234 lines
10 KiB
Python
234 lines
10 KiB
Python
import cv2
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import numpy as np
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from PIL import Image, ImageFilter, ImageChops, ImageEnhance
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import node_helpers
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import torch
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def pil2tensor(image: Image) -> torch.Tensor:
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return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
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def tensor2pil(t_image: torch.Tensor) -> Image:
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return Image.fromarray(np.clip(255.0 * t_image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
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class TTP_Expand_And_Mask:
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"""
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这是一个节点类，用于将输入图片在指定方向扩展一定数量的块并创建相应蒙版。
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功能：
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1. 支持同时在多个方向上扩展图像。
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2. 分别控制每个方向的扩展块数量。
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3. 将输入图像的透明通道（Alpha 通道）信息转换为蒙版，并与新创建的蒙版合并。
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4. 添加一个布尔参数 fill_alpha_decision 来决定是否将输出图片中的透明区域填充为白色，并输出 RGB 图像。
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"""
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def __init__(self, *args, **kwargs):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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directions = ["left", "right", "top", "bottom"]
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return {
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"required": {
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"image": ("IMAGE",), # 输入一张图片
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"fill_mode": (["duplicate", "white"], {"default": "duplicate", "label": "Fill Mode"}),
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# fill_mode是一个字符串列表参数，可以选择"duplicate"或"white"
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"fill_alpha_decision": ("BOOLEAN", {"default": False, "label": "Fill Alpha with White"}),
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# fill_alpha_decision为一个布尔值参数，用来决定是否将输出图像透明区域填充为白色
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},
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"optional": {
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**{f"expand_{dir}": ("BOOLEAN", {"default": False, "label": f"Expand {dir.capitalize()}"}) for dir in directions},
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**{f"num_blocks_{dir}": ("INT", {"default": 1, "min": 0, "max": 3, "step": 1, "label": f"Blocks {dir.capitalize()}"}) for dir in directions},
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}
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}
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RETURN_TYPES = ("IMAGE", "MASK")
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RETURN_NAMES = ("EXPANDED_IMAGE", "MASK")
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FUNCTION = "expand_and_mask"
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CATEGORY = "TTP/Image"
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def expand_and_mask(self, image, fill_mode="duplicate", fill_alpha_decision=False, **kwargs):
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pil_image = tensor2pil(image)
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orig_width, orig_height = pil_image.size
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has_alpha = (pil_image.mode == 'RGBA')
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# 解析方向和块数
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directions = ["left", "right", "top", "bottom"]
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expand_directions = {dir: kwargs.get(f"expand_{dir}", False) for dir in directions}
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num_blocks = {dir: kwargs.get(f"num_blocks_{dir}", 0) if expand_directions[dir] else 0 for dir in directions}
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# 计算扩展后的尺寸
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total_width = orig_width + orig_width * (num_blocks["left"] + num_blocks["right"])
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total_height = orig_height + orig_height * (num_blocks["top"] + num_blocks["bottom"])
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# 创建扩展后的图像
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expanded_image_mode = pil_image.mode
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expanded_image = Image.new(expanded_image_mode, (total_width, total_height))
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# 根据 fill_mode 创建填充图像
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def create_fill_image():
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if pil_image.mode == 'RGBA':
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return Image.new("RGBA", (orig_width, orig_height), color=(255, 255, 255, 255))
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elif pil_image.mode == 'RGB':
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return Image.new("RGB", (orig_width, orig_height), color=(255, 255, 255))
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elif pil_image.mode == 'L':
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return Image.new("L", (orig_width, orig_height), color=255)
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else:
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raise ValueError(f"Unsupported image mode for fill: {pil_image.mode}")
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if fill_mode == "duplicate":
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fill_image = pil_image.copy()
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elif fill_mode == "white":
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fill_image = create_fill_image()
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else:
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fill_image = pil_image.copy()
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# 计算原图在扩展图像中的位置
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left_offset = orig_width * num_blocks["left"]
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top_offset = orig_height * num_blocks["top"]
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# 粘贴原始图像
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expanded_image.paste(pil_image, (left_offset, top_offset))
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# 粘贴填充区域
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for dir in directions:
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blocks = num_blocks[dir]
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for i in range(blocks):
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if dir == "left":
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x = left_offset - orig_width * (i + 1)
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y = top_offset
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elif dir == "right":
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x = left_offset + orig_width * (i + 1)
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y = top_offset
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elif dir == "top":
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x = left_offset
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y = top_offset - orig_height * (i + 1)
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elif dir == "bottom":
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x = left_offset
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y = top_offset + orig_height * (i + 1)
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else:
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continue
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expanded_image.paste(fill_image, (x, y))
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# 粘贴角落填充区域（处理同时选择多个方向的情况）
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corner_positions = []
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if expand_directions["left"] and expand_directions["top"]:
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for i in range(num_blocks["left"]):
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for j in range(num_blocks["top"]):
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x = left_offset - orig_width * (i + 1)
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y = top_offset - orig_height * (j + 1)
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corner_positions.append((x, y))
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if expand_directions["left"] and expand_directions["bottom"]:
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for i in range(num_blocks["left"]):
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for j in range(num_blocks["bottom"]):
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x = left_offset - orig_width * (i + 1)
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y = top_offset + orig_height * (j + 1)
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corner_positions.append((x, y))
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if expand_directions["right"] and expand_directions["top"]:
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for i in range(num_blocks["right"]):
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for j in range(num_blocks["top"]):
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x = left_offset + orig_width * (i + 1)
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y = top_offset - orig_height * (j + 1)
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corner_positions.append((x, y))
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if expand_directions["right"] and expand_directions["bottom"]:
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for i in range(num_blocks["right"]):
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for j in range(num_blocks["bottom"]):
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x = left_offset + orig_width * (i + 1)
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y = top_offset + orig_height * (j + 1)
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corner_positions.append((x, y))
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for pos in corner_positions:
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expanded_image.paste(fill_image, pos)
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# 创建蒙版
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mask_array = np.zeros((total_height, total_width), dtype=np.float32)
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# 原始图像区域蒙版处理
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if has_alpha:
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alpha_array = np.array(pil_image.getchannel("A"), dtype=np.float32) / 255.0
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alpha_mask_array = 1.0 - alpha_array
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mask_array[top_offset:top_offset + orig_height, left_offset:left_offset + orig_width] = alpha_mask_array
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# 填充区域蒙版设置为1.0
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# 左右扩展区域
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for dir in ["left", "right"]:
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blocks = num_blocks[dir]
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for i in range(blocks):
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if dir == "left":
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x_start = left_offset - orig_width * (i + 1)
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x_end = left_offset - orig_width * i
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elif dir == "right":
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x_start = left_offset + orig_width * (i + 1)
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x_end = left_offset + orig_width * (i + 2)
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else:
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continue
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mask_array[top_offset:top_offset + orig_height, x_start:x_end] = 1.0
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# 上下扩展区域
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for dir in ["top", "bottom"]:
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blocks = num_blocks[dir]
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for i in range(blocks):
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if dir == "top":
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y_start = top_offset - orig_height * (i + 1)
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y_end = top_offset - orig_height * i
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elif dir == "bottom":
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y_start = top_offset + orig_height * (i + 1)
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y_end = top_offset + orig_height * (i + 2)
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else:
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continue
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mask_array[y_start:y_end, left_offset:left_offset + orig_width] = 1.0
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# 角落区域蒙版设置为1.0
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for pos in corner_positions:
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x, y = pos
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mask_array[y:y + orig_height, x:x + orig_width] = 1.0
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# 创建蒙版张量 (1, 1, height, width)
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mask_tensor = torch.from_numpy(mask_array).unsqueeze(0).unsqueeze(0)
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# 根据 fill_alpha_decision 参数决定是否将输出图像中的透明区域填充为白色
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if fill_alpha_decision and has_alpha:
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expanded_image = expanded_image.convert('RGBA') # 确保图像是RGBA模式
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background = Image.new('RGBA', expanded_image.size, (255, 255, 255, 255))
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expanded_image = Image.alpha_composite(background, expanded_image)
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expanded_image = expanded_image.convert('RGB') # 转换为RGB模式
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expanded_image_mode = 'RGB'
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expanded_image_tensor = pil2tensor(expanded_image)
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return (expanded_image_tensor, mask_tensor)
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class TTP_text_mix:
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def __init__(self, *args, **kwargs):
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pass
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"text1": ("STRING", {"default": "", "multiline": True, "label": "Text Box 1"}),
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"text2": ("STRING", {"default": "", "multiline": True, "label": "Text Box 2"}),
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"text3": ("STRING", {"default": "", "multiline": True, "label": "Text Box 3"}),
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"template": ("STRING", {"default": "", "multiline": True, "label": "Template Text Box"}),
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}
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}
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RETURN_TYPES = ("STRING", "STRING", "STRING", "STRING")
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RETURN_NAMES = ("text1", "text2", "text3", "final_text")
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FUNCTION = "mix_texts"
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CATEGORY = "TTP/text"
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def mix_texts(self, text1, text2, text3, template):
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# 使用replace方法替换模板中的占位符{text1}和{text2}
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final_text = template.replace("{text1}", text1).replace("{text2}", text2).replace("{text3}", text3)
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return (text1, text2, text3, final_text)
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NODE_CLASS_MAPPINGS = {
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"TTP_Expand_And_Mask": TTP_Expand_And_Mask,
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"TTP_text_mix": TTP_text_mix
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}
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NODE_DISPLAY_NAME_MAPPINGS = {
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"TTP_Expand_And_Mask": "TTP_Expand_And_Mask",
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"TTP_text_mix": "TTP_text_mix"
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}
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