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')