| 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" |
| } |
