Files
2024-12-06 00:09:12 +08:00

84 lines
2.8 KiB
Python

import torch
from PIL import Image
from .imagefunc import log, tensor2pil, pil2tensor, image2mask
class RestoreCropBox:
def __init__(self):
self.NODE_NAME = 'RestoreCropBox'
@classmethod
def INPUT_TYPES(self):
return {
"required": {
"background_image": ("IMAGE", ),
"croped_image": ("IMAGE",),
"invert_mask": ("BOOLEAN", {"default": False}), # 反转mask#
"crop_box": ("BOX",),
},
"optional": {
"croped_mask": ("MASK",),
}
}
RETURN_TYPES = ("IMAGE", "MASK", )
RETURN_NAMES = ("image", "mask", )
FUNCTION = 'restore_crop_box'
CATEGORY = '😺dzNodes/LayerUtility'
def restore_crop_box(self, background_image, croped_image, invert_mask, crop_box,
croped_mask=None
):
b_images = []
l_images = []
l_masks = []
ret_images = []
ret_masks = []
for b in background_image:
b_images.append(torch.unsqueeze(b, 0))
for l in croped_image:
l_images.append(torch.unsqueeze(l, 0))
m = tensor2pil(l)
if m.mode == 'RGBA':
l_masks.append(m.split()[-1])
else:
l_masks.append(Image.new('L', size=m.size, color='white'))
if croped_mask is not None:
if croped_mask.dim() == 2:
croped_mask = torch.unsqueeze(croped_mask, 0)
l_masks = []
for m in croped_mask:
if invert_mask:
m = 1 - m
l_masks.append(tensor2pil(torch.unsqueeze(m, 0)).convert('L'))
max_batch = max(len(b_images), len(l_images), len(l_masks))
for i in range(max_batch):
background_image = b_images[i] if i < len(b_images) else b_images[-1]
croped_image = l_images[i] if i < len(l_images) else l_images[-1]
_mask = l_masks[i] if i < len(l_masks) else l_masks[-1]
_canvas = tensor2pil(background_image).convert('RGB')
_layer = tensor2pil(croped_image).convert('RGB')
ret_mask = Image.new('L', size=_canvas.size, color='black')
_canvas.paste(_layer, box=tuple(crop_box), mask=_mask)
ret_mask.paste(_mask, box=tuple(crop_box))
ret_images.append(pil2tensor(_canvas))
ret_masks.append(image2mask(ret_mask))
log(f"{self.NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish')
return (torch.cat(ret_images, dim=0), torch.cat(ret_masks, dim=0),)
NODE_CLASS_MAPPINGS = {
"LayerUtility: RestoreCropBox": RestoreCropBox
}
NODE_DISPLAY_NAME_MAPPINGS = {
"LayerUtility: RestoreCropBox": "LayerUtility: RestoreCropBox"
}