def f(file):
image = Image.open(file)
image = np.array(image)
for n in nodes[1:]:
n.multipleLoad(image.size)
updateNode(n)
if len(nodes):
updateNode(nodes[0].parent)
if len(image.shape) == 2:
return image.reshape(*image.shape, 1)
if image.shape[2] == 3 or image.shape[2] == 4:
return image
else:
raise RuntimeError('Unknown image format')
def f(im):
nonlocal h, w
if opt['update']:
_, h, w = im.shape
oriLoad = h * w
h = round(h * opt['scaleH']) if 'scaleH' in opt else opt['height']
w = round(w * opt['scaleW']) if 'scaleW' in opt else opt['width']
newLoad = h * w
if len(nodes):
nodes[pos].load = im.nelement()
newLoad /= oriLoad
for n in nodes[pos + 1:]:
n.multipleLoad(newLoad)
updateNode(n)
if out['source']:
opt['update'] = False
return resizeByTorch(im, w, h, opt['method'])
def f(file):
image = Image.open(file)
context.imageMode = image.mode
if image.mode == 'P':
context.palette = image
image = image.convert('RGB')
image = np.array(image)
for n in nodes:
n.multipleLoad(image.size)
updateNode(n)
if len(nodes):
p = nodes[0].parent
updateNode(p)
p.callback(p)
if len(image.shape) == 2:
return image.reshape(*image.shape, 1)
if image.shape[2] == 3 or image.shape[2] == 4:
return image
else:
raise RuntimeError('Unknown image format')