高级图片加载节点，扩充图片节点bug修复
This commit is contained in:
AbyssYuan0
+133
-6
@@ -1,16 +1,19 @@
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import math
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import os
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import hashlib
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import uuid
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from PIL import Image
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from PIL import Image, ImageOps, ImageSequence
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import numpy as np
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import torch
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import comfy.utils
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from .videoCut import getCutList, video_to_frames, cutToDir, frames_to_video
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from .seg import get_masks
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from .line_editor import fill_white_segments, find_largest_white_component
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from .color_editor import get_colors, find_similar_colors, most_common_fuzzy_color, detect_outline
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from .color_editor import get_colors, find_similar_colors, most_common_fuzzy_color, detect_outline,hex_to_rgba
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from .pixel import *
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import gc
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import sys
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import folder_paths
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def getImageSize(IMAGE) -> tuple[int, int]:
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@@ -67,6 +70,86 @@ def garbage_collect():
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torch.cuda.ipc_collect()
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gc.collect()
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class LoadImageAdvanced:
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@classmethod
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def INPUT_TYPES(s):
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input_dir = folder_paths.get_input_directory()
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files = [f for f in os.listdir(input_dir) if os.path.isfile(os.path.join(input_dir, f))]
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return {"required":
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{"image": (sorted(files), {"image_upload": True})},
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"optional":
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{"color": ("STRING", {"default": "#FFFFFF"})}
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}
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CATEGORY = "image"
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RETURN_TYPES = ("IMAGE", "MASK")
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FUNCTION = "load_image"
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def load_image(self, image,color):
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image_path = folder_paths.get_annotated_filepath(image)
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img = Image.open(image_path)
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if color:
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rgba_color = hex_to_rgba(color)
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new_img = Image.new("RGBA",img.size, rgba_color)
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new_img.paste(img, (0, 0), img)
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img = new_img
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output_images = []
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output_masks = []
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for i in ImageSequence.Iterator(img):
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i = ImageOps.exif_transpose(i)
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if i.mode == 'I':
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i = i.point(lambda i: i * (1 / 255))
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image = i.convert("RGB" if color else "RGBA")
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image = np.array(image).astype(np.float32) / 255.0
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image = torch.from_numpy(image)[None,]
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if 'A' in i.getbands():
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mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
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mask = 1. - torch.from_numpy(mask)
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else:
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mask = torch.zeros((64,64), dtype=torch.float32, device="cpu")
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output_images.append(image)
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output_masks.append(mask.unsqueeze(0))
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if len(output_images) > 1:
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output_image = torch.cat(output_images, dim=0)
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output_mask = torch.cat(output_masks, dim=0)
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else:
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output_image = output_images[0]
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output_mask = output_masks[0]
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return (output_image, output_mask)
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@classmethod
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def IS_CHANGED(s, image):
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image_path = folder_paths.get_annotated_filepath(image)
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m = hashlib.sha256()
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with open(image_path, 'rb') as f:
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m.update(f.read())
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return m.digest().hex()
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@classmethod
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def VALIDATE_INPUTS(s, image):
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if not folder_paths.exists_annotated_filepath(image):
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return "Invalid image file: {}".format(image)
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return True
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@classmethod
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def IS_CHANGED(s, image):
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image_path = folder_paths.get_annotated_filepath(image)
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m = hashlib.sha256()
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with open(image_path, 'rb') as f:
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m.update(f.read())
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return m.digest().hex()
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@classmethod
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def VALIDATE_INPUTS(s, image):
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if not folder_paths.exists_annotated_filepath(image):
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return "Invalid image file: {}".format(image)
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return True
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class ImageOverlap:
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@@ -176,6 +259,47 @@ class IntToString:
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def intToString(self, int):
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return (str(int),)
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class IntToStringAdvanced:
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def __init__(self):
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pass
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@classmethod
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def INPUT_TYPES(s):
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return {
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"required": {
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"int": ("INT", {
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"default": 0,
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"min": -sys.maxsize - 1,
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"max": sys.maxsize,
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"step": 1,
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"display": "number"
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}),
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"length": ("INT", {
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"default": 5,
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"min": 0,
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"max": 30,
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"step": 1,
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"display": "number"
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}),
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"prefix":("STRING", {"default": ""}),
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"suffix":("STRING", {"default": ""}),
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},
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}
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RETURN_TYPES = ("STRING",)
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# RETURN_NAMES = ("image_output_name",)
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FUNCTION = "int_to_string"
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# OUTPUT_NODE = False
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CATEGORY = "badger"
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def int_to_string(self, int,length,prefix,suffix):
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return (prefix+str(int).zfill(length)+suffix,)
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class FloatToString:
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@@ -977,21 +1101,22 @@ class ExpandImageWithColor:
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def expand_image_with_color(self, image, top, bottom, left, right, color=None):
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img = tensorToImg(image)
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img = img.convert("RGBA")
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img = img.convert("RGBA") # 确保图片是RGBA模式
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# Determine the new size of the image
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new_width = img.width + left + right
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new_height = img.height + top + bottom
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# Create a new image with the new size and the given background color
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# 如果提供了颜色，并且是十六进制形式，转换为RGBA格式
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if color:
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new_img = Image.new("RGBA", (new_width, new_height), color)
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rgba_color = hex_to_rgba(color)
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new_img = Image.new("RGBA", (new_width, new_height), rgba_color)
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else:
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# Use transparency if no color was provided
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new_img = Image.new("RGBA", (new_width, new_height), (0, 0, 0, 0))
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# Paste the original image onto the new image
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new_img.paste(img, (left, top), img)
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result = imgToTensor(new_img)
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garbage_collect()
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return (result,)
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@@ -1290,6 +1415,8 @@ NODE_CLASS_MAPPINGS = {
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"ImageOverlap-badger": ImageOverlap,
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"FloatToInt-badger": FloatToInt,
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"IntToString-badger": IntToString,
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"LoadImageAdvanced-badger": LoadImageAdvanced,
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"IntToStringAdvanced-badger":IntToStringAdvanced,
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"FloatToString-badger": FloatToString,
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"ImageNormalization-badger": ImageNormalization,
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"ImageScaleToSide-badger": ImageScaleToSide,
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@@ -11,6 +11,15 @@ def hex_to_rgb(hex_color):
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hex_color = hex_color.lstrip('#')
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return tuple(int(hex_color[i:i + 2], 16) for i in (0, 2, 4))
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def hex_to_rgba(hex_color, alpha=255):
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"""
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将十六进制颜色字符串转换为RGBA格式。
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默认透明度（alpha）为255（不透明）。
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"""
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hex_color = hex_color.lstrip('#')
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lv = len(hex_color)
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return tuple(int(hex_color[i:i + lv // 3], 16) for i in range(0, lv, lv // 3)) + (alpha,)
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def get_colors(PIL_img, n):
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color_list = []
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