diff --git a/py/drop_shadow_v3.py b/py/drop_shadow_v3.py new file mode 100644 index 0000000..b84ee39 --- /dev/null +++ b/py/drop_shadow_v3.py @@ -0,0 +1,112 @@ +from PIL import Image +from .imagefunc import * + +NODE_NAME = 'DropShadowV3' + +class DropShadowV3: + + def __init__(self): + pass + + @classmethod + def INPUT_TYPES(self): + + return { + "required": { + "layer_image": ("IMAGE",), # + "invert_mask": ("BOOLEAN", {"default": True}), # 反转mask + "blend_mode": (chop_mode_v2,), # 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": 1000, "step": 1}), # 模糊 + "shadow_color": ("STRING", {"default": "#000000"}), # 背景颜色 + }, + "optional": { + "background_image": ("IMAGE", ), # + "layer_mask": ("MASK",), # + } + } + + RETURN_TYPES = ("IMAGE",) + RETURN_NAMES = ("image",) + FUNCTION = 'drop_shadow_v2' + CATEGORY = '😺dzNodes/LayerStyle' + + def drop_shadow_v2(self, layer_image, invert_mask, blend_mode, opacity, + distance_x, distance_y, grow, blur, shadow_color, + background_image=None, layer_mask=None + ): + + # If background image is empty, create transparent background image for each layer image + if background_image == None: + background_image = [] + for l in layer_image: + m = tensor2pil(l) + background_image.append(pil2tensor(Image.new('RGBA', (m.width, m.height), (0, 0, 0, 0)))) + + 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: {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("RGBA", 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('RGBA') + _layer = tensor2pil(layer_image) + + if _mask.size != _layer.size: + _mask = Image.new('L', _layer.size, 'white') + log(f"Warning: {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_v2(_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"{NODE_NAME} Processed {len(ret_images)} image(s).", message_type='finish') + return (torch.cat(ret_images, dim=0),) + + +NODE_CLASS_MAPPINGS = { + "LayerStyle: DropShadow V3": DropShadowV3 +} + +NODE_DISPLAY_NAME_MAPPINGS = { + "LayerStyle: DropShadow V3": "LayerStyle: DropShadow V3" +} \ No newline at end of file diff --git a/py/image_blend_advance_v3.py b/py/image_blend_advance_v3.py new file mode 100644 index 0000000..0212e8c --- /dev/null +++ b/py/image_blend_advance_v3.py @@ -0,0 +1,137 @@ +from .imagefunc import * + +NODE_NAME = 'ImageBlendAdvanceV3' + +class ImageBlendAdvanceV3: + + def __init__(self): + pass + + @classmethod + def INPUT_TYPES(self): + + mirror_mode = ['None', 'horizontal', 'vertical'] + method_mode = ['lanczos', 'bicubic', 'hamming', 'bilinear', 'box', 'nearest'] + return { + "required": { + "layer_image": ("IMAGE",), # + "invert_mask": ("BOOLEAN", {"default": True}), # 反转mask + "blend_mode": (chop_mode_v2,), # 混合模式 + "opacity": ("INT", {"default": 100, "min": 0, "max": 100, "step": 1}), # 透明度 + "x_percent": ("FLOAT", {"default": 50, "min": -999, "max": 999, "step": 0.01}), + "y_percent": ("FLOAT", {"default": 50, "min": -999, "max": 999, "step": 0.01}), + "mirror": (mirror_mode,), # 镜像翻转 + "scale": ("FLOAT", {"default": 1, "min": 0.01, "max": 100, "step": 0.01}), + "aspect_ratio": ("FLOAT", {"default": 1, "min": 0.01, "max": 100, "step": 0.01}), + "rotate": ("FLOAT", {"default": 0, "min": -999999, "max": 999999, "step": 0.01}), + "transform_method": (method_mode,), + "anti_aliasing": ("INT", {"default": 0, "min": 0, "max": 16, "step": 1}), + }, + "optional": { + "background_image": ("IMAGE", ), # + "layer_mask": ("MASK",), # + } + } + + RETURN_TYPES = ("IMAGE", "MASK") + RETURN_NAMES = ("image", "mask") + FUNCTION = 'image_blend_advance_v2' + CATEGORY = '😺dzNodes/LayerUtility' + + def image_blend_advance_v2(self, layer_image, invert_mask, blend_mode, opacity, + x_percent, y_percent, mirror, scale, aspect_ratio, rotate, + transform_method, anti_aliasing, background_image=None, layer_mask=None + ): + + # If background image is empty, create transparent background image for each layer image + if background_image == None: + background_image = [] + for l in layer_image: + m = tensor2pil(l) + background_image.append(pil2tensor(Image.new('RGBA', (m.width, m.height), (0, 0, 0, 0)))) + + 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 layer_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', m.size, 'white')) + 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')) + + 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] + 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('RGBA') + _layer = tensor2pil(layer_image) + + if _mask.size != _layer.size: + _mask = Image.new('L', _layer.size, 'white') + log(f"Warning: {NODE_NAME} mask mismatch, dropped!", message_type='warning') + + orig_layer_width = _layer.width + orig_layer_height = _layer.height + _mask = _mask.convert("RGBA") + + target_layer_width = int(orig_layer_width * scale) + target_layer_height = int(orig_layer_height * scale * aspect_ratio) + + # mirror + if mirror == 'horizontal': + _layer = _layer.transpose(Image.FLIP_LEFT_RIGHT) + _mask = _mask.transpose(Image.FLIP_LEFT_RIGHT) + elif mirror == 'vertical': + _layer = _layer.transpose(Image.FLIP_TOP_BOTTOM) + _mask = _mask.transpose(Image.FLIP_TOP_BOTTOM) + + # scale + _layer = _layer.resize((target_layer_width, target_layer_height)) + _mask = _mask.resize((target_layer_width, target_layer_height)) + # rotate + _layer, _mask, _ = image_rotate_extend_with_alpha(_layer, rotate, _mask, transform_method, anti_aliasing) + + # 处理位置 + x = int(_canvas.width * x_percent / 100 - _layer.width / 2) + y = int(_canvas.height * y_percent / 100 - _layer.height / 2) + + # composit layer + _comp = copy.copy(_canvas) + _compmask = Image.new("RGBA", _comp.size, color='black') + _comp.paste(_layer, (x, y)) + _compmask.paste(_mask, (x, y)) + _compmask = _compmask.convert('L') + _comp = chop_image_v2(_canvas, _comp, blend_mode, opacity) + + # composition background + _canvas.paste(_comp, mask=_compmask) + + ret_images.append(pil2tensor(_canvas)) + ret_masks.append(image2mask(_compmask)) + + log(f"{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: ImageBlendAdvance V3": ImageBlendAdvanceV3 +} + +NODE_DISPLAY_NAME_MAPPINGS = { + "LayerUtility: ImageBlendAdvance V3": "LayerUtility: ImageBlendAdvance V3" +} \ No newline at end of file