
m[key] = color_match(col, REFERENCE_COLOR, DM_THRESH, DA_THRESH)
return m
xP=[x.replace('lfw','lfw_aegan') for x in P]
xQ=[x.replace('lfw','lfw_aegan') for x in Q]
PF=model.mean_F(utils.image_feed(xP[:K],image_dims))
QF=model.mean_F(utils.image_feed(xQ[:K],image_dims))
if config.scaling=='beta':
WF=(QF-PF)/((QF-PF)**2).mean()
elif config.scaling=='none':
WF=(QF-PF)
max_iter=config.iter
init=o
# for each interpolation step
for delta in delta_params:
print(xX,b,delta)
t2=time.time()
Y=model.F_inverse(XF+WF*delta,max_iter=max_iter,initial_image=init)
t3=time.time()
print('{} minutes to reconstruct'.format((t3-t2)/60.0))
result[-1].append(Y)
max_iter=config.iter//2
init=Y
result=numpy.asarray(result)
original=numpy.asarray(original)
if 'color' in postprocess:
result=utils.color_match(numpy.expand_dims(original,1),result)
m=imageutils.montage(numpy.concatenate([numpy.expand_dims(original,1),result],axis=1))
imageutils.write('results/demo1.png',m)
print('Output is results/demo1.png')
t1=time.time()
print('{} minutes ({} minutes per image).'.format((t1-t0)/60.0,(t1-t0)/60.0/result.shape[0]/result.shape[1]))
t2=time.time()
Y=model.F_inverse(XF+WF*delta,max_iter=max_iter,initial_image=init)
t3=time.time()
print('{} minutes to reconstruct'.format((t3-t2)/60.0))
result.append(Y)
max_iter=config.iter//2
init=Y
result=numpy.asarray([result])
original=numpy.asarray([original])
X_mask=prefix_path+'-mask.png'
if 'mask' in postprocess and os.path.exists(X_mask):
mask=imageutils.resize(imageutils.read(X_mask),image_dims)
result*=mask
result+=original*(1-mask)
if 'color' in postprocess:
result=utils.color_match(numpy.asarray([original]),result)
if 'mask' in postprocess and os.path.exists(X_mask):
result*=mask
result+=original*(1-mask)
if config.include_original:
m=imageutils.montage(numpy.concatenate([numpy.expand_dims(original,1),result],axis=1))
else:
m=imageutils.montage(result)
if config.output:
opath=config.output
else:
opath='{}_{}_{}{}.{}'.format(prefix_path,timestamp,config.method,postfix_comment,config.output_format)
imageutils.write(opath,m)
opathlist.append(opath)
print('Outputs are {}'.format(' '.join(opathlist)))
t1=time.time()
delta = delta0
while delta <= delta1:
print('Starting frame #{:06}, {}'.format(i + 1,
(time.time() - t0) / 60.0))
result = model.F_inverse(XF + WF * delta,
max_iter=max_iter,
initial_image=init)
max_iter = config.step_iter
init = result
i = i + 1
delta = delta + ddelta
if 'mask' in postprocess and os.path.exists(X_mask):
result *= mask
result += original * (1 - mask)
if 'color' in postprocess:
result = utils.color_match(numpy.asarray([original]),
numpy.asarray([[result]]))[0, 0]
if 'mask' in postprocess and os.path.exists(X_mask):
result *= mask
result += original * (1 - mask)
imageutils.write(
prefix_path + postfix_comment + '/{:06}.png'.format(i), result)
# generate movie
cmd = [
'ffmpeg', '-y', '-f', 'image2', '-i',
prefix_path + postfix_comment + '/%06d.png', '-crf', '19', '-g', '60',
'-r', '30', '-s', '{}x{}'.format(original.shape[1], original.shape[0]),
'-pix_fmt', 'yuv420p', prefix_path + postfix_comment +
'_movie.{}'.format(config.output_format)
]
print(' '.join(pipes.quote(x) for x in cmd))