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Author SHA1 Message Date
shadowcz007 a363713ae0 v0.13.0
EmbeddingPrompt & 修复若干bug
2024-01-16 23:17:56 +08:00
shadowcz007 1566165bd4 Create space.txt 2024-01-16 17:50:51 +08:00
shadowcz007 fe065fa318 OutlineMask for inpaint 2024-01-16 10:54:26 +08:00
shadowcz007 202d5cf071 支持富文本定义跳转按钮 2024-01-15 14:21:39 +08:00
shadowcz007 b785a9dc5b add EmbeddingPrompt 2024-01-15 13:02:26 +08:00
shadowcz007 73bc658b2f 修复 sentencepiece 未安装的bug 2024-01-15 08:40:07 +08:00
shadowcz007 0b94216138 Update ui_mixlab.js 2024-01-14 20:35:27 +08:00
shadowcz007 86eec2b4cc Update ui_mixlab.js 2024-01-14 20:34:07 +08:00
shadowcz007 c99b531d28 Update ui_mixlab.js 2024-01-14 20:33:53 +08:00
shadowcz007 74a4338cb5 Merge branch 'main' of https://github.com/shadowcz007/comfyui-mixlab-nodes 2024-01-14 13:14:42 +08:00
shadowcz007 d691c52e49 Update TextGenerateNode.py 2024-01-14 13:12:10 +08:00
gold3bear bd3e9e4b3c 去掉调试数据 2024-01-14 12:31:05 +08:00
shadow 3c3ca5fb9c Merge pull request #138 from shadowcz007/fix-chinese-prompt
Fix chinese prompt
2024-01-14 11:58:08 +08:00
shadowcz007 e4ff4fce1c update 2024-01-14 11:57:18 +08:00
shadowcz007 4ccda20975 add rembg 2024-01-14 11:06:46 +08:00
12 changed files with 496 additions and 93 deletions
+3
View File
@@ -164,6 +164,9 @@ An improvement has been made to directly redirect to GitHub to search for missin
### Models
[Download rembg Models](https://github.com/danielgatis/rembg/tree/main#Models),move to:models/rembg
[Download CLIPSeg](https://huggingface.co/CIDAS/clipseg-rd64-refined/tree/main), move to : models/clipseg
[Download lama](https://github.com/enesmsahin/simple-lama-inpainting/releases/download/v0.1.0/big-lama.pt), move to : models/lama
+20 -10
View File
@@ -534,7 +534,7 @@ PromptServer.add_routes=new_add_routes
# 导入节点
from .nodes.PromptNode import RandomPrompt,PromptSlide,PromptSimplification,PromptImage
from .nodes.PromptNode import EmbeddingPrompt,RandomPrompt,PromptSlide,PromptSimplification,PromptImage
from .nodes.ImageNode import GetImageSize_,MirroredImage,ImageColorTransfer,NoiseImage,TransparentImage,GradientImage,LoadImagesFromPath,LoadImagesFromURL,ResizeImage,TextImage,SvgImage,Image3D,ShowLayer,NewLayer,MergeLayers,AreaToMask,SmoothMask,FeatheredMask,SplitLongMask,ImageCropByAlpha,EnhanceImage,FaceToMask
from .nodes.Vae import VAELoader,VAEDecode
from .nodes.ScreenShareNode import ScreenShareNode,FloatingVideo
@@ -542,7 +542,7 @@ from .nodes.Clipseg import CLIPSeg,CombineMasks
from .nodes.ChatGPT import ChatGPTNode,ShowTextForGPT,CharacterInText
from .nodes.Audio import GamePal,SpeechRecognition,SpeechSynthesis
from .nodes.Utils import TESTNODE_,AppInfo,IntNumber,FloatSlider,TextInput,ColorInput,FontInput,TextToNumber,DynamicDelayProcessor,LimitNumber,SwitchByIndex,MultiplicationNode
from .nodes.Mask import OutlineMask
# 要导出的所有节点及其名称的字典
@@ -551,6 +551,7 @@ NODE_CLASS_MAPPINGS = {
"AppInfo":AppInfo,
"TESTNODE_":TESTNODE_,
"RandomPrompt":RandomPrompt,
"EmbeddingPrompt":EmbeddingPrompt,
"PromptSlide":PromptSlide,
"PromptSimplification":PromptSimplification,
"PromptImage":PromptImage,
@@ -597,6 +598,7 @@ NODE_CLASS_MAPPINGS = {
"GetImageSize_":GetImageSize_,
"SwitchByIndex":SwitchByIndex,
"LimitNumber":LimitNumber,
"OutlineMask":OutlineMask
# "LaMaInpainting":LaMaInpainting
# "GamePal":GamePal
}
@@ -622,7 +624,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"PromptSlide":"PromptSlide ♾️Mixlab",
"PromptGenerate_Mix":"PromptGenerate ♾️Mixlab",
"ChinesePrompt_Mix":"ChinesePrompt ♾️Mixlab",
"GamePal":"GamePal ♾️Mixlab"
"GamePal":"GamePal ♾️Mixlab",
"RembgNode_Mix":"Removebg"
}
# web ui的节点功能
@@ -636,16 +639,16 @@ try:
print('LaMaInpainting.available',LaMaInpainting.available)
if LaMaInpainting.available:
NODE_CLASS_MAPPINGS['LaMaInpainting']=LaMaInpainting
except:
print('LaMaInpainting.available',False)
except Exception as e:
print('LaMaInpainting.available',False,e)
try:
from .nodes.ClipInterrogator import ClipInterrogator
print('ClipInterrogator.available',ClipInterrogator.available)
if ClipInterrogator.available:
NODE_CLASS_MAPPINGS['ClipInterrogator']=ClipInterrogator
except:
print('ClipInterrogator.available',False)
except Exception as e:
print('ClipInterrogator.available',False,e)
try:
from .nodes.TextGenerateNode import PromptGenerate,ChinesePrompt
@@ -655,8 +658,15 @@ try:
print('ChinesePrompt.available',ChinesePrompt.available)
if ChinesePrompt.available:
NODE_CLASS_MAPPINGS['ChinesePrompt_Mix']=ChinesePrompt
except:
print('TextGenerateNode.available',False)
except Exception as e:
print('TextGenerateNode.available',False,e)
try:
from .nodes.RembgNode import RembgNode_
print('RembgNode_.available',RembgNode_.available)
if RembgNode_.available:
NODE_CLASS_MAPPINGS['RembgNode_Mix']=RembgNode_
except Exception as e:
print('RembgNode_.available',False,e)
print('\033[93m -------------- \033[0m')
+58
View File
@@ -0,0 +1,58 @@
Residential space
Apartment building
Villa
Bungalow
Condominium
Commercial space
Shopping mall
Supermarket
Restaurant
Store
Market
Office space
Office building
Office
Meeting room
Co-working space
Educational space
School
University
Training institution
Library
Laboratory
Medical space
Hospital
Clinic
Pharmacy
Nursing home
Rehabilitation center
Cultural space
Museum
Library
Theater
Concert hall
Gallery
Sports space
Sports stadium
Gym
Swimming pool
Basketball court
Football field
Transportation space
Airport
Train station
Subway station
Bus stop
Parking lot
Public space
Park
Square
Street
Pedestrian street
Community center
Industrial space
Factory
Warehouse
Production workshop
Mine
Power plant
+55 -5
View File
@@ -14,6 +14,8 @@ import math
from .Watcher import FolderWatcher
FONT_PATH= os.path.abspath(os.path.join(os.path.dirname(__file__),'../assets/王汉宗颜楷体繁.ttf'))
MAX_RESOLUTION=8192
@@ -70,6 +72,48 @@ def color_transfer(source,target):
# 组合
def create_big_image(image_folder, image_count):
# 计算行数和列数
rows = math.ceil(math.sqrt(image_count))
cols = math.ceil(image_count / rows)
# 获取每个小图的尺寸
small_width = 100
small_height = 100
# 计算大图的尺寸
big_width = small_width * cols
big_height = small_height * rows
# 创建一个新的大图
big_image = Image.new('RGB', (big_width, big_height))
# 获取所有图片文件的路径
image_files = [f for f in os.listdir(image_folder) if os.path.isfile(os.path.join(image_folder, f))]
# 遍历所有图片文件
for i, image_file in enumerate(image_files):
# 打开图片并调整大小
image = Image.open(os.path.join(image_folder, image_file))
image = image.resize((small_width, small_height))
# 计算当前小图的位置
row = i // cols
col = i % cols
x = col * small_width
y = row * small_height
# 将小图粘贴到大图上
big_image.paste(image, (x, y))
return big_image
# # 调用方法并保存大图
# image_folder = 'path/to/folder/containing/images'
# image_count = 100
# big_image = create_big_image(image_folder, image_count)
# big_image.save('path/to/save/big_image.jpg')
@@ -945,7 +989,7 @@ class TransparentImage:
# 运行的函数
def run(self,images,masks,invert,save,filename_prefix,prompt=None, extra_pnginfo=None):
print('TransparentImage',images.shape,images.size())
# print('TransparentImage',images.shape,images.size(),masks.shape,masks.size())
# print(masks.shape,masks.size())
ui_images=[]
@@ -955,11 +999,16 @@ class TransparentImage:
masks_new=[]
nh=masks.shape[0]//count
#INPUT_IS_LIST = False, 一个batch传进来
if nh*count==masks.shape[0]:
masks_new=split_mask_by_new_height(masks,nh)
masks_new=masks
if images.shape[0]==masks.shape[0] and images.shape[1]==masks.shape[1] and images.shape[2]==masks.shape[2]:
print('TransparentImage',images.shape,images.size(),masks.shape,masks.size())
else:
masks_new=split_mask_by_new_height(masks,masks.shape[0])
#INPUT_IS_LIST = False, 一个batch传进来
if nh*count==masks.shape[0]:
masks_new=split_mask_by_new_height(masks,nh)
else:
masks_new=split_mask_by_new_height(masks,masks.shape[0])
is_save=True if save=='yes' else False
@@ -2129,3 +2178,4 @@ class ImageColorTransfer:
return (res,)
+71
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@@ -0,0 +1,71 @@
import numpy as np
import scipy.ndimage
import torch
import comfy.utils
from nodes import MAX_RESOLUTION
def grow(mask, expand, tapered_corners):
c = 0 if tapered_corners else 1
kernel = np.array([[c, 1, c],
[1, 1, 1],
[c, 1, c]])
mask = mask.reshape((-1, mask.shape[-2], mask.shape[-1]))
out = []
for m in mask:
output = m.numpy()
for _ in range(abs(expand)):
if expand < 0:
output = scipy.ndimage.grey_erosion(output, footprint=kernel)
else:
output = scipy.ndimage.grey_dilation(output, footprint=kernel)
output = torch.from_numpy(output)
out.append(output)
return torch.stack(out, dim=0)
def combine(destination, source, x, y):
output = destination.reshape((-1, destination.shape[-2], destination.shape[-1])).clone()
source = source.reshape((-1, source.shape[-2], source.shape[-1]))
left, top = (x, y,)
right, bottom = (min(left + source.shape[-1], destination.shape[-1]), min(top + source.shape[-2], destination.shape[-2]))
visible_width, visible_height = (right - left, bottom - top,)
source_portion = source[:, :visible_height, :visible_width]
destination_portion = destination[:, top:bottom, left:right]
#operation == "subtract":
output[:, top:bottom, left:right] = destination_portion - source_portion
output = torch.clamp(output, 0.0, 1.0)
return output
class OutlineMask:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"mask": ("MASK",),
"outline_width":("INT", {"default": 10,"min": 1, "max": MAX_RESOLUTION, "step": 1}),
"tapered_corners": ("BOOLEAN", {"default": True}),
}
}
RETURN_TYPES = ('MASK',)
FUNCTION = "run"
CATEGORY = "♾️Mixlab/Mask"
# 运行的函数
def run(self, mask, outline_width, tapered_corners):
m1=grow(mask,outline_width,tapered_corners)
m2=grow(mask,-outline_width,tapered_corners)
m3=combine(m1,m2,0,0)
return (m3,)
+38 -53
View File
@@ -12,6 +12,17 @@ from PIL.PngImagePlugin import PngInfo
# req = request.Request("http://127.0.0.1:8188/prompt", data=data)
# request.urlopen(req)
embeddings_path=os.path.join(folder_paths.models_dir, "embeddings")
def get_files_with_extension(directory, extension):
file_list = []
for root, dirs, files in os.walk(directory):
for file in files:
if file.endswith(extension):
file_name = os.path.splitext(file)[0]
file_list.append(file_name)
return file_list
default_prompt1='''Swing
Slide
@@ -334,7 +345,10 @@ class RandomPrompt:
for w2 in words2:
w2=w2.strip()
if '``' not in w2:
w2=w2+',``'
if w2=="":
w2='``'
else:
w2=w2+',``'
if w1!='' and w2!='':
prompts.append(w2.replace('``', w1))
pbar.update(1)
@@ -357,62 +371,33 @@ class RandomPrompt:
# class RunWorkflow:
# @classmethod
# def INPUT_TYPES(s):
# return {
# "required": {
# "workflow": ("STRING", {
# "multiline": False,
# "default": ''
# }),
# "prompt": ("STRING", {
# "multiline": False,
# "default": ''
# }),
# "image": ("IMAGE",),
# "input_node": ("STRING", {
# "multiline": False,
# "default": ''
# }),
# "output_node": ("STRING", {
# "multiline": False,
# "default": ''
# }),
# },
class EmbeddingPrompt:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"embedding":(get_files_with_extension(embeddings_path,'.pt'),),
"weight": ("FLOAT", {"default": 1, "min": -2, "max": 2,"step":0.01 ,"display": "slider"}),
},
# }
}
RETURN_TYPES = ("STRING",)
# RETURN_TYPES = ("IMAGE","STRING",)
FUNCTION = "run"
# FUNCTION = "run"
CATEGORY = "♾️Mixlab/Prompt"
# CATEGORY = "♾️Mixlab/workflow"
OUTPUT_IS_LIST = (False,)
# OUTPUT_NODE = True
# OUTPUT_IS_LIST = (True,)
# OUTPUT_NODE = True
# # 运行的函数
# def run(self,workflow,prompt,image,input_node,output_node):
# print('#运行的函数',prompt,image,input_node,output_node)
# workflow=json.loads(workflow)
# input_node=input_node.split(".")
# workflow[input_node[0]][input_node[1]][input_node[2]]=prompt
# workflow_new={}
# # 遍历,seed设为随机
# for key, value in workflow.items():
# if 'inputs' in value:
# if 'seed' in value['inputs']:
# value['inputs']['seed']= random.randint(1, 18446744073709551614)
# workflow_new[key]=value
# queue_prompt(workflow_new)
# print('#运行的函数',workflow_new[input_node[0]])
# # return (new_prompt)
# return {"ui":{"images": []},"result": ([image],['text'],)}
# 运行的函数
def run(self,embedding,weight):
prompt='embedding:'+embedding
if weight!=1:
prompt='('+prompt+':'+str(weight)+')'
prompt=" "+prompt+' '
# return (new_prompt)
return (prompt,)
+164
View File
@@ -0,0 +1,164 @@
import os,sys
import folder_paths
from PIL import Image
import importlib.util
import comfy.utils
import numpy as np
import torch
U2NET_HOME=os.path.join(folder_paths.models_dir, "rembg")
os.environ["U2NET_HOME"] = U2NET_HOME
global _available
_available=False
def is_installed(package):
try:
spec = importlib.util.find_spec(package)
except ModuleNotFoundError:
return False
return spec is not None
try:
if is_installed('rembg')==False:
import subprocess
# 安装
print('#pip install rembg[gpu]')
result = subprocess.run([sys.executable, '-s', '-m', 'pip', 'install', 'rembg[gpu]'], capture_output=True, text=True)
#检查命令执行结果
if result.returncode == 0:
print("#install success")
from rembg import new_session, remove
_available=True
else:
print("#install error")
else:
from rembg import new_session, remove
_available=True
except:
_available=False
def run_bg(model_name= "unet",images=[]):
# model_name = "unet" # "isnet-general-use"
rembg_session = new_session(model_name)
masks=[]
rgba_images=[]
rgb_images=[]
# 进度条
pbar = comfy.utils.ProgressBar(len(images) )
for img in images:
# use the post_process_mask argument to post process the mask to get better results.
mask = remove(img, session=rembg_session,only_mask=True,post_process_mask=True)
# mask=mask.convert('L')
# masks.append(mask)
if model_name=="u2net_cloth_seg":
width, original_height = mask.size
num_slices = original_height // img.height
for i in range(num_slices):
top = i * img.height
bottom = (i + 1) * img.height
slice_image = mask.crop((0, top, width, bottom))
slice_mask=slice_image.convert('L')
masks.append(slice_mask)
# rgba图
image_rgba = img.convert("RGBA")
image_rgba.putalpha(slice_mask)
rgba_images.append(image_rgba)
#rgb
rgb_image = Image.new("RGB", image_rgba.size, (0, 0, 0))
rgb_image.paste(image_rgba, mask=image_rgba.split()[3])
rgb_images.append(rgb_image)
else:
mask=mask.convert('L')
# mask.save(output_path)
masks.append(mask)
# rgba图
image_rgba = img.convert("RGBA")
image_rgba.putalpha(mask)
rgba_images.append(image_rgba)
#rgb
rgb_image = Image.new("RGB", image_rgba.size, (0, 0, 0))
rgb_image.paste(image_rgba, mask=image_rgba.split()[3])
rgb_images.append(rgb_image)
pbar.update(1)
return (masks,rgba_images,rgb_images)
# Tensor to PIL
def tensor2pil(image):
return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
# Convert PIL to Tensor
def pil2tensor(image):
return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
class RembgNode_:
global _available
available=_available
@classmethod
def INPUT_TYPES(s):
return {"required": {
"image": ("IMAGE",),
"model_name": (["u2net",
"u2netp",
"u2net_human_seg",
"u2net_cloth_seg",
"silueta",
"isnet-general-use",
"isnet-anime",
# "sam"
],),
},
}
RETURN_TYPES = ("MASK","IMAGE","RGBA",)
RETURN_NAMES = ("masks","images","RGBAs")
FUNCTION = "run"
CATEGORY = "♾️Mixlab/Mask"
OUTPUT_NODE = True
INPUT_IS_LIST = True
OUTPUT_IS_LIST = (True,True,True,)
def run(self,image,model_name):
# 兼容list输入和batch输入
model_name=model_name[0]
images=[]
for ims in image:
for im in ims:
im=tensor2pil(im)
images.append(im)
masks,rgba_images,rgb_images=run_bg(model_name,images)
masks=[pil2tensor(m) for m in masks]
rgba_images=[pil2tensor(m) for m in rgba_images]
rgb_images=[pil2tensor(m) for m in rgb_images]
return (masks,rgb_images,rgba_images,)
+50 -14
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@@ -6,7 +6,7 @@ import os,sys
import folder_paths
# from PIL import Image
# import importlib.util
import importlib.util
import comfy.utils
# import numpy as np
@@ -29,14 +29,47 @@ if not os.path.exists(zh_en_model_path):
def translate(zh_en_tokenizer,zh_en_model,texts):
def is_installed(package):
try:
spec = importlib.util.find_spec(package)
except ModuleNotFoundError:
return False
return spec is not None
try:
if is_installed('sentencepiece')==False:
import subprocess
# 安装
print('#pip install sentencepiece')
result = subprocess.run([sys.executable, '-s', '-m', 'pip', 'install', 'sentencepiece'], capture_output=True, text=True)
#检查命令执行结果
if result.returncode == 0 and is_installed('sentencepiece'):
print("#install success")
_available=True
else:
print("#install error")
_available=False
else:
_available=True
except:
_available=False
def translate(zh_en_tokenizer,zh_en_model,text):
with torch.no_grad():
encoded = zh_en_tokenizer(texts, return_tensors="pt")
encoded = zh_en_tokenizer([text], return_tensors="pt")
encoded.to(zh_en_model.device)
sequences = zh_en_model.generate(**encoded)
return zh_en_tokenizer.batch_decode(sequences, skip_special_tokens=True)
return zh_en_tokenizer.batch_decode(sequences, skip_special_tokens=True)[0]
input = "青春不能回头,所以青春没有终点。 ——《火影忍者》"
# input = "青春不能回头,所以青春没有终点。 ——《火影忍者》"
# print(input, translate(input))
@@ -159,12 +192,12 @@ class ChinesePrompt:
# 进度条
pbar = comfy.utils.ProgressBar(len(text)+1)
text = correct_prompt_syntax(text[0])
texts = [correct_prompt_syntax(t) for t in text]
print('correct_prompt_syntax::',texts)
if zh_en_model==None:
zh_en_model = AutoModelForSeq2SeqLM.from_pretrained(zh_en_model_path).eval()
zh_en_tokenizer = AutoTokenizer.from_pretrained(zh_en_model_path)
zh_en_tokenizer = AutoTokenizer.from_pretrained(zh_en_model_path,padding=True, truncation=True)
zh_en_model.to("cuda" if torch.cuda.is_available() else "cpu")
# zh_en_tokenizer.to("cuda" if torch.cuda.is_available() else "cpu")
@@ -176,14 +209,17 @@ class ChinesePrompt:
prompt_result=[]
# print('zh_en_model device',zh_en_model.device,text_pipe.model.device,torch.cuda.current_device() )
en_text=translate(zh_en_tokenizer,zh_en_model,text)
en_texts=[]
for t in texts:
en_text=translate(zh_en_tokenizer,zh_en_model,t)
en_texts.append(en_text)
zh_en_model.to('cpu')
print("test en_text",en_text)
print("test en_text",en_texts)
# en_text.to("cuda" if torch.cuda.is_available() else "cpu")
pbar.update(1)
for t in en_text:
for t in en_texts:
if generation=='on':
prompt =text_generate(text_pipe,t,seed)
# 多条,还是单条
@@ -196,7 +232,7 @@ class ChinesePrompt:
pbar.update(1)
text_pipe.model.to('cpu')
prompt_result = [correct_prompt_syntax(prompt_result[0])]
prompt_result = [correct_prompt_syntax(p) for p in prompt_result]
return {
"ui":{
+31 -6
View File
@@ -761,19 +761,44 @@
} catch (error) {
isURL = false;
}
let isAElement = undefined;
try {
let div = document.createElement('div');
div.innerHTML = link;
let a = div.querySelector('a');
if (a.href) {
new URL(a.href);
isAElement = div.innerHTML;
}
} catch (error) {
}
// new URL(link)
if (isURL) {
if (isURL || isAElement) {
const linkBtn = document.createElement('button');
// linkBtn.href = link;
linkBtn.innerText = 'go to'
if (isURL) {
// linkBtn.href = link;
linkBtn.innerText = 'go to'
} else if (isAElement) {
linkBtn.innerHTML = isAElement
}
action.appendChild(linkBtn)
linkBtn.style.marginLeft = '18px';
linkBtn.addEventListener('click', e => {
e.preventDefault();
window.open(link);
if (isURL) {
e.preventDefault();
window.open(link);
}
// if(isURL) window.open(link);
})
}
const output_card = document.createElement("div");
output_card.className = 'output_card'
container.appendChild(output_card)
@@ -1826,7 +1851,7 @@
p.className = 'prompt_image'
p.innerText = prompt;
a.appendChild(p)
img.alt=prompt
img.alt = prompt
}
// imgDiv.parentElement.appendChild(a);
+1 -1
View File
@@ -3,7 +3,7 @@ import { app } from '../../../scripts/app.js'
const repoOwner = 'shadowcz007' // 替换为仓库的所有者
const repoName = 'comfyui-mixlab-nodes' // 替换为仓库的名称
const version = 'v0.12.0'
const version = 'v0.13.0'
fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
.then(response => response.json())
+1 -2
View File
@@ -178,8 +178,7 @@ app.registerExtension({
const orig_nodeCreated = nodeType.prototype.onNodeCreated
nodeType.prototype.onNodeCreated = async function () {
orig_nodeCreated?.apply(this, arguments)
name
const mutable_prompt = this.widgets.filter(
w => w.name == 'mutable_prompt'
)[0]
+4 -2
View File
@@ -739,8 +739,9 @@ app.registerExtension({
if (category === '0') {
apps_opts.push(
...Array.from(apps_map[category], a => {
// console.log('#1级',a)
return {
content: a.name,
content: `${a.name}_${a.version}`,
has_submenu: false,
callback: async () => {
try {
@@ -768,8 +769,9 @@ app.registerExtension({
disabled: false,
submenu: {
options: Array.from(apps_map[category], a => {
// console.log('#二级',a)
return {
content: a.name,
content: `${a.name}_${a.version}`,
callback: async () => {
try {
let item = (await get_my_app(a.filename, a.category))[0]