add some nodes for batch
This commit is contained in:
刘雪峰
@@ -65,7 +65,14 @@ Tips: base64格式字符串比较长，会导致界面卡顿，接口请求带
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| ForEachClose | 循环结束节点 |
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| LoadJsonStrToList | json字符串转换为对象列表 |
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| GetValueFromJsonObj | 从对象中获取指定key的值 |
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| FilterValueForList | 根据指定值过滤列表中元素 ||
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| FilterValueForList | 根据指定值过滤列表中元素 |
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| SliceList | 列表切片 |
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| LoadLocalFilePath | 列出给定路径下的文件列表 |
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| LoadImageFromLocalPath | 根据图片全路径加载图片 |
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| LoadMaskFromLocalPath | 根据遮罩全路径加载遮罩 | |
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| IsNoneOrEmpty | 判断是否为空或空字符串或空列表或空字典 |
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| IsNoneOrEmptyOptional | 为空时返回指定值(惰性求值)，否则返回原值 |
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| EmptyOutputNode | 空的输出类型节点 |
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### 示例
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@@ -76,6 +83,9 @@ Tips: base64格式字符串比较长，会导致界面卡顿，接口请求带
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## 更新记录
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### 2024-10-18
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- 新增节点：SliceList、LoadLocalFilePath、LoadImageFromLocalPath、LoadMaskFromLocalPath、IsNoneOrEmpty、IsNoneOrEmptyOptional、EmptyOutputNode
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### 2024-09-29
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- 新增节点：FilterValueForList
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+111
-1
@@ -1,9 +1,13 @@
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import base64
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import copy
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import io
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import os
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import numpy as np
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import torch
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from PIL import ImageOps, Image
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from PIL import ImageOps, Image, ImageSequence
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import node_helpers
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from nodes import LoadImage
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from comfy.cli_args import args
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from PIL.PngImagePlugin import PngInfo
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@@ -340,6 +344,108 @@ class LoadImageToBase64(LoadImage):
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return encoded_image, img, mask
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class LoadImageFromLocalPath:
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@classmethod
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def INPUT_TYPES(s):
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return {"required":
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{
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"image_path": ("STRING", {"default": ""},)
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},
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}
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CATEGORY = "EasyApi/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_path):
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img = node_helpers.pillow(Image.open, image_path)
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output_images = []
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output_masks = []
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w, h = None, None
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excluded_formats = ['MPO']
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# 遍历图像的每一帧
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for i in ImageSequence.Iterator(img):
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# 旋转图像
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i = node_helpers.pillow(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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# 将图像转换为RGB格式
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image = i.convert("RGB")
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if len(output_images) == 0:
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w = image.size[0]
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h = image.size[1]
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if image.size[0] != w or image.size[1] != h:
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continue
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# 将图像转换为浮点数组 (H,W,Channel)
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image = np.array(image).astype(np.float32) / 255.0
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# 先把图片转成3维张量，并再在最前面添加一个维度，变成4维(1, H, W,Channel)
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image = torch.from_numpy(image)[None,]
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# 如果图像包含alpha通道，则将其转换为掩码
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if 'A' in i.getbands():
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# 计算后结果数组中透明像素会是0
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mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0
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# 把数组中透明像素设为1
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mask = 1. - torch.from_numpy(mask)
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else:
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# 否则，创建一个64x64的零张量作为掩码
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mask = torch.zeros((64, 64,), dtype=torch.float32, device="cpu")
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# 将图像和掩码添加到输出列表中
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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 and img.format not in excluded_formats:
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# 如果有多个图像，则将它们按维度0拼接在一起
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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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# 否则，返回单个图像和掩码
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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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# 返回输出图像和掩码
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return (output_image, output_mask)
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class LoadMaskFromLocalPath:
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_color_channels = ["alpha", "red", "green", "blue"]
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@classmethod
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def INPUT_TYPES(s):
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return {"required":
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{
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"image_path": ("STRING", {"default": ""}),
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"channel": (s._color_channels, ),
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}
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}
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CATEGORY = "EasyApi/Image"
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RETURN_TYPES = ("MASK",)
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FUNCTION = "load_mask"
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def load_mask(self, image_path, channel):
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i = node_helpers.pillow(Image.open, image_path)
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i = node_helpers.pillow(ImageOps.exif_transpose, i)
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if i.getbands() != ("R", "G", "B", "A"):
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if i.mode == 'I':
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i = i.point(lambda i: i * (1 / 255))
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i = i.convert("RGBA")
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mask = None
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c = channel[0].upper()
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if c in i.getbands():
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mask = np.array(i.getchannel(c)).astype(np.float32) / 255.0
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mask = torch.from_numpy(mask)
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if c == 'A':
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mask = 1. - mask
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else:
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mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu")
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return (mask.unsqueeze(0),)
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NODE_CLASS_MAPPINGS = {
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"Base64ToImage": Base64ToImage,
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"LoadImageFromURL": LoadImageFromURL,
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@@ -351,6 +457,8 @@ NODE_CLASS_MAPPINGS = {
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"MaskToBase64Image": MaskToBase64Image,
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"MaskImageToBase64": MaskImageToBase64,
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"LoadImageToBase64": LoadImageToBase64,
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"LoadImageFromLocalPath": LoadImageFromLocalPath,
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"LoadMaskFromLocalPath": LoadMaskFromLocalPath,
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}
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# A dictionary that contains the friendly/humanly readable titles for the nodes
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@@ -365,4 +473,6 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"MaskToBase64Image": "Mask To Base64 Image",
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"MaskImageToBase64": "Mask Image To Base64",
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"LoadImageToBase64": "Load Image To Base64",
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"LoadImageFromLocalPath": "Load Image From Local Path",
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"LoadMaskFromLocalPath": "Load Mask From Local Path",
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}
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+210
-3
@@ -1,6 +1,10 @@
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import mimetypes
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import os
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import simplejson
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import torch
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import folder_paths
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from comfy.model_patcher import ModelPatcher
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import comfy.model_base
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from .util import tensor_to_pil, hex_to_rgba, any_type
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@@ -136,6 +140,9 @@ class SplitStringToList:
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"str": ('STRING', {"forceInput": True}),
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"to_type": (["str", "int", "float", "bool"], {"default": "str"}),
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"delimiter": ('STRING', {"default": ","}),
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},
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"optional": {
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"method": (["delimiter", "LF", "tab"], {"default": "delimiter", "tooltip": "分隔符选取方式"}),
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}
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}
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@@ -147,7 +154,11 @@ class SplitStringToList:
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CATEGORY = "EasyApi/String"
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DESCRIPTION = "按分隔符把字符串拆分成列表。如 \"a,b,c\" => [a,b,c]"
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def convert(self, str, to_type, delimiter):
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def convert(self, str, to_type, delimiter, method="delimiter"):
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if method == "LF":
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delimiter = "\n"
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elif method == "tab":
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delimiter = "\t"
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result = [item.strip() for item in str.split(delimiter)]
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if to_type == "int":
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result = [int(x) for x in result]
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@@ -458,7 +469,7 @@ class IndexOfList:
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return {
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"required": {
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"lst": (any_type, {}),
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"index": ('INT', {'default': 0, 'step': 1, 'min': 0, 'max': 50}),
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"index": ('INT', {'default': 0, 'step': 1, 'min': 0, 'max': 100000}),
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}
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}
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@@ -469,7 +480,7 @@ class IndexOfList:
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CATEGORY = "EasyApi/List"
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DESCRIPTION = "根据索引过滤"
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DESCRIPTION = "根据索引过滤，若index >= len(lst)，返回None"
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def execute(self, lst, index):
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if isinstance(lst, list) and len(lst) > index:
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@@ -504,6 +515,37 @@ class IndexesOfList:
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return (None, )
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class SliceList:
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@classmethod
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def INPUT_TYPES(self):
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return {
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"required": {
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"lst": (any_type, {}),
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"start_index": ('INT', {'default': 0, 'step': 1, 'min': -100000, 'max': 100000}),
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"step": ('INT', {'default': 1, 'step': 1, 'min': -100000, 'max': 100000}),
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"end_index": ('INT', {'default': 100000, 'step': 1, 'min': -100000, 'max': 100000}),
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"reverse": ('BOOLEAN', {'default': False}),
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}
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}
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RETURN_TYPES = (any_type,)
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RETURN_NAMES = ("lst",)
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FUNCTION = "execute"
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CATEGORY = "EasyApi/List"
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DESCRIPTION = "列表切片, lst入参不是list时，返回None"
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def execute(self, lst, start_index, step, end_index, reverse):
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if isinstance(lst, list):
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sliceList = lst[start_index:end_index:step]
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if reverse:
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sliceList.reverse()
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return (sliceList, )
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return (None, )
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class StringArea:
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@classmethod
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def INPUT_TYPES(s):
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@@ -625,6 +667,161 @@ class FilterValueForList:
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return (filtered,)
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class LoadLocalFilePath:
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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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"directory": ("STRING", {"default": "", "tooltip": "若为空，遍历input目录"}),
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"max_depth": ("INT", {"default": 1, "min": 1, "max": 64, "step": 1, "tooltip": "查找最大目录层级"}),
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"file_type": (["image", "video", "text"], {"default": "image", "tooltip": "file_suffix值不为空时，此配置失效"}),
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"file_suffix": ("STRING", {"default": "", "tooltip": "指定过滤文件后缀，多个以|分割，如.png|.jpg"}),
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}
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}
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RETURN_TYPES = ("LIST", "INT",)
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RETURN_NAMES = ("paths", "count",)
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OUTPUT_TOOLTIPS = ("文件路径列表，若过滤不到文件返回空列表", "文件个数",)
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FUNCTION = "get_paths"
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CATEGORY = "EasyApi/Utils"
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DESCRIPTION = "根据条件遍历指定目录下文件路径"
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mime_types_dict = {
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'image': {'image/jpeg', 'image/png', 'image/gif', 'image/bmp', 'image/tiff'},
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'video': {'video/mp4', 'video/quicktime', 'video/x-msvideo', 'video/x-matroska'},
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'text': {'text/plain', 'text/html', 'text/css', 'text/csv'}
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}
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@classmethod
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def recursive_file_paths(cls, directory, max_depth, file_type, file_suffix, current_depth=1):
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"""
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获取指定目录及其子目录中的图片文件路径（深度优先遍历）
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参数:
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directory (str): 要遍历的目录路径
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max_depth (int): 最大遍历层级
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current_depth (int): 当前遍历层级（默认值为1）
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返回:
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List[str]: 图片文件路径列表
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"""
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image_paths = []
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if current_depth > max_depth:
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return image_paths
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with os.scandir(directory) as it:
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for item in it:
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if item.is_file():
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if len(file_suffix.strip()) > 0:
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suffixes = [s.strip().lower() for s in file_suffix.split('|')]
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if any(item.name.lower().endswith(suffix) for suffix in suffixes):
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image_paths.append(item.path)
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elif file_type:
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mime_type, _ = mimetypes.guess_type(item.path)
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if mime_type in cls.mime_types_dict.get(file_type, set()):
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image_paths.append(item.path)
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elif item.is_dir():
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image_paths.extend(cls.recursive_file_paths(item.path, max_depth, file_type, file_suffix, current_depth + 1))
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return image_paths
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def get_paths(self, directory, max_depth, file_type, file_suffix):
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if directory is None or len(directory.strip()) == 0:
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directory = folder_paths.get_input_directory()
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image_paths = self.recursive_file_paths(directory, max_depth, file_type, file_suffix)
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return image_paths, len(image_paths),
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class IsNoneOrEmpty:
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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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"any": (any_type,)
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}
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}
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RETURN_TYPES = ("BOOLEAN",)
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RETURN_NAMES = ("boolean",)
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FUNCTION = "execute"
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CATEGORY = "EasyApi/Utils"
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DESCRIPTION = "判断输入是否为None、空列表、空字符串(trim后判断)、空字典"
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def execute(self, any):
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if any is None:
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return True,
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if isinstance(any, list):
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return (True if len(any) == 0 else False,)
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if isinstance(any, str):
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return (True if len(any.strip()) == 0 else False,)
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if isinstance(any, dict):
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return (True if len(any) == 0 else False,)
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return False
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class IsNoneOrEmptyOptional:
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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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"any": (any_type,)
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},
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"optional": {
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"default": (any_type, {"lazy": True})
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}
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}
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RETURN_TYPES = (any_type,)
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RETURN_NAMES = ("any",)
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FUNCTION = "execute"
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CATEGORY = "EasyApi/Utils"
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DESCRIPTION = "判断输入any是否为None、空列表、空字符串(trim后判断)、空字典，若为true，返回default的值，否则返回输入值"
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def execute(self, any, default=None):
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if any is None:
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return default,
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if isinstance(any, list):
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return (default if len(any) == 0 else any,)
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if isinstance(any, str):
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return (default if len(any.strip()) == 0 else any,)
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if isinstance(any, dict):
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return (default if len(any) == 0 else any,)
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return (any,)
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def check_lazy_status(self, any, default=None):
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if any is None:
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return ["default"]
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if isinstance(any, list):
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return ["default"] if len(any) == 0 else ["any"]
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if isinstance(any, str):
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return ["default"] if len(any.strip()) == 0 else ["any"]
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if isinstance(any, dict):
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return ["default"] if len(any) == 0 else ["any"]
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return ["any"]
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class EmptyOutputNode:
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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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"any": (any_type,)
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}
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}
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RETURN_TYPES = ()
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FUNCTION = "execute"
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CATEGORY = "EasyApi/Utils"
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DESCRIPTION = "可配合for循环批量处理图片，for循环后连接此输出节点"
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OUTPUT_NODE = True
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def execute(self, any):
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return ()
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NODE_CLASS_MAPPINGS = {
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"GetImageBatchSize": GetImageBatchSize,
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"JoinList": JoinList,
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@@ -645,11 +842,16 @@ NODE_CLASS_MAPPINGS = {
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"SplitStringToList": SplitStringToList,
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"IndexOfList": IndexOfList,
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"IndexesOfList": IndexesOfList,
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"SliceList": SliceList,
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"StringArea": StringArea,
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"ConvertTypeToAny": ConvertTypeToAny,
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"GetValueFromJsonObj": GetValueFromJsonObj,
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"LoadJsonStrToList": LoadJsonStrToList,
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"FilterValueForList": FilterValueForList,
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"LoadLocalFilePath": LoadLocalFilePath,
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"IsNoneOrEmpty": IsNoneOrEmpty,
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"IsNoneOrEmptyOptional": IsNoneOrEmptyOptional,
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"EmptyOutputNode": EmptyOutputNode,
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}
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# A dictionary that contains the friendly/humanly readable titles for the nodes
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@@ -673,9 +875,14 @@ NODE_DISPLAY_NAME_MAPPINGS = {
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"SplitStringToList": "SplitStringToList",
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"IndexOfList": "IndexOfList",
|
||||
"IndexesOfList": "IndexesOfList",
|
||||
"SliceList": "SliceList",
|
||||
"StringArea": "StringArea",
|
||||
"ConvertTypeToAny": "ConvertTypeToAny",
|
||||
"GetValueFromJsonObj": "GetValueFromJsonObj",
|
||||
"LoadJsonStrToList": "LoadJsonStrToList",
|
||||
"FilterValueForList": "FilterValueForList",
|
||||
"LoadLocalFilePath": "LoadLocalFilePath",
|
||||
"IsNoneOrEmpty": "IsNoneOrEmpty",
|
||||
"IsNoneOrEmptyOptional": "IsNoneOrEmptyOptional",
|
||||
"EmptyOutputNode": "EmptyOutputNode",
|
||||
}
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
[project]
|
||||
name = "comfyui-easyapi-nodes"
|
||||
description = "Provides some features and nodes related to API calls."
|
||||
version = "1.0.5"
|
||||
version = "1.0.6"
|
||||
license = { file = "LICENSE" }
|
||||
dependencies = ["segment_anything", "simple_lama_inpainting", "insightface"]
|
||||
|
||||
|
||||
Reference in New Issue
Block a user