| import torch
|
| from PIL import Image
|
| from .imagefunc import log, tensor2pil, pil2tensor, image2mask
|
|
|
|
|
| class ExtendCanvas:
|
|
|
| def __init__(self):
|
| self.NODE_NAME = 'ExtendCanvas'
|
|
|
| @classmethod
|
| def INPUT_TYPES(self):
|
|
|
| return {
|
| "required": {
|
| "image": ("IMAGE", ),
|
| "invert_mask": ("BOOLEAN", {"default": True}),
|
| "top": ("INT", {"default": 0, "min": 0, "max": 99999, "step": 1}),
|
| "bottom": ("INT", {"default": 0, "min": 0, "max": 99999, "step": 1}),
|
| "left": ("INT", {"default": 0, "min": 0, "max": 99999, "step": 1}),
|
| "right": ("INT", {"default": 0, "min": 0, "max": 99999, "step": 1}),
|
| "color": ("COLOR", {"default": "#000000"},),
|
| },
|
| "optional": {
|
| "mask": ("MASK",),
|
| }
|
| }
|
|
|
| RETURN_TYPES = ("IMAGE", "MASK",)
|
| RETURN_NAMES = ("image", "mask")
|
| FUNCTION = 'extend_canvas'
|
| CATEGORY = '😺dzNodes/LayerUtility'
|
|
|
| def extend_canvas(self, image, invert_mask,
|
| top, bottom, left, right, color,
|
| mask=None,
|
| ):
|
|
|
| l_images = []
|
| l_masks = []
|
| ret_images = []
|
| ret_masks = []
|
|
|
| for l in image:
|
| l_images.append(torch.unsqueeze(l, 0))
|
| m = tensor2pil(l)
|
| if m.mode == 'RGBA':
|
| l_masks.append(m.split()[-1])
|
|
|
| if mask is not None:
|
| if mask.dim() == 2:
|
| mask = torch.unsqueeze(mask, 0)
|
| l_masks = []
|
| for m in mask:
|
| if invert_mask:
|
| m = 1 - m
|
| l_masks.append(tensor2pil(torch.unsqueeze(m, 0)).convert('L'))
|
| else:
|
| if len(l_masks) == 0:
|
| l_masks.append(Image.new('L', size=tensor2pil(l_images[0]).size, color='white'))
|
|
|
| max_batch = max(len(l_images), len(l_masks))
|
| for i in range(max_batch):
|
|
|
| _image = l_images[i] if i < len(l_images) else l_images[-1]
|
| _image = tensor2pil(_image).convert('RGB')
|
| _mask = l_masks[i] if i < len(l_masks) else l_masks[-1]
|
|
|
| width = _image.width + left + right
|
| height = _image.height + top + bottom
|
| _canvas = Image.new('RGB', (width, height), color)
|
| _mask_canvas = Image.new('L', (width, height), "black")
|
|
|
| _canvas.paste(_image, box=(left,top))
|
| _mask_canvas.paste(_mask.convert('L'), box=(left, top))
|
|
|
| ret_images.append(pil2tensor(_canvas))
|
| ret_masks.append(image2mask(_mask_canvas))
|
|
|
| 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: ExtendCanvas": ExtendCanvas
|
| }
|
|
|
| NODE_DISPLAY_NAME_MAPPINGS = {
|
| "LayerUtility: ExtendCanvas": "LayerUtility: ExtendCanvas"
|
| } |
