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| import torch | |
| from PIL import Image | |
| from .imagefunc import log, tensor2pil, pil2tensor, image2mask, mask2image | |
| from .imagefunc import chop_image, chop_mode, shift_image, expand_mask | |
| class DropShadow: | |
| def __init__(self): | |
| self.NODE_NAME = 'DropShadow' | |
| def INPUT_TYPES(self): | |
| return { | |
| "required": { | |
| "background_image": ("IMAGE", ), # | |
| "layer_image": ("IMAGE",), # | |
| "invert_mask": ("BOOLEAN", {"default": True}), # 反转mask | |
| "blend_mode": (chop_mode,), # 混合模式 | |
| "opacity": ("INT", {"default": 50, "min": 0, "max": 100, "step": 1}), # 透明度 | |
| "distance_x": ("INT", {"default": 25, "min": -9999, "max": 9999, "step": 1}), # x_偏移 | |
| "distance_y": ("INT", {"default": 25, "min": -9999, "max": 9999, "step": 1}), # y_偏移 | |
| "grow": ("INT", {"default": 6, "min": -9999, "max": 9999, "step": 1}), # 扩张 | |
| "blur": ("INT", {"default": 18, "min": 0, "max": 100, "step": 1}), # 模糊 | |
| "shadow_color": ("STRING", {"default": "#000000"}), # 背景颜色 | |
| }, | |
| "optional": { | |
| "layer_mask": ("MASK",), # | |
| } | |
| } | |
| RETURN_TYPES = ("IMAGE",) | |
| RETURN_NAMES = ("image",) | |
| FUNCTION = 'drop_shadow' | |
| CATEGORY = '😺dzNodes/LayerStyle' | |
| def drop_shadow(self, background_image, layer_image, | |
| invert_mask, blend_mode, opacity, distance_x, distance_y, | |
| grow, blur, shadow_color, | |
| layer_mask=None | |
| ): | |
| b_images = [] | |
| l_images = [] | |
| l_masks = [] | |
| ret_images = [] | |
| for b in background_image: | |
| b_images.append(torch.unsqueeze(b, 0)) | |
| for l in layer_image: | |
| l_images.append(torch.unsqueeze(l, 0)) | |
| m = tensor2pil(l) | |
| if m.mode == 'RGBA': | |
| l_masks.append(m.split()[-1]) | |
| if layer_mask is not None: | |
| if layer_mask.dim() == 2: | |
| layer_mask = torch.unsqueeze(layer_mask, 0) | |
| l_masks = [] | |
| for m in layer_mask: | |
| if invert_mask: | |
| m = 1 - m | |
| l_masks.append(tensor2pil(torch.unsqueeze(m, 0)).convert('L')) | |
| if len(l_masks) == 0: | |
| log(f"Error: {self.NODE_NAME} skipped, because the available mask is not found.", message_type='error') | |
| return (background_image,) | |
| max_batch = max(len(b_images), len(l_images), len(l_masks)) | |
| distance_x = -distance_x | |
| distance_y = -distance_y | |
| shadow_color = Image.new("RGB", tensor2pil(l_images[0]).size, color=shadow_color) | |
| for i in range(max_batch): | |
| background_image = b_images[i] if i < len(b_images) else b_images[-1] | |
| layer_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] | |
| # preprocess | |
| _canvas = tensor2pil(background_image).convert('RGB') | |
| _layer = tensor2pil(layer_image) | |
| if _mask.size != _layer.size: | |
| _mask = Image.new('L', _layer.size, 'white') | |
| log(f"Warning: {self.NODE_NAME} mask mismatch, dropped!", message_type='warning') | |
| if distance_x != 0 or distance_y != 0: | |
| __mask = shift_image(_mask, distance_x, distance_y) # 位移 | |
| shadow_mask = expand_mask(image2mask(__mask), grow, blur) #扩张，模糊 | |
| # 合成阴影 | |
| alpha = tensor2pil(shadow_mask).convert('L') | |
| _shadow = chop_image(_canvas, shadow_color, blend_mode, opacity) | |
| _canvas.paste(_shadow, mask=alpha) | |
| # 合成layer | |
| _canvas.paste(_layer, mask=_mask) | |
| ret_images.append(pil2tensor(_canvas)) | |
| log(f"{self.NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish') | |
| return (torch.cat(ret_images, dim=0),) | |
| NODE_CLASS_MAPPINGS = { | |
| "LayerStyle: DropShadow": DropShadow | |
| } | |
| NODE_DISPLAY_NAME_MAPPINGS = { | |
| "LayerStyle: DropShadow": "LayerStyle: DropShadow" | |
| } |