Update README.md

- 优化ImageColorTransfer
- 支持动态提示
- 添加更多节点支持，AppInfo自动填充id
- LoadImagesToBatch加载
- zhipuai 按需安装

README.md

@@ -3,13 +3,15 @@
 > [Mixlab nodes discord](https://discord.gg/cXs9vZSqeK)
 
 #### 
+[comfyui-sd-prompt-mixlab](https://github.com/shadowcz007/comfyui-sd-prompt-mixlab)
+
 [comfyui-Image-reward](https://github.com/shadowcz007/comfyui-Image-reward)
 
 [comfyui-ultralytics-yolo](https://github.com/shadowcz007/comfyui-ultralytics-yolo)
 
 [comfyui-moondream](https://github.com/shadowcz007/comfyui-moondream)
 
-[comfyui-CLIPSeg](https://github.com/shadowcz007/comfyui-CLIPSeg)
+<!-- [comfyui-CLIPSeg](https://github.com/shadowcz007/comfyui-CLIPSeg) -->
 
 
 ## 🚀🚗🚚🏃 Workflow-to-APP 
@@ -17,7 +19,9 @@
 - 支持多个web app 切换
 - 发布为app的workflow，可以在右键里再次编辑了
 - web app可以设置分类，在comfyui右键菜单可以编辑更新web app
+- 支持动态提示
 
+![](./assets/微信图片_20240421205440.png)
 
 - Support multiple web app switching.
 - Add the AppInfo node, which allows you to transform the workflow into a web app by simple configuration.

__init__.py

@@ -576,9 +576,6 @@ async def post_prompt_result(request):
     
     return web.json_response({"result":res})
 
-
-
-
 # 扩展api接口
 # from server import PromptServer
 # from aiohttp import web
@@ -599,7 +596,7 @@ from .nodes.ScreenShareNode import ScreenShareNode,FloatingVideo
 from .nodes.ChatGPT import ChatGPTNode,ShowTextForGPT,CharacterInText,TextSplitByDelimiter
 from .nodes.Audio import GamePal,SpeechRecognition,SpeechSynthesis
 from .nodes.Utils import IncrementingListNode,ListSplit,CreateLoraNames,CreateSampler_names,CreateCkptNames,CreateSeedNode,TESTNODE_,TESTNODE_TOKEN,AppInfo,IntNumber,FloatSlider,TextInput,ColorInput,FontInput,TextToNumber,DynamicDelayProcessor,LimitNumber,SwitchByIndex,MultiplicationNode
-from .nodes.Mask import MaskListReplace,MaskListMerge,OutlineMask,FeatheredMask
+from .nodes.Mask import PreviewMask_,MaskListReplace,MaskListMerge,OutlineMask,FeatheredMask
 
 from .nodes.Style import ApplyVisualStylePrompting,StyleAlignedReferenceSampler,StyleAlignedBatchAlign,StyleAlignedSampleReferenceLatents
 
@@ -688,7 +685,8 @@ NODE_CLASS_MAPPINGS = {
     "MaskListReplace_":MaskListReplace,
     "ImageListReplace_":ImageListReplace,
     "VAEEncodeForInpaint_Frames":VAEEncodeForInpaint_Frames,
-    "IncrementingListNode_":IncrementingListNode
+    "IncrementingListNode_":IncrementingListNode,
+    "PreviewMask_":PreviewMask_
     # "GamePal":GamePal
 }
 
@@ -703,7 +701,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "SaveImageAndMetadata_":"Save Image Output ♾️MixlabApp",
     "ResizeImageMixlab":"Resize Image ♾️Mixlab",
     "RandomPrompt": "Random Prompt ♾️Mixlab",
-    "PromptImage":"Output Prompt and Image",
+    "PromptImage":"Output Prompt and Image ♾️Mixlab",
     "SplitLongMask":"Splitting a long image into sections",
     "VAELoaderConsistencyDecoder":"Consistency Decoder Loader",
     "VAEDecodeConsistencyDecoder":"Consistency Decoder Decode",
@@ -715,34 +713,35 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "SpeechSynthesis":"SpeechSynthesis ♾️Mixlab",
     "SpeechRecognition":"SpeechRecognition ♾️Mixlab",
     "3DImage":"3DImage ♾️Mixlab",
-    "CompositeImages_":"Composite Images",
+    "CompositeImages_":"Composite Images ♾️Mixlab",
     "DynamicDelayProcessor":"DynamicDelayByText ♾️Mixlab",
     "LaMaInpainting":"LaMaInpainting ♾️Mixlab",
     "PromptSlide":"Prompt Slide ♾️Mixlab",
     "PromptGenerate_Mix":"Prompt Generate ♾️Mixlab",
     "ChinesePrompt_Mix":"Chinese Prompt ♾️Mixlab",
     "GamePal":"GamePal ♾️Mixlab",
-    "RembgNode_Mix":"Remove Background",
-    "LoraNames_":"LoraName",
-    "ApplyVisualStylePrompting_":"Apply VisualStyle Prompting",
-    "StyleAlignedReferenceSampler_": "StyleAligned Reference Sampler",
-    "StyleAlignedSampleReferenceLatents_": "StyleAligned Sample Reference Latents",
-    "StyleAlignedBatchAlign_": "StyleAligned Batch Align",
-    "LoadVideoAndSegment_":"Load Video And Segment",
-    "VideoCombine_Adv":"Video Combine",
-    "MaskListMerge_":"MaskList to Mask",
-    "ListSplit_":"Split List",
-    "MaskListReplace_":"MaskList Replace",
-    "ImageListReplace_":"ImageList Replace",
-    "SwitchByIndex":"List Switch By Index",
+    "RembgNode_Mix":"Remove Background ♾️Mixlab",
+    "LoraNames_":"LoraName ♾️Mixlab",
+    "ApplyVisualStylePrompting_":"Apply VisualStyle Prompting ♾️Mixlab",
+    "StyleAlignedReferenceSampler_": "StyleAligned Reference Sampler ♾️Mixlab",
+    "StyleAlignedSampleReferenceLatents_": "StyleAligned Sample Reference Latents ♾️Mixlab",
+    "StyleAlignedBatchAlign_": "StyleAligned Batch Align ♾️Mixlab",
+    "LoadVideoAndSegment_":"Load Video And Segment ♾️Mixlab",
+    "VideoCombine_Adv":"Video Combine ♾️Mixlab",
+    "MaskListMerge_":"MaskList to Mask ♾️Mixlab",
+    "ListSplit_":"Split List ♾️Mixlab",
+    "MaskListReplace_":"MaskList Replace ♾️Mixlab",
+    "ImageListReplace_":"ImageList Replace ♾️Mixlab",
+    "SwitchByIndex":"List Switch By Index ♾️Mixlab",
     "GLIGENTextBoxApply_Advanced":"GLIGEN TextBox Apply ♾️Mixlab",
-    "GridDisplayAndSave":"Grid Display And Save",
-    "GridInput":"Grid Input",
-    "GridOutput":"Grid Output",
-    "GetImageSize_":"Get Image Size",
-    "VAEEncodeForInpaint_Frames":"VAE Encode For Inpaint Frames",
-    "IncrementingListNode_":"Create Incrementing Number List",
-    "LoadImagesToBatch":"Load Images To Batch"
+    "GridDisplayAndSave":"Grid Display And Save ♾️Mixlab",
+    "GridInput":"Grid Input ♾️Mixlab",
+    "GridOutput":"Grid Output ♾️Mixlab",
+    "GetImageSize_":"Get Image Size ♾️Mixlab",
+    "VAEEncodeForInpaint_Frames":"VAE Encode For Inpaint Frames ♾️Mixlab",
+    "IncrementingListNode_":"Create Incrementing Number List ♾️Mixlab",
+    "LoadImagesToBatch":"Load Images(base64) ♾️Mixlab",
+    "PreviewMask_":"Preview Mask"
 }
 
 # web ui的节点功能

nodes/ChatGPT.py

@@ -4,8 +4,17 @@ import urllib.error
 import re,json,os,string,random
 import folder_paths
 import hashlib
-import codecs
-from zhipuai import ZhipuAI
+import codecs,sys
+import importlib.util
+
+
+def is_installed(package):
+    try:
+        spec = importlib.util.find_spec(package)
+    except ModuleNotFoundError:
+        return False
+    return spec is not None
+
 
 def get_unique_hash(string):
     hash_object = hashlib.sha1(string.encode())
@@ -48,14 +57,36 @@ def openai_client(key,url):
     base_url=url
     )
     return client
+
 def ZhipuAI_client(key):
+
+    try:
+        if is_installed('zhipuai')==False:
+            import subprocess
+
+            # 安装
+            print('#pip install zhipuai')
+
+            result = subprocess.run([sys.executable, '-s', '-m', 'pip', 'install', 'zhipuai'], capture_output=True, text=True)
+
+            #检查命令执行结果
+            if result.returncode == 0:
+                print("#install success")
+                from zhipuai import ZhipuAI
+            else:
+                print("#install error")
+            
+        else:
+            from zhipuai import ZhipuAI
+    except:
+        print("#install zhipuai error")
+
     client = ZhipuAI(
         api_key=key, # 填写您的 APIKey
     ) 
     return client
 
 
-
 def chat(client, model_name,messages ):
 
         try_count = 0

nodes/ImageNode.py

@@ -16,6 +16,19 @@ import math,glob
 from .Watcher import FolderWatcher
 import hashlib
 
+
+
+# 将PIL图片转换为OpenCV格式
+def pil_to_opencv(image):
+    open_cv_image = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+    return open_cv_image
+
+# 将OpenCV格式图片转换为PIL格式
+def opencv_to_pil(image):
+    pil_image = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
+    return pil_image
+
+
 def composite_images(foreground, background, mask):
     width,height=foreground.size
  
@@ -620,7 +633,7 @@ def detect_faces(image):
 
 def areaToMask(x,y,w,h,image):
     # 创建一个与原图片大小相同的空白图片
-    mask = Image.new('1', image.size)
+    mask = Image.new('L', image.size)
 
     # 创建一个可用于绘制的对象
     draw = ImageDraw.Draw(mask)
@@ -653,7 +666,46 @@ def areaToMask(x,y,w,h,image):
 #     # bg_image.save("output.jpg")
 #     return bg_image
 
-def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option):
+
+import cv2
+import numpy as np
+
+# ps的正片叠底
+# 可以基于https://www.cnblogs.com/jsxyhelu/p/16947810.html ，用gpt写python代码
+def multiply_blend(image1, image2):
+    image1=pil_to_opencv(image1)
+    image2=pil_to_opencv(image2)
+    # 将图像转换为浮点型
+    image1 = image1.astype(float)
+    image2 = image2.astype(float)
+    if image1.shape != image2.shape:
+        image1 = cv2.resize(image1, (image2.shape[1], image2.shape[0]))
+        
+    # 归一化图像
+    image1 /= 255.0
+    image2 /= 255.0
+
+    # 正片叠底混合
+    blended = image1 * image2
+
+    # 将图像还原为8位无符号整数
+    blended = (blended * 255).astype(np.uint8)
+
+    blended=opencv_to_pil(blended)
+    return blended
+
+# # 读取图像
+# image1 = cv2.imread('1.png')
+# image2 = cv2.imread('3.png')
+
+# # 进行正片叠底混合
+# result = multiply_blend(image1, image2)
+
+# cv2.imwrite('result.jpg', result)
+
+
+
+def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option,is_multiply_blend=False):
     # 打开底图
     bg_image = bg_image.convert("RGBA")
 
@@ -682,8 +734,27 @@ def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option)
     nw, nh = layer_image.size
     mask = mask.resize((nw, nh))
 
-    # 在底图上粘贴图层
-    bg_image.paste(layer_image, (x, y), mask=mask)
+    # 分离出a通道
+    r, g, b, alpha = layer_image.split()
+    alpha = ImageOps.invert(alpha)
+    # 创建一个新的RGB图像
+    new_rgb_image = Image.new("RGB", layer_image.size)
+    # 将透明通道粘贴到新的RGB图像上
+    new_rgb_image.paste(layer_image, (0, 0), mask=alpha)
+   
+    new_rgb_image.paste(layer_image, (x, y), mask=mask)
+    mask=new_rgb_image.convert('L')
+    mask = ImageOps.invert(mask)
+
+    if is_multiply_blend:
+        bg_image_white=Image.new("RGB", bg_image.size,(255, 255, 255))
+
+        bg_image_white.paste(layer_image, (x, y), mask=mask)
+        bg_image=multiply_blend(bg_image_white,bg_image)
+        bg_image=bg_image.convert("RGBA")
+    else:
+        # 在底图上粘贴图层
+        bg_image.paste(layer_image, (x, y), mask=mask)
 
     # 输出合成后的图片
     return bg_image
@@ -1517,7 +1588,7 @@ class Image3D:
 
     FUNCTION = "run"
 
-    CATEGORY = "♾️Mixlab/Image"
+    CATEGORY = "♾️Mixlab/3D"
 
     INPUT_IS_LIST = False
     OUTPUT_IS_LIST = (False,False,False,False,)
@@ -1753,7 +1824,7 @@ class NewLayer:
                     "display": "number" # Cosmetic only: display as "number" or "slider"
                 }),
                 "scale_option": (["width","height",'overall'],),
-                "image": ("IMAGE",),
+                "image": (any_type,),
             },
              "optional":{
                     "mask": ("MASK",{"default": None}),
@@ -1810,21 +1881,20 @@ def createMask(image,x,y,w,h):
     # mask.save("mask.png")
     return mask
 
-
 def splitImage(image, num):
     width, height = image.size
 
     num_rows = int(num ** 0.5)
     num_cols = int(num / num_rows)
     
-    grid_width = width // num_cols
-    grid_height = height // num_rows
+    grid_width = int(width // num_cols)
+    grid_height = int(height // num_rows)
 
     grid_coordinates = []
     for i in range(num_rows):
         for j in range(num_cols):
-            x = j * grid_width
-            y = i * grid_height
+            x = int(j * grid_width)
+            y = int(i * grid_height)
             grid_coordinates.append((x, y, grid_width, grid_height))
 
     return grid_coordinates
@@ -2156,12 +2226,16 @@ class GridOutput:
     def INPUT_TYPES(s):
         return { 
             "required": {
-                "grid": ("_GRID",)
-            }
+                "grid": ("_GRID",),
+                
+            },
+            "optional":{
+                  "bg_image":("IMAGE",)
+                }
                 }
     
-    RETURN_TYPES = ("INT","INT","INT","INT",)
-    RETURN_NAMES = ("x","y","width","height",)
+    RETURN_TYPES = ("INT","INT","INT","INT","MASK",)
+    RETURN_NAMES = ("x","y","width","height","mask",)
 
     FUNCTION = "run"
 
@@ -2170,9 +2244,26 @@ class GridOutput:
     INPUT_IS_LIST = False
     # OUTPUT_IS_LIST = (True,)
 
-    def run(self,grid):
+    def run(self,grid,bg_image=None):
         x,y,w,h=grid
-        return (x,y,w,h,)
+        x=int(x)
+        y=int(y)
+        w=int(w)
+        h=int(h)
+
+        masks=[]
+        if bg_image!=None:
+            for i in range(len(bg_image)):
+                im=bg_image[i]
+                #增加输出mask
+                im=tensor2pil(im)
+                mask=areaToMask(x,y,w,h,im)
+                mask=pil2tensor(mask)
+                masks.append(mask)
+        out=None
+        if len(masks)>0:
+            out = torch.cat(masks, dim=0)
+        return (x,y,w,h,out,)
 
 
 
@@ -2267,10 +2358,14 @@ class MergeLayers:
     @classmethod
     def INPUT_TYPES(s):
         return {"required": { 
-            "layers": ("LAYER",),
-            "images": ("IMAGE",),
-                             },
-
+                            "layers": ("LAYER",),
+                            "images": ("IMAGE",),
+                                            },
+            "optional":{
+                           
+                            "is_multiply_blend":  ("BOOLEAN", {"default": False}),
+                            
+                    }
                 }
     
     RETURN_TYPES = ("IMAGE","MASK",)
@@ -2283,11 +2378,12 @@ class MergeLayers:
     INPUT_IS_LIST = True
     # OUTPUT_IS_LIST = (False,)
 
-    def run(self,layers,images):
+    def run(self,layers,images,is_multiply_blend):
 
         bg_images=[]
         masks=[]
- 
+        
+        is_multiply_blend=is_multiply_blend[0]
         # print(len(images),images[0].shape)
         # 1  torch.Size([2, 512, 512, 3])
         # 4  torch.Size([1, 1024, 768, 3])
@@ -2318,6 +2414,8 @@ class MergeLayers:
                     
                     layer_image=tensor2pil(image)
                     layer_mask=tensor2pil(mask)
+                    # t=layer_image.convert("RGBA")
+                    # t.save('test.png') 如果layerimage传入的是rgba，则是透明的
                     bg_image=merge_images(bg_image,
                                         layer_image,
                                         layer_mask,
@@ -2325,7 +2423,8 @@ class MergeLayers:
                                         layer['y'],
                                         layer['width'],
                                         layer['height'],
-                                        layer['scale_option']
+                                        layer['scale_option'],
+                                        is_multiply_blend
                                         )
                     
                     final_mask=merge_images(final_mask,
@@ -2738,6 +2837,7 @@ class ImageColorTransfer:
         return {"required": {
                 "source": ("IMAGE",),
                 "target": ("IMAGE",),
+                "weight": ("FLOAT", {"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01}),
                 },
                 }
     
@@ -2751,25 +2851,45 @@ class ImageColorTransfer:
     CATEGORY = "♾️Mixlab/Color"
 
     # 输入是否为列表
-    INPUT_IS_LIST = True
+    # INPUT_IS_LIST = True
 
     # 输出是否为列表
-    OUTPUT_IS_LIST = (True,)
+    # OUTPUT_IS_LIST = (True,)
 
-    def run(self,source,target):
+    def run(self,source,target,weight):
 
         res=[]
 
-        target=target[0][0]
-        print(target.shape)
-        target=tensor2pil(target)
+        #batch-list
+        source_list = [source[i:i + 1, ...] for i in range(source.shape[0])]
+        target_list = [target[i:i + 1, ...] for i in range(target.shape[0])]
 
-        for ims in source:
-            for im in ims:
-                image=tensor2pil(im)
-                image=color_transfer(image,target)
-                image=pil2tensor(image)
-                res.append(image)
+        # 长度纠正为相等
+        if len(target_list) != len(source_list):
+            target_list = target_list * (len(source_list) // len(target_list)) + target_list[:len(source_list) % len(target_list)]
+        
+        for i in range(len(source_list)):
+            target=target_list[i]
+            source=source_list[i]
+            target=tensor2pil(target)
+
+            image=tensor2pil(source)
+
+            image_res=color_transfer(image,target)
+
+            # weight Blend image # contributors:@ning
+            blend_mask = Image.new(mode="L", size=image.size,
+                                    color=(round(weight * 255)))
+            blend_mask = ImageOps.invert(blend_mask)
+            img_result = Image.composite(image, image_res, blend_mask)
+            del image, image_res, blend_mask
+            
+            img_result=pil2tensor(img_result)
+
+            res.append(img_result)
+
+        # list - batch
+        res=torch.cat(res, dim=0)
 
         return (res,)
 

nodes/Mask.py

@@ -2,16 +2,14 @@
 import scipy.ndimage
 import torch
 
-from nodes import MAX_RESOLUTION
-
 import numpy as np 
 # from PIL import Image, ImageDraw
 from PIL import Image, ImageOps 
 
 from comfy.cli_args import args
-import cv2
-
-
+import cv2,os
+from nodes import MAX_RESOLUTION, SaveImage, common_ksampler
+import folder_paths,random
 
 # Tensor to PIL
 def tensor2pil(image):
@@ -71,6 +69,35 @@ def combine(destination, source, x, y):
 
     return output
 
+
+class PreviewMask_(SaveImage):
+    def __init__(self):
+        self.output_dir = folder_paths.get_temp_directory()
+        self.type = "temp"
+        self.prefix_append =''.join(random.choice("abcdehijklmnopqrstupvxyzfg") for x in range(5))
+        self.compress_level = 4
+
+    @classmethod
+    def INPUT_TYPES(s):
+        return {
+                "required": {
+                                "mask": ("MASK",), 
+                            }
+            }
+    
+    RETURN_TYPES = ()
+    OUTPUT_NODE = True
+    FUNCTION = "run"
+    CATEGORY = "♾️Mixlab/Mask"
+
+    # 运行的函数
+    def run(self, mask ):
+        img=tensor2pil(mask)
+        img=img.convert('RGB')
+        img=pil2tensor(img) 
+        return self.save_images(img, 'temp_', None,  None)
+
+
 class OutlineMask:
 
     @classmethod

requirements.txt

@@ -7,6 +7,6 @@ openai
 simple-lama-inpainting
 clip-interrogator==0.6.0
 transformers>=4.36.0
-zhipuai
 lark-parser
-imageio-ffmpeg
+imageio-ffmpeg
+rembg[gpu]

web/index.html

@@ -278,8 +278,11 @@
         }
 
         button:hover {
-            border-color: yellow !important;
-            color: yellow !important;
+            /* border-color: yellow !important; */
+            color: #ffffff !important;
+            /* font-weight: 400; */
+            background: #232222;
+            cursor: pointer;
         }
 
         .disabled {
@@ -400,12 +403,53 @@
         .hidden-caption-content {
             display: none;
         }
+
+         /* 定义滚动条轨道的背景颜色 */
+
+         ::-webkit-scrollbar-track {
+            background-color: #f1f1f1;
+            /* 轨道背景颜色 */
+        }
+
+        /* 定义滚动条滑块的颜色 */
+
+        ::-webkit-scrollbar-thumb {
+            background-color: #888;
+            /* 滑块颜色 */
+            border-radius: 4px;
+            /* 滑块圆角 */
+        }
+
+        /* 鼠标悬停时滚动条滑块的颜色 */
+
+        ::-webkit-scrollbar-thumb:hover {
+            background-color: #555;
+            /* 悬停时滑块颜色 */
+        }
+
+        /* 定义滚动条角落的颜色 */
+
+        ::-webkit-scrollbar-corner {
+            background-color: transparent;
+            /* 角落颜色 */
+        }
+
+
+        .dynamic_prompt::after {
+            content: attr(title);
+            position: absolute; 
+            color: black;
+            padding: 4px;
+            padding-left: 25px;
+            border-radius: 4px;
+        }
     </style>
     <!-- <script src="../../../scripts/api.js" type="module"></script> -->
     <link href="/extensions/comfyui-mixlab-nodes/lib/photoswipe.min.css" rel="stylesheet">
     <link href="/extensions/comfyui-mixlab-nodes/lib/classic.min.css" rel="stylesheet">
     <script src="/extensions/comfyui-mixlab-nodes/lib/pickr.min.js"></script>
     <script src="/extensions/comfyui-mixlab-nodes/lib/filerobot-image-editor.min.js"></script>
+    <script type="module" src="/extensions/comfyui-mixlab-nodes/lib/model-viewer.min.js"></script>
     <link rel="stylesheet" href="/extensions/comfyui-mixlab-nodes/lib/login.css">
 </head>
 
@@ -439,8 +483,39 @@
     <script type="module">
         import PhotoSwipeLightbox from '/extensions/comfyui-mixlab-nodes/lib/photoswipe-lightbox.esm.min.js'
         // console.log(Lightbox)
-
         import { api } from "../../../scripts/api.js";
+
+
+        // ComfyUI\web\extensions\core\dynamicPrompts.js
+        // 官方实现修改
+        // Allows for simple dynamic prompt replacement
+        // Inputs in the format {a|b} will have a random value of a or b chosen when the prompt is queued.
+
+        /*
+         * Strips C-style line and block comments from a string
+         */
+        function stripComments(str) {
+            return str.replace(/\/\*[\s\S]*?\*\/|\/\/.*/g, '');
+        }
+
+        function dynamicPrompts(prompt) {
+            prompt = stripComments(prompt);
+            while (prompt.replace("\\{", "").includes("{") && prompt.replace("\\}", "").includes("}")) {
+                const startIndex = prompt.replace("\\{", "00").indexOf("{");
+                const endIndex = prompt.replace("\\}", "00").indexOf("}");
+
+                const optionsString = prompt.substring(startIndex + 1, endIndex);
+                const options = optionsString.split("|");
+
+                const randomIndex = Math.floor(Math.random() * options.length);
+                const randomOption = options[randomIndex];
+
+                prompt = prompt.substring(0, startIndex) + randomOption + prompt.substring(endIndex + 1);
+            }
+            return prompt
+        }
+
+
         // console.log('api', api)
         const base64Df =
             'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAwAAAAMCAYAAABWdVznAAAAAXNSR0IArs4c6QAAALZJREFUKFOFkLERwjAQBPdbgBkInECGaMLUQDsE0AkRVRAYWqAByxldPPOWHwnw4OBGye1p50UDSoA+W2ABLPN7i+C5dyC6R/uiAUXRQCs0bXoNIu4QPQzAxDKxHoALOrZcqtiyR/T6CXw7+3IGHhkYcy6BOR2izwT8LptG8rbMiCRAUb+CQ6WzQVb0SNOi5Z2/nX35DRyb/ENazhpWKoGwrpD6nICp5c2qogc4of+c7QcrhgF4Aa/aoAFHiL+RAAAAAElFTkSuQmCC'
@@ -498,6 +573,39 @@
             })
         }
 
+        //给load image to batch节点使用的输入
+        function createBase64ImageForLoadImageToBatch(imageElement, nodeId, bs) {
+            let im = new Image()
+            im.src = bs;
+            im.className = "base64"
+            imageElement.appendChild(im);
+
+            let base64s = imageElement.querySelectorAll('.base64')
+            //更新输入
+            window._appData.data[nodeId].inputs.images.base64 = Array.from(base64s, (b) => b.src)
+
+            // 删除
+            im.addEventListener('click', e => {
+                e.preventDefault();
+                im.remove();
+                let base64s = imageElement.querySelectorAll('.base64')
+                //更新输入
+                window._appData.data[nodeId].inputs.images.base64 = Array.from(base64s, (b) => b.src)
+            })
+        }
+
+        const blobToBase64 = blob => {
+            return new Promise((res, rej) => {
+                const reader = new FileReader()
+                reader.onloadend = () => {
+                    const base64data = reader.result
+                    res(base64data)
+                    // 在这里可以将base64数据用于进一步处理或显示图片
+                }
+                reader.readAsDataURL(blob)
+            })
+        }
+
 
         function base64ToBlob(base64) {
             // 去除base64编码中的前缀
@@ -712,7 +820,7 @@
                     data[id].inputs.noise_seed = Math.round(Math.random() * max_seed)
                 }
                 // class_type:"Seed_"
-                if (data[id].class_type == "Seed_") {
+                if (data[id].class_type == "Seed_" && ['increment', 'decrement', 'randomize'].includes(seed[id])) {
                     data[id].inputs.seed = Math.round(Math.random() * max_seed)
                 }
                 console.log('new Seed', data[id])
@@ -737,6 +845,21 @@
             // 随机seed
             promptWorkflow = randomSeed(seed, promptWorkflow);
 
+            // //动态提示,改为输入的时候，手动触发
+            // for (const id in promptWorkflow) {
+            //     let node = promptWorkflow[id]
+            //     if (["TextInput_", "CLIPTextEncode", "PromptSimplification", "ChinesePrompt_Mix"].includes(
+            //         node.class_type
+            //     )) {
+            //         if (node.class_type == "PromptSimplification") {
+            //             promptWorkflow[id].inputs.prompt = dynamicPrompts(node.inputs.prompt);
+            //         } else {
+            //             promptWorkflow[id].inputs.text = dynamicPrompts(node.inputs.text);
+            //         }
+            //         console.log('#动态提示', promptWorkflow[id].inputs)
+            //     }
+            // }
+
             let url = get_url()
             const data = JSON.stringify({ prompt: promptWorkflow, client_id });
             fetch(`${url}/prompt`, {
@@ -912,6 +1035,9 @@
                 // copyImagesToClipboard(output_card.outerHTML)
             })
 
+            //是否显示复制图片，复制html两个按钮
+            let isShowImageFn = false;
+
             for (const node of outputData) {
                 // console.log('output', node)
                 if (node.class_type == "ShowTextForGPT") {
@@ -930,8 +1056,31 @@
                     output_card.appendChild(div);
                 };
 
-                if (["SaveImage", "PreviewImage", "PromptImage", "Image Save", "SaveImageAndMetadata_"].includes(node.class_type)) {
+                if (["SaveImage",
+                    "PreviewImage",
+                    "PromptImage",
+                    "Image Save",
+                    "SaveImageAndMetadata_",
+                    "TransparentImage"].includes(node.class_type)) {
+                    console.log('output#image', node)
+                    let a = document.createElement('a');
+                    a.id = `output_${node.id}`
+                    a.setAttribute('data-pswp-width', "200");
+                    a.setAttribute('data-pswp-height', "200");
+                    a.setAttribute('target', "_blank");
+                    a.setAttribute('href', base64Df);
+                    a.setAttribute('title', node.title);
 
+                    let img = new Image();
+                    // img;
+                    img.src = window._appData?.icon || base64Df;
+                    a.appendChild(img)
+                    output_card.appendChild(a);
+                    isShowImageFn = true;
+                }
+
+                //3d 
+                if (["SaveTripoSRMesh"].includes(node.class_type)) {
                     let a = document.createElement('a');
                     a.id = `output_${node.id}`
                     a.setAttribute('data-pswp-width', "200");
@@ -947,7 +1096,7 @@
                 }
 
                 // video ,gif
-                if (["VHS_VideoCombine"].includes(node.class_type)) {
+                if (["VHS_VideoCombine", "VideoCombine_Adv"].includes(node.class_type)) {
 
                     let a = document.createElement('a');
                     a.id = `output_${node.id}`
@@ -974,6 +1123,12 @@
                 }
 
             }
+
+            if (isShowImageFn === false) {
+                copyImage.remove();
+                copyHTML.remove();
+            }
+
             return container
         }
 
@@ -1030,6 +1185,7 @@
         }
 
         async function handleClipboardImage(imageElement, data) {
+            //data.class_type === 'LoadImagesToBatch'
             try {
                 const clipboardItems = await navigator.clipboard.read();
                 for (const clipboardItem of clipboardItems) {
@@ -1042,18 +1198,17 @@
 
                             if (hashId == window._appData.data[data.id].hashId) return
 
-                            let { url, name } = await uploadImage(fileBlob);
-                            // 在这里可以对 Blob 对象进行进一步处理
-                            imageElement.src = url;
-                            window._appData.data[data.id].inputs.image = name;
-                            window._appData.data[data.id].hashId = hashId;
-
-                            console.log("上传的文件：", url, data.id, name);
-
-                            // const img = document.createElement('img');
-                            // img.src = URL.createObjectURL(blob);
-                            // document.body.appendChild(img);
-                            // console.log( URL.createObjectURL(blob));
+                            if (data.class_type === 'LoadImagesToBatch') {
+                                let base64 = await blobToBase64(fileBlob)
+                                createBase64ImageForLoadImageToBatch(imageElement, data.id, base64)
+                            } else {
+                                let { url, name } = await uploadImage(fileBlob);
+                                // 在这里可以对 Blob 对象进行进一步处理
+                                imageElement.src = url;
+                                window._appData.data[data.id].inputs.image = name;
+                                window._appData.data[data.id].hashId = hashId;
+                                console.log("上传的文件：", url, data.id, name);
+                            }
                         }
                     }
                 }
@@ -1217,10 +1372,16 @@
                 console.log('inputData', data);
 
                 // 图片 or 视频输入
-                if (data.class_type === "LoadImage" || data.class_type === "VHS_LoadVideo" || data.class_type === 'ImagesPrompt_') {
+
+                if (["LoadImage",
+                    "VHS_LoadVideo",
+                    "ImagesPrompt_",
+                    "LoadImagesToBatch"].includes(data.class_type)) {
 
                     let isVideoUpload = data.class_type === "VHS_LoadVideo";
 
+                    let isBase64Upload = data.class_type === "LoadImagesToBatch";
+
                     // Create a container for the upload control
                     const uploadContainer = document.createElement("div");
                     uploadContainer.className = 'card';
@@ -1252,7 +1413,7 @@
                     const btnForImageEdit = document.createElement("button");
                     btnForImageEdit.style = ` width: 32px; background: none;margin-left: 18px;`
                     btnForImageEdit.innerHTML = '<?xml version="1.0" ?><svg version="1.1" style="width: 24px;" viewBox="0 0 50 50" xml:space="preserve" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g id="Layer_1_1_"><path d="M18.293,31.707h6.414l24-24l-6.414-6.414l-24,24V31.707z M45.879,7.707l-3.586,3.586l-3.586-3.586l3.586-3.586   L45.879,7.707z M20.293,26.121l17-17l3.586,3.586l-17,17h-3.586V26.121z"/><polygon points="43.293,19.707 41.293,19.707 41.293,46.707 3.293,46.707 3.293,8.707 31.293,8.707 31.293,6.707 1.293,6.707    1.293,48.707 43.293,48.707  "/></g></svg>'
-                    if (!isVideoUpload && data.class_type !== 'ImagesPrompt_') actionDiv.appendChild(btnForImageEdit);
+                    if ((!isVideoUpload && !isBase64Upload) && data.class_type !== 'ImagesPrompt_') actionDiv.appendChild(btnForImageEdit);
 
 
                     uploadContainer.appendChild(actionDiv)
@@ -1299,6 +1460,16 @@
                             })
                         uploadContainer.appendChild(imgDiv);
                         window._appData.data[data.id].inputs.image_base64 = mainImage.querySelector('.images_prompt_main').src;
+                    } else if (data.class_type === 'LoadImagesToBatch') {
+                        // 多张base64 图片
+                        let base64 = data.inputs.images.base64
+
+                        imageElement = document.createElement('div');
+                        imageElement.className = "images"
+                        for (const bs of base64) {
+                            createBase64ImageForLoadImageToBatch(imageElement, data.id, bs)
+                        }
+
                     }
 
 
@@ -1306,7 +1477,7 @@
 
                     if (!isVideoUpload) btnFromClipboard.addEventListener('click', (event) => handleClipboardImage(imageElement, data));
 
-                    if (!isVideoUpload) btnForImageEdit.addEventListener('click', e => editImage(imageElement, data))
+                    if (!isVideoUpload && !isBase64Upload) btnForImageEdit.addEventListener('click', e => editImage(imageElement, data))
 
 
                     uploadImageInput.addEventListener('click', (event) => {
@@ -1329,33 +1500,43 @@
 
                             if (hashId == window._appData.data[data.id].hashId) return
 
-                            let { url, name } = await uploadImage(fileBlob, '.' + file.type.split('/')[1])
-
-                            if (data.class_type === 'ImagesPrompt_') {
-                                // 
-                                let base64 = await parseImageToBase64(url);
-                                uploadContainer.querySelector('.images_prompt_main').src = base64
-                                window._appData.data[data.id].inputs.image_base64 = base64;
+                            if (data.class_type === 'LoadImagesToBatch') {
+                                // 上传 ，转为base64
+                                let base64 = await blobToBase64(fileBlob)
+                                createBase64ImageForLoadImageToBatch(imageElement, data.id, base64)
                             } else {
-                                if (isVideoUpload) {
-                                    imageElement.srcObject = null;
-                                }
-                                // 在这里可以对 Blob 对象进行进一步处理
-                                imageElement.src = url;
+                                //上传，返回url
+                                let { url, name } = await uploadImage(fileBlob, '.' + file.type.split('/')[1])
 
-
-                                if (isVideoUpload) {
-                                    window._appData.data[data.id].inputs.video = name;
+                                if (data.class_type === 'ImagesPrompt_') {
+                                    // 
+                                    let base64 = await parseImageToBase64(url);
+                                    uploadContainer.querySelector('.images_prompt_main').src = base64
+                                    window._appData.data[data.id].inputs.image_base64 = base64;
                                 } else {
-                                    window._appData.data[data.id].inputs.image = name;
+                                    if (isVideoUpload) {
+                                        imageElement.srcObject = null;
+                                    }
+                                    // 在这里可以对 Blob 对象进行进一步处理
+                                    imageElement.src = url;
+
+
+                                    if (isVideoUpload) {
+                                        window._appData.data[data.id].inputs.video = name;
+                                    } else {
+                                        window._appData.data[data.id].inputs.image = name;
+                                    }
+
                                 }
 
+
+                                window._appData.data[data.id].hashId = hashId;
+
+                                console.log("上传的文件：", url, data.id, name);
                             }
 
 
-                            window._appData.data[data.id].hashId = hashId;
 
-                            console.log("上传的文件：", url, data.id, name);
                         };
 
                         // 开始读取文件
@@ -1442,7 +1623,7 @@
                         textInput.value = data.inputs.prompt;
                     } else {
                         textInput.value = data.inputs.text;
-                    }
+                    };
 
                     // uploadImageInput.type = "text";
                     let json = localStorage.getItem(`t_${data.id}`)
@@ -1458,7 +1639,6 @@
                             window._appData.data[data.id].inputs.text = textInput.value;
                         }
 
-
                     } catch (error) {
 
                     }
@@ -1466,6 +1646,27 @@
                     uploadContainer.appendChild(textInput);
                     // autoResize(textInput);
 
+
+                    //动态提示功能
+                    const dynamicPromptsBtn = document.createElement('button');
+                    dynamicPromptsBtn.className = "dynamic_prompt"
+                    dynamicPromptsBtn.innerText = 'dynamic';
+                    dynamicPromptsBtn.style.width = '88px'
+                    uploadContainer.appendChild(dynamicPromptsBtn);
+                    dynamicPromptsBtn.addEventListener('click', e => {
+                        e.preventDefault();
+                        e.stopPropagation();
+                        let prompt = dynamicPrompts(textInput.value)
+                        textInput.setAttribute('title', prompt)
+                        dynamicPromptsBtn.setAttribute('title', prompt)
+                        if (data.class_type == "PromptSimplification") {
+                            window._appData.data[data.id].inputs.prompt = prompt;
+                        } else {
+                            window._appData.data[data.id].inputs.text = prompt;
+                        }
+                    })
+
+
                     function autoResize(textarea) {
                         textarea.style.height = 'auto';
                         textarea.style.height = textarea.scrollHeight + 'px';
@@ -2201,6 +2402,51 @@
 
                         if (val && type == "text" && output.querySelector(`#output_${id}`)) output.querySelector(`#output_${id}`).innerText = val;
 
+                        // 3d meshes
+                        if (val && type == 'meshes' && output.querySelector(`#output_${id}`)) {
+
+                            let threeD = output.querySelector('.threeD')
+                            //判断默认的图片，需要去掉后创建model-viewer
+                            let imgDf = output.querySelector(`#output_${id} img`);
+                            if (!threeD) {
+                                if (imgDf) imgDf.parentElement.remove();
+                                threeD = document.createElement('div');
+                                threeD.className = 'threeD'
+                                threeD.id = `output_${id}`
+                                output.querySelector('.output_card').appendChild(threeD)
+                                // output.insertBefore(threeD, output.firstChild);
+                            };
+
+
+                            for (const meshUrl of val) {
+                                const modelViewer = document.createElement('div');
+                                modelViewer.style = `width:300px;margin:4px;height:300px;display:block`
+                                modelViewer.innerHTML = `<model-viewer  src="${meshUrl}" 
+                                    min-field-of-view="0deg" max-field-of-view="180deg"
+                                    shadow-intensity="1" 
+                                    camera-controls 
+                                    touch-action="pan-y"
+                                    style="width:300px;height:300px;"
+                                    > 
+                                    <div class="controls">
+                                        <button class="export">Save As</button>
+                                    </div>
+                                </model-viewer>`
+
+                                const btn = modelViewer.querySelector('.export');
+                                btn.addEventListener('click', async e => {
+                                    e.preventDefault();
+                                    const glTF = await (modelViewer.querySelector('model-viewer')).exportScene()
+                                    const file = new File([glTF], 'mixlab.glb')
+                                    const link = document.createElement('a')
+                                    link.download = file.name
+                                    link.href = URL.createObjectURL(file)
+                                    link.click()
+                                })
+                                threeD.appendChild(modelViewer)
+                            }
+
+                        }
                     }
                 },
                 submitButton: {
@@ -2316,6 +2562,9 @@
             const _images = detail?.output?._images;
             const prompts = detail?.output?.prompts;
 
+            // 3d模型
+            const meshes = detail?.output?.mesh;
+
             if (images) {
                 // if (!images) return;
 
@@ -2325,6 +2574,14 @@
                     return `${url}/view?filename=${encodeURIComponent(img.filename)}&type=${img.type}&subfolder=${encodeURIComponent(img.subfolder)}&t=${+new Date()}`;
                 }), detail.node, 'images');
 
+            } else if (meshes) {
+                //多个
+                let url = get_url();
+
+                show(Array.from(meshes, mesh => {
+                    return `${url}/view?filename=${encodeURIComponent(mesh.filename)}&type=${mesh.type}&subfolder=${encodeURIComponent(mesh.subfolder)}&t=${+new Date()}`;
+                }), detail.node, 'meshes');
+
             } else if (_images && prompts) {
                 let url = get_url();
 
@@ -2558,6 +2815,9 @@
         // 创建app的选择菜单
         function createAppList(apps = [], innerApp = false) {
             window.prompt_ids = {};
+            if (document.body.querySelector('.apps')) {
+                document.body.querySelector('.apps').remove()
+            }
             let details = document.createElement('details');
             details.className = 'apps';
 
@@ -2758,20 +3018,21 @@
                 card.addEventListener('click', async e => {
                     e.preventDefault();
                     // console.log(c)
+
+                    const { category, filename } = c.appInfo;
+                    window._appData = (await get_my_app(category, filename))[0];
+
+                    await createApp(window._appData);
+
+                    executed(c.data, window._show);
+
                     try {
                         document.body.querySelector('#app_container').setAttribute('open', true)
                         document.body.querySelector('#app_input_pannel').removeAttribute('open')
                         document.body.querySelector('.apps').removeAttribute('open')
                     } catch (error) {
-
+                        console.log(error)
                     }
-
-                    const { category, filename } = c.appInfo;
-                    window._appData = (await get_my_app(category, filename))[0];
-
-                    createApp(window._appData);
-
-                    executed(c.data, window._show);
                 })
             }
 

web/javascript/app_mixlab.js

@@ -2,6 +2,24 @@ import { app } from '../../../scripts/app.js'
 import { $el } from '../../../scripts/ui.js'
 import { api } from '../../../scripts/api.js'
 
+//本机安装的插件节点全集
+window._nodesAll = null
+
+//获取当前系统的插件，节点清单
+function getObjectInfo () {
+  return new Promise(async (resolve, reject) => {
+    let url = getUrl()
+
+    try {
+      const response = await fetch(`${url}/object_info`)
+      const data = await response.json()
+      resolve(data)
+    } catch (error) {
+      reject(error)
+    }
+  })
+}
+
 const base64Df =
   'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAwAAAAMCAYAAABWdVznAAAAAXNSR0IArs4c6QAAALZJREFUKFOFkLERwjAQBPdbgBkInECGaMLUQDsE0AkRVRAYWqAByxldPPOWHwnw4OBGye1p50UDSoA+W2ABLPN7i+C5dyC6R/uiAUXRQCs0bXoNIu4QPQzAxDKxHoALOrZcqtiyR/T6CXw7+3IGHhkYcy6BOR2izwT8LptG8rbMiCRAUb+CQ6WzQVb0SNOi5Z2/nX35DRyb/ENazhpWKoGwrpD6nICp5c2qogc4of+c7QcrhgF4Aa/aoAFHiL+RAAAAAElFTkSuQmCC'
 
@@ -197,7 +215,8 @@ async function extractInputAndOutputData (
       if (
         node.type === 'KSampler' ||
         node.type == 'SamplerCustom' ||
-        node.type === 'ChinesePrompt_Mix'
+        node.type === 'ChinesePrompt_Mix' ||
+        node.type === 'Seed_'
       ) {
         // seed 的类型收集
         try {
@@ -266,7 +285,10 @@ function downloadJsonFile (jsonData, fileName = 'mix_app.json') {
 }
 
 async function save (json, download = false, showInfo = true) {
-  console.log('####SAVE', json[0])
+  let nodesAll = window._nodesAll || (await getObjectInfo())
+
+  console.log('####SAVE', nodesAll, json[0])
+
   const name = json[0],
     version = json[5],
     share_prefix = json[6], //用于分享的功能扩展
@@ -287,6 +309,13 @@ async function save (json, download = false, showInfo = true) {
   try {
     let data = await app.graphToPrompt()
 
+    //从output数据里把工作流的节点，插件数据统计出来
+    data.nodesMap = {}
+    for (const id in data.output) {
+      data.nodesMap[data.output[id].class_type] =
+        nodesAll[data.output[id].class_type]
+    }
+
     let { input, output, seed, seedTitle } = await extractInputAndOutputData(
       data,
       inputIds,
@@ -349,11 +378,11 @@ async function save (json, download = false, showInfo = true) {
 
 function getInputsAndOutputs () {
   const inputs =
-      `LoadImage ImagesPrompt_ VHS_LoadVideo CLIPTextEncode PromptSlide TextInput_ Color FloatSlider IntNumber CheckpointLoaderSimple LoraLoader`.split(
+      `LoadImage LoadImagesToBatch ImagesPrompt_ VHS_LoadVideo CLIPTextEncode PromptSlide TextInput_ Color FloatSlider IntNumber CheckpointLoaderSimple LoraLoader`.split(
         ' '
       ),
     outputs =
-      `PreviewImage,SaveImage,ShowTextForGPT,VHS_VideoCombine,Image Save,SaveImageAndMetadata_`.split(
+      `SaveTripoSRMesh,PreviewImage,SaveImage,TransparentImage,ShowTextForGPT,VHS_VideoCombine,VideoCombine_Adv,Image Save,SaveImageAndMetadata_,ClipInterrogator`.split(
         ','
       )
 
@@ -378,6 +407,11 @@ function getInputsAndOutputs () {
 
 app.registerExtension({
   name: 'Mixlab.utils.AppInfo',
+  init () {
+    if (!window._nodesAll) {
+      getObjectInfo().then(r => (window._nodesAll = r))
+    }
+  },
   async beforeRegisterNodeDef (nodeType, nodeData, app) {
     if (nodeType.comfyClass == 'AppInfo') {
       const orig_nodeCreated = nodeType.prototype.onNodeCreated

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 = 'v0.20.0'
+const version = 'v0.22.1'
 
 fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
   .then(response => response.json())
@@ -17,7 +17,13 @@ fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
       return
     if (latestVersion && latestVersion != version) {
       localStorage.setItem('_mixlab_nodes_vesion', latestVersion)
-      app.ui.dialog.show(`<h4 style="font-size: 18px;">${repoName} <br>
+      app.ui.dialog.show(`<a style="color: white;
+      font-size: 18px;
+      font-weight: 800;
+      letter-spacing: 2px;
+    }"
+    href="https://discord.gg/cXs9vZSqeK">Welcome to Mixlab nodes discord</a>
+    <h4 style="font-size: 18px;">${repoName} <br>
       Latest release version: ${latestVersion}</h4>
       <p>Please proceed to the official repository to download the latest version.</p>
       <a style="color: #2196F3;

web/javascript/image_mixlab.js

@@ -1,7 +1,39 @@
 import { app } from '../../../scripts/app.js'
 import { api } from '../../../scripts/api.js'
-import { ComfyWidgets } from '../../../scripts/widgets.js'
+// import { ComfyWidgets } from '../../../scripts/widgets.js'
 import { $el } from '../../../scripts/ui.js'
+import { applyTextReplacements } from '../../../scripts/utils.js'
+
+function loadImageToCanvas (base64Image) {
+  var img = new Image()
+  var canvas = document.createElement('canvas')
+  var ctx = canvas.getContext('2d')
+  return new Promise((res, rej) => {
+    img.onload = function () {
+      // 等比例缩放图片
+      var width = img.width
+      var height = img.height
+      var max_width = 1024
+      if (width > max_width) {
+        height *= max_width / width
+        width = max_width
+      }
+
+      // 设置canvas尺寸
+      canvas.width = width
+      canvas.height = height
+
+      // 在canvas上绘制图片
+      ctx.drawImage(img, 0, 0, width, height)
+
+      // 将canvas转换为base64图片数据
+      var canvasData = canvas.toDataURL()
+      res(canvasData) //  canvas转换后的base64图片数据
+    }
+
+    img.src = base64Image
+  })
+}
 
 async function uploadImage (blob, fileType = '.svg', filename) {
   // const blob = await (await fetch(src)).blob();
@@ -632,11 +664,11 @@ const createInputImageForBatch = (base64, widget) => {
 
   im.addEventListener('click', e => {
     let newValue = []
-    let items=widget.value?.base64||[];
+    let items = widget.value?.base64 || []
     for (const v of items) {
       if (v != base64) newValue.push(v)
     }
-    widget.value.base64=newValue;
+    widget.value.base64 = newValue
     im.remove()
   })
 
@@ -651,7 +683,7 @@ app.registerExtension({
         // console.log('##node', node)
         const widget = {
           value: {
-            base64:[]
+            base64: []
           }, // 不能[x,x,x]
           type: inputData[0], // the type
           name: inputName, // the name, slice
@@ -659,7 +691,7 @@ app.registerExtension({
           draw (ctx, node, width, y) {},
           computeSize (...args) {
             return [128, 32] // a method to compute the current size of the widget
-          },
+          }
           // serializeValue (nodeId, widgetIndex) {
           //   return widget.value
           // },
@@ -688,7 +720,7 @@ app.registerExtension({
               get_position_style(ctx, widget_width, 44, node.size[1])
             )
           },
-          serialize:false
+          serialize: false
         }
 
         widget.div = $el('div', {})
@@ -703,25 +735,48 @@ app.registerExtension({
         flex-wrap: wrap;
         padding: 7px;    justify-content: space-between;
         align-items: center;`
+
         let inputImage = document.createElement('input')
         inputImage.type = 'file'
+        inputImage.style.display = 'none'
         inputImage.addEventListener('change', e => {
           e.preventDefault()
           const file = e.target.files[0]
           const reader = new FileReader()
           reader.onload = async event => {
-            const base64 = event.target.result
+            let base64 = event.target.result
+            //压缩图片，控制1024以内
+            base64 = await loadImageToCanvas(base64)
             // console.log(base64)
-            if (!imagesWidget.value) imagesWidget.value = {base64:[]}
+            if (!imagesWidget.value) imagesWidget.value = { base64: [] }
             imagesWidget.value.base64.push(base64)
-            let im = createInputImageForBatch(base64,imagesWidget)
+            let im = createInputImageForBatch(base64, imagesWidget)
             imagesDiv.appendChild(im)
           }
           reader.readAsDataURL(file)
         })
 
+        const btn = document.createElement('button')
+        btn.innerText = 'Upload Image'
+
+        btn.style = `cursor: pointer;
+        font-weight: 300;
+        margin: 2px; 
+        color: var(--descrip-text);
+        background-color: var(--comfy-input-bg);
+        border-radius: 8px;
+        border-color: var(--border-color);
+        border-style: solid;height: 30px;min-width: 122px;
+       `
+
+        btn.addEventListener('click', e => {
+          e.preventDefault()
+          inputImage.click()
+        })
+
         widget.div.appendChild(imagePreview)
         imagePreview.appendChild(imagesDiv)
+        imagePreview.appendChild(btn)
         imagePreview.appendChild(inputImage)
 
         this.addCustomWidget(widget)
@@ -744,6 +799,33 @@ app.registerExtension({
         this.serialize_widgets = true //需要保存参数
       }
     }
+
+    if (nodeData.name === 'SaveImageAndMetadata_') {
+      const onNodeCreated = nodeType.prototype.onNodeCreated
+      // /web/extensions/core/saveImageExtraOutput.js
+      nodeType.prototype.onNodeCreated = function () {
+        const r = onNodeCreated
+          ? onNodeCreated.apply(this, arguments)
+          : undefined
+        const widget = this.widgets.find(w => w.name === 'filename_prefix')
+        widget.serializeValue = () => {
+          return applyTextReplacements(app, widget.value)
+        }
+
+        return r
+      }
+
+      const onExecuted = nodeType.prototype.onExecuted
+      nodeType.prototype.onExecuted = function (message) {
+        onExecuted?.apply(this, arguments)
+        console.log('##onExecuted', this, message)
+        //TODO 是否 保存base64
+        if (message.base64) {
+          if (Array.isArray(message.base64)) {
+          }
+        }
+      }
+    }
   },
   async loadedGraphNode (node, app) {
     if (node.type === 'LoadImagesToBatch') {
@@ -753,7 +835,7 @@ app.registerExtension({
 
       let pre = imagePreview.div.querySelector('.images_preview')
       for (const d of imagesWidget.value?.base64 || []) {
-        let im =  createInputImageForBatch(d,imagesWidget)
+        let im = createInputImageForBatch(d, imagesWidget)
         pre.appendChild(im)
       }
     }

web/javascript/smart_connect.js

@@ -46,6 +46,18 @@ const smart_connect_config_input = [
     node_widget_name: 'image',
     inputNodeName: 'LoadImage',
     inputNode_output_name: 'IMAGE'
+  },
+  {
+    node_type: 'TripoSRSampler_',
+    node_widget_name: 'image',
+    inputNodeName: 'LoadImagesToBatch',
+    inputNode_output_name: 'IMAGE'
+  },
+  {
+    node_type: 'TripoSRSampler_',
+    node_widget_name: 'mask',
+    inputNodeName: 'RembgNode_Mix',
+    inputNode_output_name: 'masks'
   }
 ]
 
@@ -74,6 +86,18 @@ const smart_connect_config_output = [
     outputNodeName: 'SaveImage',
     outputNode_input_name: 'images'
   },
+  {
+    node_type: 'VAEDecode',
+    node_output_name: 'IMAGE',
+    outputNodeName: 'AppInfo',
+    outputNode_input_name: 'IMAGE'
+  },
+  {
+    node_type: 'VAEDecode',
+    node_output_name: 'IMAGE',
+    outputNodeName: 'SaveImageAndMetadata_',
+    outputNode_input_name: 'images'
+  },
   {
     node_type: 'Moondream',
     node_output_name: 'STRING',
@@ -181,7 +205,10 @@ export function smart_init () {
       ]
       let node_slotType = config[0]
       // 如果input没有，则创建
-      if (!node.inputs?.filter(inp => inp.name === widget.name)[0]||!node.inputs)
+      if (
+        !node.inputs?.filter(inp => inp.name === widget.name)[0] ||
+        !node.inputs
+      )
         convertToInput(node, widget, config)
       input_node.connectByType(inputNode_slot, node, node_slotType)
     }

web/javascript/ui_mixlab.js

@@ -299,15 +299,16 @@ async function get_my_app (filename = null, category = '') {
     data = []
 
     for (const res of result.data) {
-      let { app, workflow } = res.data
-      if (app.filename)
-        data.push({
+      let { app, workflow } = res.data;
+      if (app?.filename) data.push({
           ...app,
           data: workflow,
           date: res.date
         })
     }
-  } catch (error) {}
+  } catch (error) {
+    console.log(error)
+  }
   return data
 }
 
@@ -1137,6 +1138,57 @@ app.registerExtension({
         (this.canvas.height * 0.5) / (this.ds.scale * dpr) // 考虑设备像素比
       this.setDirty(true, true)
     }
+
+    // 支持app模式的json
+    const loadAppJson = async data => {
+      let workflow
+      try {
+        let w = JSON.parse(data)
+        if (w.app && w.output) workflow = w.workflow
+      } catch (err) {}
+
+      if (workflow && workflow.version && workflow.nodes && workflow.extra) {
+        await app.loadGraphData(workflow)
+      }
+    }
+
+    if (!window._mixlab_app_paste_listener) {
+      window._mixlab_app_paste_listener = true
+      //粘贴json的事件
+      document.addEventListener('paste', async e => {
+        // ctrl+shift+v is used to paste nodes with connections
+        // this is handled by litegraph
+        if (this.shiftDown) return
+
+        let data = e.clipboardData || window.clipboardData
+
+        // No image found. Look for node data
+        data = data.getData('text/plain')
+
+        loadAppJson(data)
+      })
+
+      // 把json往里 拖
+      document.addEventListener('drop', async event => {
+        event.preventDefault()
+        event.stopPropagation()
+
+       
+
+        // Dragging from Chrome->Firefox there is a file but its a bmp, so ignore that
+        if (
+          event.dataTransfer.files.length &&
+          event.dataTransfer.files[0].type == 'application/json'
+        ) {
+          const reader = new FileReader()
+          reader.onload = async () => {
+       
+            loadAppJson(reader.result)
+          }
+          reader.readAsText(event.dataTransfer.files[0])
+        }
+      })
+    }
   },
   setup () {
     setTimeout(async () => {
@@ -1146,6 +1198,8 @@ app.registerExtension({
       const apps = await get_my_app()
       if (!apps) return
 
+      console.log('apps',apps)
+
       let apps_map = { 0: [] }
 
       for (const app of apps) {
@@ -1511,14 +1565,16 @@ app.registerExtension({
                 document.body.appendChild(div)
             }
           },
-          {
-            content: 'Workflow App ♾️Mixlab',
-            has_submenu: true,
-            disabled: false,
-            submenu: {
-              options: apps_opts
-            }
-          }
+          apps_opts.length > 0
+            ? {
+                content: 'Workflow App ♾️Mixlab',
+                has_submenu: true,
+                disabled: false,
+                submenu: {
+                  options: apps_opts
+                }
+              }
+            : null
         )
 
         return options
@@ -1587,3 +1643,41 @@ app.registerExtension({
     } catch (error) {}
   }
 })
+
+//获取当前显存
+function fetchSystemStats () {
+  return new Promise(async (resolve, reject) => {
+    try {
+      const response = await fetch('/system_stats')
+      const data = await response.json()
+      resolve(data)
+    } catch (error) {
+      reject(error)
+    }
+  })
+}
+//清理显存
+function postFreeData () {
+  return new Promise(async (resolve, reject) => {
+    try {
+      const postData = {
+        unload_models: true,
+        free_memory: true
+      }
+      const response = await fetch('/free', {
+        method: 'POST',
+        headers: {
+          'Content-Type': 'application/json'
+        },
+        body: JSON.stringify(postData)
+      })
+      if (response.ok) {
+        resolve()
+      } else {
+        reject(new Error('Request failed'))
+      }
+    } catch (error) {
+      reject(error)
+    }
+  })
+}