Update checkVersion_mixlab.js

v0.8.0 🚀🚗🚚🏃‍ LaMaInpainting
- 新增 LaMaInpainting
- 优化color节点的输出
- 修复高清显示屏上定位节点不准的情况

- Add LaMaInpainting
- Optimize the output of the color node
- Fix the issue of inaccurate positioning node on high-definition display screens

.gitignore

@@ -2,4 +2,5 @@ __pycache__/
 https/
 nodes/config.json
 workflow/my_workflow.json
-workflow/my_workflow_app.json
+workflow/my_workflow_app.json
+app/*

README.md

@@ -1,26 +1,33 @@
-## 
-v0.6.0 🚀🚗🚚🏃‍ Workflow-to-APP
+
+### Workflow-to-APP 🚀🚗🚚🏃
 - 新增AppInfo节点，可以通过简单的配置，把workflow转变为一个Web APP。
+- 支持多个web app 切换
+
+- Support multiple web app switching.
 - Add the AppInfo node, which allows you to transform the workflow into a web app by simple configuration.
 
+![](./assets/0-m-app.png)
+
 ![](./assets/appinfo-readme.png)
+
 Example:
 - workflow
 ![APP info](./workflow/appinfo-workflow.svg)
+[text-to-image](./workflow/Text-to-Image-app.json)
 
 APP-JSON:
-- [text-to-image](./app/text-to-image_1_Wed%20Dec%2027%202023.json)
-- [image-to-image](./app/image-to-image_1_Wed%20Dec%2027%202023.json)
+- [text-to-image](./example/text-to-image_1_Wed%20Dec%2027%202023.json)
+- [image-to-image](./example/image-to-image_1_Wed%20Dec%2027%202023.json)
+- text-to-text
 
-### 3D
-![](./assets/3dimage.png)
-[workflow](./workflow/3D-workflow.json)
+> 暂时支持6种节点作为界面上的输入节点：Load Image、CLIPTextEncode、TextInput_、FloatSlider、IntNumber、CheckpointLoaderSimple、LoraLoader
+
+> 输出节点：PreviewImage 、SaveImage、ShowTextForGPT、VHS_VideoCombine
 
 
-### ScreenShareNode & FloatingVideoNode
-> Now comfyui supports capturing screen pixel streams from any software and can be used for LCM-Lora integration. Let's get started with implementation and design! 💻🌐
+### Real-time Design
+> ScreenShareNode & FloatingVideoNode. Now comfyui supports capturing screen pixel streams from any software and can be used for LCM-Lora integration. Let's get started with implementation and design! 💻🌐
 
-> 
 ![screenshare](./assets/screenshare.png)
 
 https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43e-410a-ab3a-1952b7b4e7da
@@ -31,6 +38,7 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
 
 !! Please use the address with HTTPS (https://127.0.0.1).
 
+
 ### SpeechRecognition & SpeechSynthesis
 ![f](./assets/audio-workflow.svg)
 
@@ -39,17 +47,13 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
 ### GPT
 > Support for calling multiple GPTs.ChatGPT、ChatGLM3 , Some code provided by rui. If you are using OpenAI's service, fill in https://api.openai.com/v1 . If you are using a local LLM service, fill in http://127.0.0.1:xxxx/v1 .  Azure OpenAI:https://xxxx.openai.azure.com 
 
-
 ![gpt-workflow.svg](./assets/gpt-workflow.svg)
 
 [workflow-5](./workflow/5-gpt-workflow.json)
 
-### LoadImagesFromLocal
-> Monitor changes to images in a local folder, and trigger real-time execution of workflows, supporting common image formats, especially PSD format, in conjunction with Photoshop. 
-
-![watch](./assets/4-loadfromlocal-watcher-workflow.svg)
-
-[workflow-4](./workflow/4-loadfromlocal-watcher-workflow.json)
+### 3D
+![](./assets/3dimage.png)
+[workflow](./workflow/3D-workflow.json)
 
 
 ### Layers
@@ -59,6 +63,18 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
 
 ![poster](./assets/poster-workflow.svg)
 
+
+### LoadImagesFromLocal
+> Monitor changes to images in a local folder, and trigger real-time execution of workflows, supporting common image formats, especially PSD format, in conjunction with Photoshop. 
+
+![watch](./assets/4-loadfromlocal-watcher-workflow.svg)
+
+[workflow-4](./workflow/4-loadfromlocal-watcher-workflow.json)
+
+### LoadImagesFromURL
+> Conveniently load images from a fixed address on the internet to ensure that default images in the workflow can be executed.
+
+
 ## Utils
 > The Color node provides a color picker for easy color selection, the Font node offers built-in font selection for use with TextImage to generate text images, and the DynamicDelayByText node allows delayed execution based on the length of the input text.
 
@@ -98,6 +114,10 @@ Add edges to an image.
 ![FeatheredMask](./assets/FlVou_Y6kaGWYoEj1Tn0aTd4AjMI.jpg)
 
 
+> LaMaInpainting
+
+from [simple-lama-inpainting](https://github.com/enesmsahin/simple-lama-inpainting)
+
 
 ### Improvement 
 
@@ -111,14 +131,26 @@ An improvement has been made to directly redirect to GitHub to search for missin
 ![node-not-found](./assets/node-not-found.png)
 
 
+### Update 
+v0.8.0 🚀🚗🚚🏃‍ LaMaInpainting
+- 新增 LaMaInpainting
+- 优化color节点的输出
+- 修复高清显示屏上定位节点不准的情况
+
+- Add LaMaInpainting
+- Optimize the output of the color node
+- Fix the issue of inaccurate positioning node on high-definition display screens
+
+
 ### Models
-[Download CLIPSeg](https://huggingface.co/CIDAS/clipseg-rd64-refined/tree/main), move to : model/clipseg
+[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
 
 <!-- ### Workflow
 [Workflow](./workflow.md) -->
 
 
-
 ## Installation
 
 manually install, simply clone the repo into the custom_nodes directory with this command:
@@ -152,7 +184,6 @@ pip3 install -r requirements.txt
 访问 [www.mixcomfy.com](https://www.mixcomfy.com)，获得更多内测功能，关注微信公众号：Mixlab无界社区
 
 
-
 #### Thanks:
 [ComfyUI-CLIPSeg](https://github.com/biegert/ComfyUI-CLIPSeg/tree/main)
 

__init__.py

@@ -4,7 +4,7 @@ import subprocess
 import importlib.util
 import sys,json
 import urllib
-
+import hashlib
 import datetime
 
 
@@ -79,6 +79,13 @@ install_openai()
 current_path = os.path.abspath(os.path.dirname(__file__))
 
 
+
+def calculate_md5(string):
+    encoded_string = string.encode()
+    md5_hash = hashlib.md5(encoded_string).hexdigest()
+    return md5_hash
+
+
 def create_key(key_p,crt_p):
     import OpenSSL
     # 生成自签名证书
@@ -162,17 +169,75 @@ def get_workflows():
     workflows=read_workflow_json_files(workflow_path)
     return workflows
 
-def get_my_workflow_for_app():
-    # print("#####path::", current_path)
-    workflow_path=os.path.join(current_path, "workflow/my_workflow_app.json")
-    print('workflow_path: ',workflow_path)
-    json_data={}
-    try:
-        with open(workflow_path) as json_file:
-            json_data = json.load(json_file)
-    except:
-        print('-')
-    return json_data
+def get_my_workflow_for_app(filename="my_workflow_app.json"):
+    app_path=os.path.join(current_path, "app")
+    if not os.path.exists(app_path):
+        os.mkdir(app_path)
+
+    apps=[]
+    if filename==None:
+        data=read_workflow_json_files(app_path)
+        i=0
+        for item in data:
+            try:
+                x=item["data"]
+                if i==0:
+                    apps.append({
+                        "filename":item["filename"],
+                        "data":x,
+                        "date":item["date"]
+                    })
+                else:
+                    apps.append({
+                        "filename":item["filename"],
+                        "data":{
+                            "app":{
+                                "description":x['app']['description'],
+                                "filename":(x['app']['filename'] if 'filename' in x['app'] else "") ,
+                                "icon":(x['app']['icon'] if 'icon' in x['app'] else None),
+                                "name":x['app']['name'],
+                                "version":x['app']['version'],
+                            }
+                        },
+                        "date":item["date"]
+                    })
+                i+=1
+            except Exception as e:
+                print("发生异常：", str(e))
+    else:
+        app_workflow_path=os.path.join(app_path, filename)
+        # print('app_workflow_path: ',app_workflow_path)
+        try:
+            with open(app_workflow_path) as json_file:
+                apps = [{
+                    'filename':filename,
+                    'data':json.load(json_file)
+                }]
+        except Exception as e:
+            print("发生异常：", str(e))
+        
+        if len(apps)==1:
+            data=read_workflow_json_files(app_path)
+            
+            for item in data:
+                x=item["data"]
+                print(apps[0]['filename'] ,item["filename"])
+                if apps[0]['filename']!=item["filename"]:
+                    apps.append({
+                        "filename":item["filename"],
+                        "data":{
+                            "app":{
+                                "description":x['app']['description'],
+                                "filename":(x['app']['filename'] if 'filename' in x['app'] else "") ,
+                                "icon":(x['app']['icon'] if 'icon' in x['app'] else None),
+                                "name":x['app']['name'],
+                                "version":x['app']['version'],
+                            }
+                        },
+                        "date":item["date"]
+                    })
+
+    return apps
 
 def save_workflow_json(data):
     workflow_path=os.path.join(current_path, "workflow/my_workflow.json")
@@ -180,11 +245,22 @@ def save_workflow_json(data):
         json.dump(data, file)
     return workflow_path
 
-def save_workflow_for_app(data):
-    workflow_path=os.path.join(current_path, "workflow/my_workflow_app.json")
-    with open(workflow_path, 'w') as file:
+def save_workflow_for_app(data,filename="my_workflow_app.json"):
+    app_path=os.path.join(current_path, "app")
+    if not os.path.exists(app_path):
+        os.mkdir(app_path)
+    app_workflow_path=os.path.join(app_path, filename)
+ 
+    try:
+        output_str = json.dumps(data['output'])
+        data['app']['id']=calculate_md5(output_str)
+        # id=data['app']['id']
+    except Exception as e:
+        print("发生异常：", str(e))
+    
+    with open(app_workflow_path, 'w') as file:
         json.dump(data, file)
-    return workflow_path
+    return filename
 
 def get_nodes_map():
     # print("#####path::", current_path)
@@ -275,7 +351,7 @@ async def mixlab_hander(request):
 async def mixlab_app_handler(request):
     html_file = os.path.join(current_path, "web/index.html")
     if os.path.exists(html_file):
-        with open(html_file, 'r') as f:
+        with open(html_file, 'r', encoding='utf-8', errors='ignore') as f:
             html_data = f.read()
             return web.Response(text=html_data, content_type='text/html')
     else:
@@ -295,14 +371,17 @@ async def mixlab_workflow_hander(request):
                     'file_path':file_path
                 }
             elif data['task']=='save_app':
-                file_path=save_workflow_for_app(data['data'])
+                file_path=save_workflow_for_app(data['data'],data['filename'])
                 result={
                     'status':'success',
                     'file_path':file_path
                 }
             elif data['task']=='my_app':
+                filename=None
+                if 'filename' in data:
+                    filename=data['filename']
                 result={
-                    'data':get_my_workflow_for_app(),
+                    'data':get_my_workflow_for_app(filename),
                     'status':'success',
                 }
             elif data['task']=='list':
@@ -359,14 +438,14 @@ PromptServer.add_routes=new_add_routes
 
 # 导入节点
 from .nodes.PromptNode import RandomPrompt
-from .nodes.ImageNode import NoiseImage,TransparentImage,LoadImagesFromPath,ResizeImage,TextImage,SvgImage,Image3D,EmptyLayer,ShowLayer,NewLayer,MergeLayers,AreaToMask,SmoothMask,FeatheredMask,SplitLongMask,ImageCropByAlpha,EnhanceImage,FaceToMask
+from .nodes.ImageNode import NoiseImage,TransparentImage,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
 from .nodes.Clipseg import CLIPSeg,CombineMasks
 from .nodes.ChatGPT import ChatGPTNode,ShowTextForGPT,CharacterInText
 from .nodes.Audio import GamePal,SpeechRecognition,SpeechSynthesis
-from .nodes.Utils import AppInfo,FloatSlider,ColorInput,FontInput,TextToNumber,DynamicDelayProcessor
-
+from .nodes.Utils import AppInfo,IntNumber,FloatSlider,TextInput,ColorInput,FontInput,TextToNumber,DynamicDelayProcessor,LimitNumber,SwitchByIndex,GetImageSize_,MultiplicationNode
+from .nodes.Lama import LaMaInpainting
 
 # 要导出的所有节点及其名称的字典
 # 注意：名称应全局唯一
@@ -377,6 +456,7 @@ NODE_CLASS_MAPPINGS = {
     "TransparentImage":TransparentImage,
     "ResizeImageMixlab":ResizeImage,
     "LoadImagesFromPath":LoadImagesFromPath,
+    "LoadImagesFromURL":LoadImagesFromURL,
     "TextImage":TextImage,
     "EnhanceImage":EnhanceImage,
     "SvgImage":SvgImage,
@@ -403,9 +483,16 @@ NODE_CLASS_MAPPINGS = {
     "SpeechSynthesis":SpeechSynthesis,
     "Color":ColorInput,
     "FloatSlider":FloatSlider,
+    "IntNumber":IntNumber,
+    "TextInput_":TextInput,
     "Font":FontInput,
     "TextToNumber":TextToNumber,
-    "DynamicDelayProcessor":DynamicDelayProcessor
+    "DynamicDelayProcessor":DynamicDelayProcessor,
+    "MultiplicationNode":MultiplicationNode,
+    "GetImageSize_":GetImageSize_,
+    "SwitchByIndex":SwitchByIndex,
+    "LimitNumber":LimitNumber, 
+    "LaMaInpainting":LaMaInpainting
     # "GamePal":GamePal
 }
 
@@ -425,7 +512,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "SpeechSynthesis":"SpeechSynthesis ♾️Mixlab",
     "SpeechRecognition":"SpeechRecognition ♾️Mixlab",
     "3DImage":"3DImage ♾️Mixlab",
-    "DynamicDelayProcessor":"DynamicDelayByText ♾️Mixlab"
+    "DynamicDelayProcessor":"DynamicDelayByText ♾️Mixlab",
+    "LaMaInpainting":"LaMaInpainting ♾️Mixlab"
 
     # "GamePal":"GamePal ♾️Mixlab"
 }
@@ -434,5 +522,5 @@ NODE_DISPLAY_NAME_MAPPINGS = {
 WEB_DIRECTORY = "./web"
 
 print('--------------')
-print('\033[91mMixlab Nodes: \033[93mLoaded\033[0m')
+print('\033[91m ### Mixlab Nodes: \033[93mLoaded\033[0m')
 print('--------------')

data/extension-node-map.json

@@ -4763,6 +4763,8 @@
         [
             "3DImage",
             "AppInfo",
+            "IntNumber",
+            "FloatSlider",
             "ResizeImage",
             "NoiseImage",
             "AreaToMask",
@@ -4778,6 +4780,7 @@
             "Font",
             "ImageCropByAlpha",
             "LoadImagesFromPath",
+            "LoadImagesFromURL",
             "MergeLayers",
             "NewLayer",
             "RandomPrompt",
@@ -4790,11 +4793,14 @@
             "SplitLongMask",
             "SvgImage",
             "TextImage",
+            "ResizeImageMixlab",
             "TransparentImage",
             "VAEDecodeConsistencyDecoder",
             "VAELoaderConsistencyDecoder",
             "TextToNumber",
-            "DynamicDelayProcessor"
+            "TextInput_",
+            "DynamicDelayProcessor",
+            "LaMaInpainting"
         ],
         {
             "title_aux": "comfyui-mixlab-nodes"

nodes/ChatGPT.py

@@ -75,15 +75,15 @@ class ChatGPTNode:
             "required": {
                 "api_key":("KEY", {"default": "", "multiline": True}),
                 "api_url":("URL", {"default": "", "multiline": True}),
-                "prompt": ("STRING", {"multiline": True}),
+                "prompt": ("STRING", {"multiline": True,"dynamicPrompts": False}),
                 "system_content": ("STRING", 
                                    {
                                        "default": "You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.", 
-                                       "multiline": True
+                                       "multiline": True,"dynamicPrompts": False
                                        }),
                 "model": (["gpt-3.5-turbo","gpt-35-turbo","gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "gpt-4-0613","gpt-4-1106-preview"], 
                           {"default": "gpt-3.5-turbo"}),
-                "seed": ("INT", {"default": 0, "min": 0, "max": 10000, "step": 1}),
+                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "step": 1}),
                 "context_size":("INT", {"default": 1, "min": 0, "max":30, "step": 1}),
             },
              "hidden": {
@@ -167,7 +167,7 @@ class ShowTextForGPT:
     def INPUT_TYPES(s):
         return {
             "required": {
-                "text": ("STRING", {"forceInput": True}),
+                "text": ("STRING", {"forceInput": True,"dynamicPrompts": False}),
             }
         }
 
@@ -189,8 +189,8 @@ class CharacterInText:
     def INPUT_TYPES(s):
         return {
             "required": {
-                 "text": ("STRING", {"multiline": True}),
-                 "character": ("STRING", {"multiline": True}),
+                 "text": ("STRING", {"multiline": True,"dynamicPrompts": False}),
+                 "character": ("STRING", {"multiline": True,"dynamicPrompts": False}),
                  "start_index": ("INT", {
                     "default": 1,
                     "min": 0, #Minimum value

nodes/Clipseg.py

@@ -35,6 +35,16 @@ if not os.path.exists(clipseg_model_dir):
 
 """Helper methods for CLIPSeg nodes"""
 
+
+# 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)
+
+
 def tensor_to_numpy(tensor: torch.Tensor) -> np.ndarray:
     """Convert a tensor to a numpy array and scale its values to 0-255."""
     array = tensor.numpy().squeeze()
@@ -91,7 +101,7 @@ class CLIPSeg:
         return {"required":
                     {
                         "image": ("IMAGE",),
-                        "text": ("STRING", {"multiline": False}),
+                        "text": ("STRING", {"multiline": False,"dynamicPrompts": False}),
                         
                      },
                 "optional":
@@ -107,7 +117,7 @@ class CLIPSeg:
     RETURN_NAMES = ("Mask","Heatmap Mask", "BW Mask")
 
     # INPUT_IS_LIST = True
-    # OUTPUT_IS_LIST = (True,)
+    OUTPUT_IS_LIST = (False,False,False,)
 
     FUNCTION = "segment_image"
     def segment_image(self, image: torch.Tensor, text: str, blur: float, threshold: float, dilation_factor: int) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor]:
@@ -180,12 +190,13 @@ class CLIPSeg:
         binary_mask_image = Image.fromarray(binary_mask_resized[..., 0])
 
         # convert PIL image to numpy array
-        tensor_bw = binary_mask_image.convert("RGB")
-        tensor_bw = np.array(tensor_bw).astype(np.float32) / 255.0
-        tensor_bw = torch.from_numpy(tensor_bw)[None,]
-        tensor_bw = tensor_bw.squeeze(0)[..., 0]
+        tensor_bw = binary_mask_image.convert("L")
+        tensor_bw=pil2tensor(tensor_bw)
+        # tensor_bw = np.array(tensor_bw).astype(np.float32) / 255.0
+        # tensor_bw = torch.from_numpy(tensor_bw)[None,]
+        # tensor_bw = tensor_bw.squeeze(0)[..., 0]
 
-        return tensor_bw, image_out_heatmap, image_out_binary
+        return (tensor_bw, image_out_heatmap, image_out_binary,)
 
     #OUTPUT_NODE = False
 
@@ -235,7 +246,7 @@ class CombineMasks:
         
         # Resize heatmap and binary mask to match the original image dimensions
         dimensions = (image_np.shape[1], image_np.shape[0])
-        print('heatmap',heatmap)
+        # print('heatmap',heatmap)
         if dimensions is None or dimensions[0] == 0 or dimensions[1] == 0:
             raise ValueError("Invalid dimensions")
         

nodes/ImageNode.py

@@ -1,4 +1,5 @@
 import numpy as np
+import requests
 import torch
 from PIL import Image, ImageOps,ImageFilter,ImageEnhance,ImageDraw,ImageSequence, ImageFont
 from PIL.PngImagePlugin import PngInfo
@@ -197,6 +198,24 @@ def load_image(fp,white_bg=False):
         
     return images
 
+def load_image_and_mask_from_url(url, timeout=10):
+    # Load the image from the URL
+    response = requests.get(url, timeout=timeout)
+
+    content_type = response.headers.get('Content-Type')
+    
+    image = Image.open(BytesIO(response.content))
+
+    # Create a mask from the image's alpha channel
+    mask = image.convert('RGBA').split()[-1]
+
+    # Convert the mask to a black and white image
+    mask = mask.convert('L')
+
+    image=image.convert('RGB')
+
+    return (image, mask)
+
 
 # 获取图片s
 def get_images_filepath(f,white_bg=False):
@@ -487,6 +506,7 @@ def generate_text_image(text, font_path, font_size, text_color, vertical=True, s
         y = 0
         for line in lines:
             for char in line:
+                #print('char',char)
                 char_coordinates.append((x, y))
                 x += font_size + spacing
             y += font_size + spacing
@@ -495,10 +515,10 @@ def generate_text_image(text, font_path, font_size, text_color, vertical=True, s
     # 3. Calculate image width and height
     if layout == "vertical":
         width = (len(lines) * (font_size + spacing)) - spacing
-        height = (len(max(lines, key=len)) * (font_size + spacing)) - spacing
+        height = ((len(max(lines, key=len))+1) * (font_size + spacing)) + spacing
     else:
         width = (len(max(lines, key=len)) * (font_size + spacing)) - spacing
-        height = (len(lines) * (font_size + spacing)) - spacing
+        height = ((len(lines)-1) * (font_size + spacing)) + font_size
 
     # 4. Draw each character on the image
     image = Image.new('RGBA', (width, height), (255, 255, 255,0))
@@ -869,7 +889,7 @@ class LoadImagesFromPath:
                 }
             }
     
-    RETURN_TYPES = ('IMAGE','MASK','STRING')
+    RETURN_TYPES = ('IMAGE','MASK','STRING',)
 
     FUNCTION = "run"
 
@@ -902,6 +922,11 @@ class LoadImagesFromPath:
 
         images=get_images_filepath(file_path,white_bg=='enable')
 
+        # 当开启了监听，则取最新的，第一个文件
+        if watcher=='enable':
+            index_variable=0
+            newest_files='enable'
+
         # 排序
         sorted_files = sorted(images, key=lambda x: os.path.getmtime(x['file_path']), reverse=(newest_files=='enable'))
 
@@ -913,9 +938,13 @@ class LoadImagesFromPath:
             masks.append(im['mask'])
         
         # print('index_variable',index_variable)
-        if index_variable!=-1:
-            imgs=[imgs[index_variable]] if index_variable < len(imgs) else None
-            masks=[masks[index_variable]] if index_variable < len(masks) else None
+        
+        try:
+            if index_variable!=-1:
+                imgs=[imgs[index_variable]] if index_variable < len(imgs) else None
+                masks=[masks[index_variable]] if index_variable < len(masks) else None
+        except Exception as e:
+            print("发生了一个未知的错误：", str(e))
 
         # print('#prompt::::',prompt)
         return (imgs,masks,prompt,)
@@ -962,8 +991,8 @@ class TextImage:
     def INPUT_TYPES(s):
         return {"required": { 
             
-                    "text": ("STRING",{"multiline": True,"default": "龍馬精神迎新歲"}),
-                    "font_path": ("STRING",{"multiline": False,"default": FONT_PATH}),
+                    "text": ("STRING",{"multiline": True,"default": "龍馬精神迎新歲","dynamicPrompts": False}),
+                    "font_path": ("STRING",{"multiline": False,"default": FONT_PATH,"dynamicPrompts": False}),
                     "font_size": ("INT",{
                                 "default":100, 
                                 "min": 100, #Minimum value
@@ -973,17 +1002,17 @@ class TextImage:
                                 }), 
                     "spacing": ("INT",{
                                 "default":12, 
-                                "min": 1, #Minimum value
+                                "min": -200, #Minimum value
                                 "max": 200, #Maximum value
                                 "step": 1, #Slider's step
                                 "display": "number" # Cosmetic only: display as "number" or "slider"
                                 }), 
-                    "text_color":("STRING",{"multiline": False,"default": "#000000"}),
+                    "text_color":("STRING",{"multiline": False,"default": "#000000","dynamicPrompts": False}),
                     "vertical":("BOOLEAN", {"default": True},),
                              },
                 }
     
-    RETURN_TYPES = ("IMAGE","MASK")
+    RETURN_TYPES = ("IMAGE","MASK",)
     # RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
 
     FUNCTION = "run"
@@ -1004,6 +1033,62 @@ class TextImage:
 
         return (img,mask,)
 
+class LoadImagesFromURL:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": { 
+                    "url": ("STRING",{"multiline": True,"default": "https://","dynamicPrompts": False}),
+                             },
+                }
+    
+    RETURN_TYPES = ("IMAGE","MASK",)
+    RETURN_NAMES = ("images","masks",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/image"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (True,True,)
+
+
+    global urls_image
+    urls_image={}
+
+    def run(self,url):
+        global urls_image
+        print(urls_image)
+        def filter_http_urls(urls):
+            filtered_urls = []
+            for url in urls.split('\n'):
+                if url.startswith('http'):
+                    filtered_urls.append(url)
+            return filtered_urls
+
+        filtered_urls = filter_http_urls(url)
+
+        images=[]
+        masks=[]
+
+        for img_url in filtered_urls:
+            try:
+                if img_url in urls_image:
+                    img,mask=urls_image[img_url]
+                else:
+                    img,mask=load_image_and_mask_from_url(img_url)
+                    urls_image[img_url]=(img,mask)
+
+                img1=pil2tensor(img)
+                mask1=pil2tensor(mask)
+
+                images.append(img1)
+                masks.append(mask1)
+            except Exception as e:
+                print("发生了一个未知的错误：", str(e))
+            
+        return (images,masks,)
+
+
 
 
 class SvgImage:

nodes/Lama.py

@@ -0,0 +1,85 @@
+import os
+import folder_paths
+from simple_lama_inpainting import SimpleLama
+from PIL import Image
+
+import numpy as np
+
+import torch
+
+
+os.environ['LAMA_MODEL'] =  os.path.join(folder_paths.models_dir, "lama/big-lama.pt")
+if os.environ.get("LAMA_MODEL"):
+    model_path=os.environ.get("LAMA_MODEL")
+    if not os.path.exists(model_path):
+        os.environ['LAMA_MODEL']=''
+        raise FileNotFoundError(
+            f"lama torchscript model not found: {model_path}"
+                )
+
+# 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)
+
+
+# simple_lama = SimpleLama()
+
+# img_path = "image.png"
+# mask_path = "mask.png"
+
+# image = Image.open(img_path)
+# mask = Image.open(mask_path).convert('L')
+
+# result = simple_lama(image, mask)
+# result.save("inpainted.png")
+
+
+class LaMaInpainting:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+            "image": ("IMAGE",),
+            "mask": ("MASK",),
+                             },
+
+            
+                }
+    
+    RETURN_TYPES = ("IMAGE",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/image"
+
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (True,)
+    global simple_lama
+    simple_lama = None
+    def run(self,image,mask):
+        global simple_lama
+
+        result=[]
+        if simple_lama==None:
+            simple_lama = SimpleLama()
+        else:
+            simple_lama.model.to("cuda" if torch.cuda.is_available() else "cpu")
+
+        for i in range(len(image)):
+            im=image[i]
+            ma=mask[i]
+            im=tensor2pil(im)
+            ma=tensor2pil(ma)
+            ma =ma.convert('L')
+            
+            res = simple_lama(im, ma)
+            res=pil2tensor(res)
+            result.append(res)
+        # result.save("inpainted.png")
+        if simple_lama.device=='cuda':
+            simple_lama.model.to('cpu')
+
+        return (result,)

nodes/Utils.py

@@ -88,18 +88,23 @@ class ColorInput:
                              },
                 }
     
-    RETURN_TYPES = ("STRING",)
-    # RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
+    RETURN_TYPES = ("STRING","INT","INT","INT","FLOAT",)
+    RETURN_NAMES = ("hex","r","g","b","a",)
 
     FUNCTION = "run"
 
     CATEGORY = "♾️Mixlab/utils"
 
     INPUT_IS_LIST = False
-    OUTPUT_IS_LIST = (False,False,)
+    OUTPUT_IS_LIST = (False,False,False,False,False,)
 
     def run(self,color):
-        return (color,)
+        h=color['hex']
+        r=color['r']
+        g=color['g']
+        b=color['b']
+        a=color['a']
+        return (h,r,g,b,a,)
 
 
 
@@ -174,7 +179,7 @@ class FloatSlider:
                         "default": 0, 
                         "min": 0, #Minimum value
                         "max": 1, #Maximum value
-                        "step": 0.01, #Slider's step
+                        "step": 0.001, #Slider's step
                         "display": "slider" # Cosmetic only: display as "number" or "slider"
                     }),
                              },
@@ -193,6 +198,84 @@ class FloatSlider:
        
         return (number,)
     
+  
+class IntNumber:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+                    "number":("INT", {
+                        "default": 0, 
+                        "min": -1, #Minimum value
+                        "max": 0xffffffffffffffff,
+                        "step": 1, #Slider's step
+                        "display": "number" # Cosmetic only: display as "number" or "slider"
+                    }),
+                             },
+                }
+    
+    RETURN_TYPES = ("INT",) 
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/utils"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,)
+
+    def run(self,number):
+       
+        return (number,)
+
+class MultiplicationNode:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+                    "numberA":(any_type,),
+                    "numberB":("FLOAT", {
+                        "default": 0, 
+                        "min": -1, #Minimum value
+                        "max": 0xffffffffffffffff,
+                        "step": 0.1, #Slider's step
+                        "display": "number" # Cosmetic only: display as "number" or "slider"
+                    })
+                             },
+                }
+    
+    RETURN_TYPES = ("FLOAT","INT",) 
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/utils"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,False,)
+
+    def run(self,numberA,numberB):
+        b=int(numberA*numberB)
+        a=float(numberA*numberB)
+        return (a,b,) 
+
+class TextInput:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+                    "text": ("STRING",{"multiline": True,"default": ""}),
+                             },
+                }
+    
+    RETURN_TYPES = ("STRING",) 
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/utils"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,)
+
+    def run(self,text):
+       
+        return (text,)
+    
 # 接收一个值，然后根据字符串或数值长度计算延迟时间，用户可以自定义延迟"字/s"，延迟之后将转化
 
 import comfy.samplers
@@ -291,14 +374,14 @@ class AppInfo:
     @classmethod
     def INPUT_TYPES(s):
         return {"required": { 
-                    "name": ("STRING",{"multiline": False,"default": "Mixlab-App"}),
+                    "name": ("STRING",{"multiline": False,"default": "Mixlab-App","dynamicPrompts": False}),
                     "image": ("IMAGE",),
-                    "input_ids":("STRING",{"multiline": True,"default": "\n".join(["1","2","3"])}),
-                    "output_ids":("STRING",{"multiline": True,"default": "\n".join(["5","9"])}),
+                    "input_ids":("STRING",{"multiline": True,"default": "\n".join(["1","2","3"]),"dynamicPrompts": False}),
+                    "output_ids":("STRING",{"multiline": True,"default": "\n".join(["5","9"]),"dynamicPrompts": False}),
                              },
 
                 "optional":{
-                    "description":("STRING",{"multiline": True,"default": ""}),
+                    "description":("STRING",{"multiline": True,"default": "","dynamicPrompts": False}),
                     "version":("INT", {
                         "default": 1, 
                         "min": 1, 
@@ -306,6 +389,7 @@ class AppInfo:
                         "step": 1, 
                         "display": "number"  
                     }),
+                    "share_prefix":("STRING",{"multiline": False,"default": "","dynamicPrompts": False}),
                 }
 
                 }
@@ -320,15 +404,129 @@ class AppInfo:
     INPUT_IS_LIST = False
     OUTPUT_IS_LIST = (False,)
 
-    def run(self,name,image,input_ids,output_ids,description,version):
+    def run(self,name,image,input_ids,output_ids,description,version,share_prefix):
 
         im=create_temp_file(image)
         
         # id=get_json_hash([name,im,input_ids,output_ids,description,version])
 
-        return {"ui": {"json": [name,im,input_ids,output_ids,description,version]}, "result": (image,)}
+        return {"ui": {"json": [name,im,input_ids,output_ids,description,version,share_prefix]}, "result": (image,)}
     
 
     
 
+class GetImageSize_:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "image": ("IMAGE",),
+            }
+        }
+
+    RETURN_TYPES = ("INT", "INT")
+    RETURN_NAMES = ("width", "height")
+
+    FUNCTION = "get_size"
+
+    CATEGORY = "♾️Mixlab/utils"
+
+    def get_size(self, image):
+        _, height, width, _ = image.shape
+        return (width, height)
+
+
+
+class SwitchByIndex:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "A":(any_type,),
+                "B":(any_type,),
+                "index":("INT", {
+                        "default": -1, 
+                        "min": -1, 
+                        "max": 1000, 
+                        "step": 1, 
+                        "display": "number"  
+                    }),
+            }
+        }
+
+    RETURN_TYPES = (any_type,)
+    RETURN_NAMES = ("C",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/utils"
+
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (True,)
+
+    def run(self, A,B,index):
+        C=[]
+        index=index[0]
+        for a in A:
+            C.append(a)
+        for b in B:
+            C.append(b)
+        if index>-1:
+            try:
+                C=[C[index]]
+            except Exception as e:
+                C=[]
+        return (C,)
+
+
+
+class LimitNumber:
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "number":(any_type,),
+                "min_value":("INT", {
+                        "default": 0, 
+                        "min": 0, 
+                        "max": 0xffffffffffffffff,
+                        "step": 1, 
+                        "display": "number"  
+                    }),
+                "max_value":("INT", {
+                        "default": 1, 
+                        "min": 1, 
+                        "max": 0xffffffffffffffff,
+                        "step": 1, 
+                        "display": "number"  
+                    }),
+            }
+        }
+
+    RETURN_TYPES = (any_type,)
+    RETURN_NAMES = ("number",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/utils"
+
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,)
+
+    def run(self, number, min_value, max_value):
+        nn=number
+
+        if isinstance(number, int):
+            min_value=int(min_value)
+            max_value=int(max_value)
+        if isinstance(number, float):
+            min_value=float(min_value)
+            max_value=float(max_value)
+
+        if number < min_value:
+            nn= min_value
+        elif number > max_value:
+            nn= max_value
+        
+        return (nn,)
 

requirements.txt

@@ -3,4 +3,5 @@ pyOpenSSL
 watchdog
 opencv-python-headless
 matplotlib
-openai
+openai
+simple-lama-inpainting

web/javascript/app_mixlab.js

@@ -75,7 +75,24 @@ function extractInputAndOutputData (jsonData, inputIds = [], outputIds = []) {
     if (data.hasOwnProperty(id)) {
       if (inputIds.includes(id)) {
         let node = app.graph.getNodeById(id)
-        input[inputIds.indexOf(id)] = { ...data[id], title: node.title, id }
+        let options = []
+        // 模型
+        try {
+          if (node.type === 'CheckpointLoaderSimple') {
+            options = node.widgets.filter(w => w.name === 'ckpt_name')[0]
+              .options.values
+          } else if (node.type === 'LoraLoader') {
+            options = node.widgets.filter(w => w.name === 'lora_name')[0]
+              .options.values
+          }
+        } catch (error) {}
+
+        input[inputIds.indexOf(id)] = {
+          ...data[id],
+          title: node.title,
+          id,
+          options
+        }
         // input.push()
       }
       if (outputIds.includes(id)) {
@@ -103,7 +120,8 @@ async function save_app (json) {
     method: 'POST',
     body: JSON.stringify({
       data: json,
-      task: 'save_app'
+      task: 'save_app',
+      filename: json.app.filename
     })
   })
   return await res.json()
@@ -128,6 +146,7 @@ function downloadJsonFile (jsonData, fileName = 'mix_app.json') {
 async function save (json, download = false) {
   const name = json[0],
     version = json[5],
+    share_prefix = json[6], //用于分享的功能扩展
     description = json[4],
     inputIds = json[2].split('\n').filter(f => f),
     outputIds = json[3].split('\n').filter(f => f)
@@ -154,7 +173,9 @@ async function save (json, download = false) {
       description,
       version,
       input,
-      output
+      output,
+      share_prefix,
+      filename: `${name}_${version}_${new Date().toDateString()}.json`
     }
 
     try {
@@ -164,14 +185,15 @@ async function save (json, download = false) {
     // let http_workflow = app.graph.serialize()
 
     if (download) {
-      await downloadJsonFile(
-        data,
-        `${data.app.name}_${data.app.version}_${new Date().toDateString()}.json`
-      )
+       await save_app(data)
+       await downloadJsonFile(data, data.app.filename)
       let open = window.confirm(
-        `You can now access the standalone application on a new page!\n${getUrl()}/mixlab/app?type=new`
+        `You can now access the standalone application on a new page!\n${getUrl()}/mixlab/app?filename=${encodeURIComponent(data.app.filename)}`
       )
-      if (open) window.open(`${getUrl()}/mixlab/app?type=new`)
+      if (open)
+        window.open(
+          `${getUrl()}/mixlab/app?filename=${encodeURIComponent(data.app.filename)}`
+        )
     } else {
       await save_app(data)
 
@@ -192,7 +214,7 @@ app.registerExtension({
       const orig_nodeCreated = nodeType.prototype.onNodeCreated
       nodeType.prototype.onNodeCreated = function () {
         orig_nodeCreated?.apply(this, arguments)
-        // console.log(this)
+        console.log('#orig_nodeCreated', this)
         const widget = {
           type: 'div',
           name: 'AppInfoRun',
@@ -202,7 +224,7 @@ app.registerExtension({
               get_position_style(
                 ctx,
                 widget_width,
-                node.widgets[4].last_y + 24,
+                node.size[1] - widget_height,
                 node.size[1]
               )
             )
@@ -220,7 +242,7 @@ app.registerExtension({
         widget.div = $el('div', {})
 
         const btn = document.createElement('button')
-        btn.innerText = 'Save For App'
+        btn.innerText = 'Save & Open'
         btn.style = style
 
         btn.addEventListener('click', () => {
@@ -230,6 +252,7 @@ app.registerExtension({
           } else {
             alert('Please run the workflow before saving')
             // app.queuePrompt(0, 1)
+            this.widgets.filter(w => w.name === 'version')[0].value += 1
           }
         })
 
@@ -245,6 +268,7 @@ app.registerExtension({
           } else {
             alert('Please run the workflow before saving')
             // app.queuePrompt(0, 1)
+            this.widgets.filter(w => w.name === 'version')[0].value += 1
           }
         })
 
@@ -266,7 +290,7 @@ app.registerExtension({
       const onExecuted = nodeType.prototype.onExecuted
       nodeType.prototype.onExecuted = async function (message) {
         onExecuted?.apply(this, arguments)
-        // console.log(this.widgets)
+        console.log(message.json)
 
         window._mixlab_app_json = message.json
         try {

web/javascript/checkVersion_mixlab.js

@@ -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 = 'v0.6.0'
+const version = 'v0.8.0'
 
 fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
   .then(response => response.json())

web/javascript/image_mixlab.js

@@ -406,7 +406,9 @@ app.registerExtension({
 
         this.serialize_widgets = true //需要保存参数
       }
-    }
+    };
+
+ 
   },
   async loadedGraphNode (node, app) {
     // Fires every time a node is constructed

web/javascript/layer_mixlab.js

@@ -156,8 +156,8 @@ const parseSvg = async svgContent => {
   return { data, image: base64, svgElement }
 }
 
-async function setArea (cw, ch, base64, data, fn) {
-  let displayHeight = Math.round(window.screen.availHeight * 0.6)
+async function setArea (cw, ch, topBase64, base64, data, fn) {
+  let displayHeight = Math.round(window.screen.availHeight * 0.8)
   let div = document.createElement('div')
   div.innerHTML = `
     <div id='ml_overlay' style='position: absolute;top:0;background: #251f1fc4;
@@ -170,8 +170,13 @@ async function setArea (cw, ch, base64, data, fn) {
       outline: 2px solid #eaeaea;
       box-shadow: 8px 9px 17px #575757;' />
       <div id='ml_selection' style='position: absolute; 
-      border: 2px dashed red; 
-      pointer-events: none;'></div>
+      border: 2px dashed red;
+      pointer-events: none;
+      background-image: url("${topBase64}");
+            background-repeat: no-repeat;
+            background-size: cover;
+            '></div>
+      <div class="mx_close"> X </div>
     </div>`
   // document.body.querySelector('#ml_overlay')
   document.body.appendChild(div)
@@ -181,13 +186,25 @@ async function setArea (cw, ch, base64, data, fn) {
   // canvas.height = ch
 
   let img = div.querySelector('#ml_video')
-  let overlay = div.querySelector('#ml_overlay')
+  // let overlay = div.querySelector('#ml_overlay')
   let selection = div.querySelector('#ml_selection')
+  let close = div.querySelector('.mx_close')
   let startX, startY, endX, endY
   let start = false
+  let setDone = false
   // Set video source
   img.src = base64
   // canvas.toDataURL();
+  close.style = `cursor: pointer;
+  position: fixed;
+  left: 12px;
+  top: 12px;
+  z-index: 99999999;
+  background: black;
+  width: 44px;
+  height: 44px;
+  text-align: center;
+  line-height: 44px;`
 
   // init area
   // const data = getSetAreaData()
@@ -216,14 +233,37 @@ async function setArea (cw, ch, base64, data, fn) {
   img.addEventListener('mousedown', startSelection)
   img.addEventListener('mousemove', updateSelection)
   img.addEventListener('mouseup', endSelection)
-  overlay.addEventListener('click', remove)
 
-  function remove () {
-    overlay.removeEventListener('click', remove)
+  const removeDiv = () => {
+    div.remove()
+    close.removeEventListener('click', removeDiv)
     img.removeEventListener('mousedown', startSelection)
     img.removeEventListener('mousemove', updateSelection)
     img.removeEventListener('mouseup', endSelection)
-    div.remove()
+    img.removeEventListener('mousedown', setDoneCheck)
+  }
+  close.addEventListener('click', removeDiv)
+
+  const setDoneCheck = event => {
+    console.log(setDone)
+    if (setDone) {
+      img.addEventListener('mousedown', startSelection)
+      img.addEventListener('mousemove', updateSelection)
+      img.addEventListener('mouseup', endSelection)
+      setDone = false
+      start = false
+      startX = event.clientX
+      startY = event.clientY
+    }
+  }
+  img.addEventListener('mousedown', setDoneCheck)
+
+  function remove () {
+    img.removeEventListener('mousedown', startSelection)
+    img.removeEventListener('mousemove', updateSelection)
+    img.removeEventListener('mouseup', endSelection)
+    setDone = true
+    // div.remove()
   }
 
   function startSelection (event) {
@@ -531,12 +571,24 @@ app.registerExtension({
               }
             }
             try {
+              console.log('this.inputs', this.inputs)
+              let topLinkId = this.inputs[0].link
+              let topNodeId = app.graph.links[topLinkId].origin_id
+              let topIm = app.graph.getNodeById(topNodeId).imgs[0]
+
               let linkId = this.inputs[3].link
               let nodeId = app.graph.links[linkId].origin_id
               // console.log(linkId,this.inputs)
               let im = app.graph.getNodeById(nodeId).imgs[0]
-              let src = im.src
-              setArea(im.naturalWidth, im.naturalHeight, src, data, updateValue)
+              // let src = im.src
+              setArea(
+                im.naturalWidth,
+                im.naturalHeight,
+                topIm.src,
+                im.src,
+                data,
+                updateValue
+              )
             } catch (error) {}
           })
         }

web/javascript/ui_mixlab.js

@@ -4,6 +4,7 @@ import { ComfyWidgets } from '../../../scripts/widgets.js'
 import { $el } from '../../../scripts/ui.js'
 import { closeIcon } from './svg_icons.js'
 
+
 import {
   GroupNodeConfig,
   GroupNodeHandler
@@ -667,10 +668,23 @@ app.registerExtension({
         ...options
       ] // and return the options
     }
+    LGraphCanvas.prototype.centerOnNode = function(node) {
+      var dpr = window.devicePixelRatio || 1;  // 获取设备像素比
+      this.ds.offset[0] =
+          -node.pos[0] -
+          node.size[0] * 0.5 +
+          (this.canvas.width * 0.5) / (this.ds.scale * dpr);  // 考虑设备像素比
+      this.ds.offset[1] =
+          -node.pos[1] -
+          node.size[1] * 0.5 +
+          (this.canvas.height * 0.5) / (this.ds.scale * dpr);  // 考虑设备像素比
+      this.setDirty(true, true);
+    };
   },
   async setup () {
     // Add canvas menu options
     const orig = LGraphCanvas.prototype.getCanvasMenuOptions
+
     LGraphCanvas.prototype.getCanvasMenuOptions = function () {
       const options = orig.apply(this, arguments)
 
@@ -714,7 +728,7 @@ app.registerExtension({
           let textB = document.createElement('p')
           btn.appendChild(textB)
           btn.appendChild(btnB)
-          textB.style.fontSize='12px';
+          textB.style.fontSize = '12px'
           textB.innerText = `Locate and navigate nodes ♾️Mixlab`
 
           btnB.style = `float: right; border: none; color: var(--input-text);
@@ -790,11 +804,12 @@ app.registerExtension({
           for (let nodeId in nodes) {
             let n = nodes[nodeId].class_type
             if (nodesMap[n]) {
-              const { url, title } = nodesMap[n]
+              const { url, title: _title } = nodesMap[n]
+              let title = app.graph.getNodeById(nodeId).title || _title
               let d = document.createElement('button')
               d.style = `text-align: left;margin:6px;color: var(--input-text);
                 background-color: var(--comfy-input-bg); border-color: var(--border-color);cursor: pointer;`
-              d.addEventListener('click', () => {
+                d.addEventListener('click', () => {
                 const node = app.graph.getNodeById(nodeId)
                 if (!node) return
                 app.canvas.centerOnNode(node)
@@ -810,10 +825,10 @@ app.registerExtension({
               })
 
               d.innerHTML = `
-                <span>${'#' + nodeId} ${n}</span>
+                <span>${'#' + nodeId} ${title}</span>
                 <a href="${url}" target="_blank" style="text-decoration: none;">🔗</a>
                 `
-              d.title = title
+              d.title = n
 
               nodesDiv.appendChild(d)
             }

web/javascript/utils_mixlab.js

@@ -2,7 +2,7 @@ import { app } from '../../../scripts/app.js'
 import { api } from '../../../scripts/api.js'
 import { ComfyWidgets } from '../../../scripts/widgets.js'
 import { $el } from '../../../scripts/ui.js'
-import { addValueControlWidget } from "../../../scripts/widgets.js";
+import { addValueControlWidget } from '../../../scripts/widgets.js'
 
 const getLocalData = key => {
   let data = {}
@@ -45,6 +45,21 @@ function get_position_style (ctx, widget_width, y, node_height) {
   }
 }
 
+function hexToRGBA (hexColor) {
+  var hex = hexColor.replace('#', '')
+  var r = parseInt(hex.substring(0, 2), 16)
+  var g = parseInt(hex.substring(2, 4), 16)
+  var b = parseInt(hex.substring(4, 6), 16)
+
+  // 获取透明度的十六进制值
+  var alphaHex = hex.substring(6)
+
+  // 将透明度的十六进制值转换为十进制值
+  var alpha = parseInt(alphaHex, 16) / 255
+
+  return [r,g,b,alpha]
+}
+
 app.registerExtension({
   name: 'Mixlab.utils.Color',
   async getCustomWidgets (app) {
@@ -60,8 +75,16 @@ app.registerExtension({
             return [128, 32] // a method to compute the current size of the widget
           },
           async serializeValue (nodeId, widgetIndex) {
-            let data = getLocalData('_mixlab_utils_color')
-            return data[node.id] || '#000000'
+            let data = getLocalData('_mixlab_utils_color');
+            let hex=data[node.id] || '#000000'
+            let [r,g,b,a]=hexToRGBA(hex)
+            return {
+              hex,
+              r,
+              g,
+              b,
+              a
+            }
           }
         }
         //  widget.something = something;          // maybe adds stuff to it
@@ -109,7 +132,7 @@ app.registerExtension({
           ip.style = `outline: none;
             border: none;
             padding: 4px;
-            width: 100%;cursor: pointer;
+            width: 70%;cursor: pointer;
             height: 32px;`
           const label = document.createElement('label')
           label.style = 'font-size: 10px;min-width:32px'
@@ -164,16 +187,17 @@ app.registerExtension({
 
   async beforeRegisterNodeDef (nodeType, nodeData, app) {
     if (nodeType.comfyClass == 'TextToNumber') {
-
       const onExecuted = nodeType.prototype.onExecuted
       nodeType.prototype.onExecuted = function (message) {
         onExecuted?.apply(this, arguments)
-        const random_number=this.widgets.filter(w=>w.name==='random_number')[0]
-        if(random_number.value==='enable'){
-          const n=this.widgets.filter(w=>w.name==='number')[0]
-          n.value=message.num[0]
+        const random_number = this.widgets.filter(
+          w => w.name === 'random_number'
+        )[0]
+        if (random_number.value === 'enable') {
+          const n = this.widgets.filter(w => w.name === 'number')[0]
+          n.value = message.num[0]
         }
-        
+
         console.log('TextToNumber', random_number.value)
       }
     }

workflow/Text-to-Image-app.json

@@ -0,0 +1,717 @@
+{
+  "last_node_id": 25,
+  "last_link_id": 32,
+  "nodes": [
+    {
+      "id": 5,
+      "type": "CLIPTextEncode",
+      "pos": [
+        1029,
+        -2149
+      ],
+      "size": {
+        "0": 425.27801513671875,
+        "1": 180.6060791015625
+      },
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 6
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [
+            3
+          ],
+          "slot_index": 0
+        }
+      ],
+      "title": "负向prompt",
+      "properties": {
+        "Node name for S&R": "CLIPTextEncode"
+      },
+      "widgets_values": [
+        "text, watermark"
+      ]
+    },
+    {
+      "id": 6,
+      "type": "VAEDecode",
+      "pos": [
+        1867,
+        -2378
+      ],
+      "size": {
+        "0": 210,
+        "1": 46
+      },
+      "flags": {
+        "collapsed": false
+      },
+      "order": 10,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "samples",
+          "type": "LATENT",
+          "link": 7
+        },
+        {
+          "name": "vae",
+          "type": "VAE",
+          "link": 8
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            9
+          ],
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "VAEDecode"
+      }
+    },
+    {
+      "id": 15,
+      "type": "EnhanceImage",
+      "pos": [
+        2591,
+        -2531
+      ],
+      "size": {
+        "0": 315,
+        "1": 58
+      },
+      "flags": {},
+      "order": 12,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 25
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            18
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "EnhanceImage"
+      },
+      "widgets_values": [
+        1.1
+      ]
+    },
+    {
+      "id": 21,
+      "type": "EmptyLatentImage",
+      "pos": [
+        998,
+        -2674
+      ],
+      "size": [
+        315,
+        106
+      ],
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "width",
+          "type": "INT",
+          "link": 30,
+          "widget": {
+            "name": "width"
+          }
+        },
+        {
+          "name": "height",
+          "type": "INT",
+          "link": 32,
+          "widget": {
+            "name": "height"
+          }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": [
+            26
+          ],
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "EmptyLatentImage"
+      },
+      "widgets_values": [
+        512,
+        512,
+        1
+      ]
+    },
+    {
+      "id": 24,
+      "type": "LimitNumber",
+      "pos": [
+        665,
+        -2958
+      ],
+      "size": {
+        "0": 315,
+        "1": 82
+      },
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "number",
+          "type": "*",
+          "link": 29
+        }
+      ],
+      "outputs": [
+        {
+          "name": "number",
+          "type": "*",
+          "links": [
+            30
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LimitNumber"
+      },
+      "widgets_values": [
+        512,
+        4089
+      ]
+    },
+    {
+      "id": 25,
+      "type": "LimitNumber",
+      "pos": [
+        648,
+        -2659
+      ],
+      "size": {
+        "0": 315,
+        "1": 82
+      },
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "number",
+          "type": "*",
+          "link": 31
+        }
+      ],
+      "outputs": [
+        {
+          "name": "number",
+          "type": "*",
+          "links": [
+            32
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LimitNumber"
+      },
+      "widgets_values": [
+        512,
+        4089
+      ]
+    },
+    {
+      "id": 22,
+      "type": "IntNumber",
+      "pos": [
+        302,
+        -2758
+      ],
+      "size": {
+        "0": 315,
+        "1": 58
+      },
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "INT",
+          "type": "INT",
+          "links": [
+            29
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "title": "Width",
+      "properties": {
+        "Node name for S&R": "IntNumber"
+      },
+      "widgets_values": [
+        512
+      ]
+    },
+    {
+      "id": 23,
+      "type": "IntNumber",
+      "pos": [
+        299,
+        -2601
+      ],
+      "size": {
+        "0": 315,
+        "1": 58
+      },
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "INT",
+          "type": "INT",
+          "links": [
+            31
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "title": "Height",
+      "properties": {
+        "Node name for S&R": "IntNumber"
+      },
+      "widgets_values": [
+        512
+      ]
+    },
+    {
+      "id": 2,
+      "type": "CheckpointLoaderSimple",
+      "pos": [
+        567,
+        -2422
+      ],
+      "size": {
+        "0": 315,
+        "1": 98
+      },
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "MODEL",
+          "type": "MODEL",
+          "links": [
+            1
+          ],
+          "slot_index": 0
+        },
+        {
+          "name": "CLIP",
+          "type": "CLIP",
+          "links": [
+            5,
+            6
+          ],
+          "slot_index": 1
+        },
+        {
+          "name": "VAE",
+          "type": "VAE",
+          "links": [
+            8
+          ],
+          "slot_index": 2
+        }
+      ],
+      "title": "Model",
+      "properties": {
+        "Node name for S&R": "CheckpointLoaderSimple"
+      },
+      "widgets_values": [
+        "deliberate_v2.safetensors"
+      ]
+    },
+    {
+      "id": 1,
+      "type": "KSampler",
+      "pos": [
+        1509,
+        -2394
+      ],
+      "size": {
+        "0": 315,
+        "1": 262
+      },
+      "flags": {},
+      "order": 9,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "model",
+          "type": "MODEL",
+          "link": 1
+        },
+        {
+          "name": "positive",
+          "type": "CONDITIONING",
+          "link": 2
+        },
+        {
+          "name": "negative",
+          "type": "CONDITIONING",
+          "link": 3
+        },
+        {
+          "name": "latent_image",
+          "type": "LATENT",
+          "link": 26,
+          "slot_index": 3
+        },
+        {
+          "name": "denoise",
+          "type": "FLOAT",
+          "link": 16,
+          "widget": {
+            "name": "denoise"
+          },
+          "slot_index": 4
+        }
+      ],
+      "outputs": [
+        {
+          "name": "LATENT",
+          "type": "LATENT",
+          "links": [
+            7
+          ],
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "KSampler"
+      },
+      "widgets_values": [
+        730250870715434,
+        "randomize",
+        15,
+        6.9,
+        "euler",
+        "karras",
+        0.59
+      ]
+    },
+    {
+      "id": 14,
+      "type": "FloatSlider",
+      "pos": [
+        1007,
+        -2819
+      ],
+      "size": {
+        "0": 315,
+        "1": 58
+      },
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "FLOAT",
+          "type": "FLOAT",
+          "links": [
+            16
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "title": "denoise",
+      "properties": {
+        "Node name for S&R": "FloatSlider"
+      },
+      "widgets_values": [
+        1
+      ]
+    },
+    {
+      "id": 16,
+      "type": "PreviewImage",
+      "pos": [
+        2949,
+        -2615
+      ],
+      "size": {
+        "0": 210,
+        "1": 246
+      },
+      "flags": {},
+      "order": 13,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "images",
+          "type": "IMAGE",
+          "link": 18
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "PreviewImage"
+      }
+    },
+    {
+      "id": 4,
+      "type": "CLIPTextEncode",
+      "pos": [
+        1022,
+        -2375
+      ],
+      "size": {
+        "0": 422.84503173828125,
+        "1": 164.31304931640625
+      },
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "clip",
+          "type": "CLIP",
+          "link": 5
+        }
+      ],
+      "outputs": [
+        {
+          "name": "CONDITIONING",
+          "type": "CONDITIONING",
+          "links": [
+            2
+          ],
+          "slot_index": 0
+        }
+      ],
+      "title": "prompt",
+      "properties": {
+        "Node name for S&R": "CLIPTextEncode"
+      },
+      "widgets_values": [
+        "superman,fat cat"
+      ]
+    },
+    {
+      "id": 7,
+      "type": "AppInfo",
+      "pos": [
+        2134,
+        -2528
+      ],
+      "size": {
+        "0": 408.4201965332031,
+        "1": 406.9195861816406
+      },
+      "flags": {},
+      "order": 11,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": 9
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": [
+            25
+          ],
+          "shape": 3,
+          "slot_index": 0
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "AppInfo"
+      },
+      "widgets_values": [
+        "Text-to-Image",
+        "4\n22\n23\n2\n\n\n",
+        "16",
+        "演示基本的文生图流程",
+        1,
+        "#comfyui-mixlab-nodes# ",
+        null
+      ]
+    }
+  ],
+  "links": [
+    [
+      1,
+      2,
+      0,
+      1,
+      0,
+      "MODEL"
+    ],
+    [
+      2,
+      4,
+      0,
+      1,
+      1,
+      "CONDITIONING"
+    ],
+    [
+      3,
+      5,
+      0,
+      1,
+      2,
+      "CONDITIONING"
+    ],
+    [
+      5,
+      2,
+      1,
+      4,
+      0,
+      "CLIP"
+    ],
+    [
+      6,
+      2,
+      1,
+      5,
+      0,
+      "CLIP"
+    ],
+    [
+      7,
+      1,
+      0,
+      6,
+      0,
+      "LATENT"
+    ],
+    [
+      8,
+      2,
+      2,
+      6,
+      1,
+      "VAE"
+    ],
+    [
+      9,
+      6,
+      0,
+      7,
+      0,
+      "IMAGE"
+    ],
+    [
+      16,
+      14,
+      0,
+      1,
+      4,
+      "FLOAT"
+    ],
+    [
+      18,
+      15,
+      0,
+      16,
+      0,
+      "IMAGE"
+    ],
+    [
+      25,
+      7,
+      0,
+      15,
+      0,
+      "IMAGE"
+    ],
+    [
+      26,
+      21,
+      0,
+      1,
+      3,
+      "LATENT"
+    ],
+    [
+      29,
+      22,
+      0,
+      24,
+      0,
+      "*"
+    ],
+    [
+      30,
+      24,
+      0,
+      21,
+      0,
+      "INT"
+    ],
+    [
+      31,
+      23,
+      0,
+      25,
+      0,
+      "*"
+    ],
+    [
+      32,
+      25,
+      0,
+      21,
+      1,
+      "INT"
+    ]
+  ],
+  "groups": [],
+  "config": {},
+  "extra": {},
+  "version": 0.4
+}