Delete layers-test-workflow.json

0.4.1

README.md

@@ -1,29 +1,19 @@
 ## 
-v0.3.0 🚀🚗🚚🏃‍
+v0.4.0 🚀🚗🚚🏃‍
+- Add "help" option to the context menu for each node.
+- Add "find the node" option to the global context menu.
+- Optimize the 3D Image node and add workflow.
 
-- Added support for setting proxies: HTTP_PROXY, HTTPS_PROXY, http_proxy, https_proxy ✅
+### 3D
+![](./assets/3dimage.png)
+[workflow](./workflow/3D-workflow.json)
 
-- Added a new Speech feature node, enabling the use of a voice assistant: SpeechRecognition & SpeechSynthesis 🎙️
-
-- Added TextImage node, allowing conversion of text into image format 📷
-
-- Added SvgImage node, enabling layout parsing and poster generation in conjunction with the Layer class node 🖼️
-
-- Added an experimental 3DImage node for loading 3D models 🌟
-
-
-![screenshare](./assets/screenshare.png)
-
-
-### SpeechRecognition & SpeechSynthesis
-![f](./assets/audio-workflow.svg)
-
-[Voice + Real-time Face Swap Workflow](./workflow/语音+实时换脸workflow.json)
 
 ### 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
 
@@ -33,14 +23,10 @@ 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)
 
-### 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)
-
+[Voice + Real-time Face Swap Workflow](./workflow/语音+实时换脸workflow.json)
 
 ### 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 
@@ -50,6 +36,13 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
 
 [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)
+
 
 ### Layers
 > A new layer class node has been added, allowing you to separate the image into layers. After merging the images, you can input the controlnet for further processing.
@@ -92,8 +85,14 @@ Add edges to an image.
 
 
 ### Improvement 
+
+- Add "help" option to the context menu for each node.
+- Add "find the node" option to the global context menu.
+
 An improvement has been made to directly redirect to GitHub to search for missing nodes when loading the graph.
 
+![help](./assets/help.png)
+
 ![node-not-found](./assets/node-not-found.png)
 
 

__init__.py

@@ -318,7 +318,7 @@ PromptServer.add_routes=new_add_routes
 
 # 导入节点
 from .nodes.PromptNode import RandomPrompt
-from .nodes.ImageNode import TransparentImage,LoadImagesFromPath,TextImage,SvgImage,Image3D,EmptyLayer,ShowLayer,NewLayer,MergeLayers,AreaToMask,SmoothMask,FeatheredMask,SplitLongMask,ImageCropByAlpha,EnhanceImage,FaceToMask
+from .nodes.ImageNode import TransparentImage,LoadImagesFromPath,ResizeImage,TextImage,SvgImage,Image3D,EmptyLayer,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
@@ -332,12 +332,13 @@ from .nodes.Utils import ColorInput,FontInput
 NODE_CLASS_MAPPINGS = {
     "RandomPrompt":RandomPrompt,
     "TransparentImage":TransparentImage,
+    "ResizeImageMixlab":ResizeImage,
     "LoadImagesFromPath":LoadImagesFromPath,
     "TextImage":TextImage,
     "EnhanceImage":EnhanceImage,
     "SvgImage":SvgImage,
     "3DImage":Image3D,
-    "EmptyLayer":EmptyLayer,
+    # "EmptyLayer":EmptyLayer,
     "ShowLayer":ShowLayer,
     "NewLayer":NewLayer,
     "MergeLayers":MergeLayers,
@@ -364,6 +365,7 @@ NODE_CLASS_MAPPINGS = {
 
 # 一个包含节点友好/可读的标题的字典
 NODE_DISPLAY_NAME_MAPPINGS = {
+    "ResizeImageMixlab":"ResizeImage",
     "RandomPrompt": "Random Prompt ♾️Mixlab",
     "SplitLongMask":"Splitting a long image into sections",
     "VAELoaderConsistencyDecoder":"Consistency Decoder Loader",
@@ -374,7 +376,8 @@ NODE_DISPLAY_NAME_MAPPINGS = {
     "ShowTextForGPT":"ShowTextForGPT ♾️Mixlab",
     "MergeLayers":"MergeLayers ♾️Mixlab",
     "SpeechSynthesis":"SpeechSynthesis ♾️Mixlab",
-    "SpeechRecognition":"SpeechRecognition ♾️Mixlab"
+    "SpeechRecognition":"SpeechRecognition ♾️Mixlab",
+    "3DImage":"3DImage ♾️Mixlab"
 }
 
 # web ui的节点功能

nodes/ImageNode.py

@@ -376,6 +376,25 @@ def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option)
     return bg_image
 
 
+def resize_image(layer_image,scale_option,width,height):
+    layer_image = layer_image.convert("RGB")
+    if scale_option == "height":
+        # 按照高度比例缩放
+        original_width, original_height = layer_image.size
+        scale = height / original_height
+        new_width = int(original_width * scale)
+        layer_image = layer_image.resize((new_width, height))
+    elif scale_option == "width":
+        # 按照宽度比例缩放
+        original_width, original_height = layer_image.size
+        scale = width / original_width
+        new_height = int(original_height * scale)
+        layer_image = layer_image.resize((width, new_height))
+    elif scale_option == "overall":
+        # 整体缩放
+        layer_image = layer_image.resize((width, height))
+    return layer_image
+
 
 def generate_text_image(text_list, font_path, font_size, text_color, vertical=True, spacing=0):
     # Load Chinese font
@@ -434,6 +453,32 @@ def base64_to_image(base64_string):
     return image
 
 
+def create_temp_file(image):
+    output_dir = folder_paths.get_temp_directory()
+
+    (
+            full_output_folder,
+            filename,
+            counter,
+            subfolder,
+            _,
+        ) = folder_paths.get_save_image_path('material', output_dir)
+
+    
+    image=tensor2pil(image)
+ 
+    image_file = f"{filename}_{counter:05}.png"
+     
+    image_path=os.path.join(full_output_folder, image_file)
+
+    image.save(image_path,compress_level=4)
+
+    return [{
+                "filename": image_file,
+                "subfolder": subfolder,
+                "type": "temp"
+                }]
+
 
 class SmoothMask:
     @classmethod
@@ -659,7 +704,7 @@ class TransparentImage:
         
         # ui.images 节点里显示图片，和 传参，image_path自定义的数据，需要写节点的自定义ui
         # result 里输出给下个节点的数据 
-        print('TransparentImage',len(images_rgb))
+        # print('TransparentImage',len(images_rgb))
         return {"ui":{"images": ui_images,"image_paths":image_paths},"result": (image_paths,images_rgb,images_rgba)}
         
 
@@ -822,6 +867,8 @@ class ImageCropByAlpha:
 
 
 
+
+
 class TextImage:
     @classmethod
     def INPUT_TYPES(s):
@@ -906,29 +953,50 @@ class Image3D:
     @classmethod
     def INPUT_TYPES(s):
         return {"required": { 
-                    "upload":("THREED",),   },
+                    "upload":("THREED",),}, 
+                "optional":{
+                    "material": ("IMAGE",),
+                    }
                 }
     
-    RETURN_TYPES = ("IMAGE","MASK",)
-    # RETURN_NAMES = ("IMAGE",)
+    RETURN_TYPES = ("IMAGE","MASK","IMAGE","IMAGE",)
+    RETURN_NAMES = ("IMAGE","MASK","BG_IMAGE","MATERIAL",)
 
     FUNCTION = "run"
 
     CATEGORY = "♾️Mixlab/image"
 
     INPUT_IS_LIST = False
-    OUTPUT_IS_LIST = (False,False,)
+    OUTPUT_IS_LIST = (False,False,False,False,)
+    OUTPUT_NODE = True
 
-    def run(self,upload):
+    def run(self,upload,material=None):
+        # print('material',material)
         # print(upload['image'])
         image = base64_to_image(upload['image'])
+        mat=base64_to_image(upload['material'])
+        mask = image.split()[3]
         image=image.convert('RGB')
-        mask=image.convert('L')
-        
+        mat=mat.convert('RGB')
+        mask=mask.convert('L')
+
+        bg_image=None
+        if upload['bg_image']:
+            bg_image = base64_to_image(upload['bg_image'])
+            bg_image=bg_image.convert('RGB')
+            bg_image=pil2tensor(bg_image)
+
+
         mask=pil2tensor(mask)
         image=pil2tensor(image)
+        mat=pil2tensor(mat)
+
+        m=[]
+        if not material is None:
+            m=create_temp_file(material[0])
+        
+        return {"ui":{"material": m},"result": (image,mask,bg_image,mat,)}
 
-        return (image,mask,)
 
 
 
@@ -1056,14 +1124,14 @@ class NewLayer:
             "required": { 
                 "x": ("INT",{
                     "default": 0, 
-                    "min": -100, #Minimum value
+                    "min": -1024, #Minimum value
                     "max": 8192, #Maximum value
                     "step": 1, #Slider's step
                     "display": "number" # Cosmetic only: display as "number" or "slider"
                 }),
                 "y": ("INT",{
                     "default": 0, 
-                    "min": 0, #Minimum value
+                    "min": -1024, #Minimum value
                     "max": 8192, #Maximum value
                     "step": 1, #Slider's step
                     "display": "number" # Cosmetic only: display as "number" or "slider"
@@ -1095,6 +1163,7 @@ class NewLayer:
              "optional":{
                     "mask": ("MASK",{"default": None}),
                     "layers": ("LAYER",{"default": None}), 
+                    "canvas": ("IMAGE",{"default": None}), 
                 }
                 }
     
@@ -1108,16 +1177,16 @@ class NewLayer:
     INPUT_IS_LIST = True
     OUTPUT_IS_LIST = (True,)
 
-    def run(self,x,y,width,height,z_index,scale_option,image,mask,layers):
+    def run(self,x,y,width,height,z_index,scale_option,image,mask=None,layers=None,canvas=None):
         # print(x,y,width,height,z_index,image,mask)
         
         if mask==None:
-            im=tensor2pil(image)
+            im=tensor2pil(image[0])
             mask=im.convert('L')
             mask=pil2tensor(mask)
         else:
             mask=mask[0]
-
+        
         layer_n=[{
             "x":x[0],
             "y":y[0],
@@ -1134,7 +1203,6 @@ class NewLayer:
 
         return (layer_n,)
 
-
 class ShowLayer:
     @classmethod
     def INPUT_TYPES(s):
@@ -1282,4 +1350,55 @@ class MergeLayers:
         # print(mask,mask.shape)
         mask = mask[:, :, :, channels.index("green")]
         
-        return (bg_image,mask,)
+        return (bg_image,mask,)
+    
+
+
+
+class ResizeImage:
+    @classmethod
+    def INPUT_TYPES(s):
+        return {"required": {
+            "image": ("IMAGE",),
+
+            "width": ("INT",{
+                    "default": 512, 
+                    "min": 1, #Minimum value
+                    "max": 8192, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "height": ("INT",{
+                    "default": 512, 
+                    "min": 1, #Minimum value
+                    "max": 8192, #Maximum value
+                    "step": 1, #Slider's step
+                    "display": "number" # Cosmetic only: display as "number" or "slider"
+                }),
+                "scale_option": (["width","height",'overall'],),
+
+                             },
+                }
+    
+    RETURN_TYPES = ("IMAGE",)
+
+    FUNCTION = "run"
+
+    CATEGORY = "♾️Mixlab/image"
+
+    INPUT_IS_LIST = True
+    OUTPUT_IS_LIST = (False,)
+
+    def run(self,image,width,height,scale_option):
+        
+        w=width[0]
+        h=height[0]
+        scale_option=scale_option[0]
+        im=image[0]
+
+        im=tensor2pil(im)
+        im=resize_image(im,scale_option,w,h)
+        im=im.convert('RGB')
+        im=pil2tensor(im)
+        
+        return (im,)

nodes/Vae.py

@@ -145,7 +145,7 @@ class VAELoader:
     RETURN_TYPES = ("VAE",)
     FUNCTION = "load_vae"
 
-    CATEGORY = "♾️Mixlab/ConsistencyDecoder"
+    CATEGORY = "♾️Mixlab/_test"
 
     #TODO: scale factor?
     def load_vae(self, vae_name):
@@ -165,7 +165,7 @@ class VAEDecode:
     RETURN_TYPES = ("IMAGE",)
     FUNCTION = "decode"
 
-    CATEGORY = "♾️Mixlab/ConsistencyDecoder"
+    CATEGORY = "♾️Mixlab/_test"
 
     def decode(self, vae, samples):
         image = vae.decode(samples["samples"].to("cuda:0"))

web/javascript/3d_mixlab.js

@@ -0,0 +1,608 @@
+import { app } from '../../../scripts/app.js'
+import { api } from '../../../scripts/api.js'
+import { $el } from '../../../scripts/ui.js'
+
+const getLocalData = key => {
+  let data = {}
+  try {
+    data = JSON.parse(localStorage.getItem(key)) || {}
+  } catch (error) {
+    return {}
+  }
+  return data
+}
+function getContentTypeFromBase64 (base64Data) {
+  const regex = /^data:(.+);base64,/
+  const matches = base64Data.match(regex)
+  if (matches && matches.length >= 2) {
+    return matches[1]
+  }
+  return null
+}
+function base64ToBlobFromURL (base64URL, contentType) {
+  return fetch(base64URL).then(response => response.blob())
+}
+const setLocalDataOfWin = (key, value) => {
+  localStorage.setItem(key, JSON.stringify(value))
+  // window[key] = value
+}
+async function uploadImage (blob, fileType = '.svg', filename) {
+  // const blob = await (await fetch(src)).blob();
+  const body = new FormData()
+  body.append(
+    'image',
+    new File([blob], (filename || new Date().getTime()) + fileType)
+  )
+
+  const resp = await api.fetchApi('/upload/image', {
+    method: 'POST',
+    body
+  })
+
+  // console.log(resp)
+  let data = await resp.json()
+  let { name, subfolder } = data
+  let src = api.apiURL(
+    `/view?filename=${encodeURIComponent(
+      name
+    )}&type=input&subfolder=${subfolder}${app.getPreviewFormatParam()}${app.getRandParam()}`
+  )
+
+  return src
+}
+
+function createImage (url) {
+  let im = new Image()
+  return new Promise((res, rej) => {
+    im.onload = () => res(im)
+    im.src = url
+  })
+}
+
+const parseImage = url => {
+  return new Promise((res, rej) => {
+    fetch(url)
+      .then(response => response.blob())
+      .then(blob => {
+        const reader = new FileReader()
+        reader.onloadend = () => {
+          const base64data = reader.result
+          res(base64data)
+          // 在这里可以将base64数据用于进一步处理或显示图片
+        }
+        reader.readAsDataURL(blob)
+      })
+      .catch(error => {
+        console.log('发生错误:', error)
+      })
+  })
+}
+
+function get_position_style (ctx, widget_width, y, node_height) {
+  const MARGIN = 4 // the margin around the html element
+
+  /* Create a transform that deals with all the scrolling and zooming */
+  const elRect = ctx.canvas.getBoundingClientRect()
+  const transform = new DOMMatrix()
+    .scaleSelf(
+      elRect.width / ctx.canvas.width,
+      elRect.height / ctx.canvas.height
+    )
+    .multiplySelf(ctx.getTransform())
+    .translateSelf(MARGIN, MARGIN + y)
+
+  return {
+    transformOrigin: '0 0',
+    transform: transform,
+    left: `0`,
+    top: `0`,
+    cursor: 'pointer',
+    position: 'absolute',
+    maxWidth: `${widget_width - MARGIN * 2}px`,
+    // maxHeight: `${node_height - MARGIN * 2}px`, // we're assuming we have the whole height of the node
+    width: `${widget_width - MARGIN * 2}px`,
+    // height: `${node_height * 0.3 - MARGIN * 2}px`,
+    // background: '#EEEEEE',
+    display: 'flex',
+    flexDirection: 'column',
+    // alignItems: 'center',
+    justifyContent: 'space-around'
+  }
+}
+
+async function extractMaterial (
+  modelViewerVariants,
+  selectMaterial,
+  material_img
+) {
+  // 材质
+  const materialsNames = []
+  for (
+    let index = 0;
+    index < modelViewerVariants.model.materials.length;
+    index++
+  ) {
+    let m = modelViewerVariants.model.materials[index]
+    let thumbUrl
+    try {
+      thumbUrl =
+        await m.pbrMetallicRoughness.baseColorTexture.texture.source.createThumbnail(
+          1024,
+          1024
+        )
+    } catch (error) {}
+    if (thumbUrl)
+      materialsNames.push({
+        value: m.name,
+        text: `#${index} ${m.name}`,
+        index,
+        thumbUrl
+      })
+  }
+
+  selectMaterial.innerHTML = ''
+  material_img.innerHTML = ''
+
+  for (let index = 0; index < materialsNames.length; index++) {
+    const name = materialsNames[index]
+    const option = document.createElement('option')
+    option.value = name.thumbUrl
+    option.textContent = name.text
+    option.setAttribute('data-index', index)
+    selectMaterial.appendChild(option)
+    let img = new Image()
+    img.src = name.thumbUrl
+    // img.setAttribute('data-index',name.index)
+    img.style.width = '40px'
+    material_img.appendChild(img)
+    if (index == 0) {
+      material_img.setAttribute('src', name.thumbUrl)
+    }
+  }
+}
+
+async function changeMaterial (
+  modelViewerVariants,
+  targetMaterial,
+  newImageUrl
+) {
+  const targetTexture = await modelViewerVariants.createTexture(newImageUrl)
+  // 用图片创建纹理
+  targetMaterial.pbrMetallicRoughness.baseColorTexture.setTexture(targetTexture)
+}
+
+app.registerExtension({
+  name: 'Mixlab.3D.3DImage',
+  async getCustomWidgets (app) {
+    return {
+      THREED (node, inputName, inputData, app) {
+        // console.log('##node', node, inputName, inputData)
+        const widget = {
+          type: inputData[0], // the type, CHEESE
+          name: inputName, // the name, slice
+          size: [128, 88], // a default size
+          draw (ctx, node, width, y) {},
+          computeSize (...args) {
+            return [128, 88] // a method to compute the current size of the widget
+          },
+          async serializeValue (nodeId, widgetIndex) {
+            let d = getLocalData('_mixlab_3d_image')
+            console.log('serializeValue', node)
+            if (d && d[node.id]) {
+              let { url, bg, material } = d[node.id]
+              let base64 = await parseImage(url)
+              let bg_base64 = await parseImage(bg)
+              let material_base64 = await parseImage(material)
+
+              return JSON.parse(
+                JSON.stringify({
+                  image: base64,
+                  bg_image: bg_base64,
+                  material: material_base64
+                })
+              )
+            } else {
+              return {}
+            }
+          }
+        }
+        node.addCustomWidget(widget)
+        return widget
+      }
+    }
+  },
+
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == '3DImage') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = async function () {
+        orig_nodeCreated?.apply(this, arguments)
+
+        const uploadWidget = this.widgets.filter(w => w.name == 'upload')[0]
+
+        const widget = {
+          type: 'div',
+          name: 'upload-preview',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(
+              this.div.style,
+              get_position_style(ctx, widget_width, 88, node.size[1])
+            )
+          }
+        }
+
+        widget.div = $el('div', {})
+        widget.div.style.width = `120px`
+
+        document.body.appendChild(widget.div)
+
+        const inputDiv = (key, placeholder, preview) => {
+          let div = document.createElement('div')
+          const ip = document.createElement('input')
+          ip.type = 'file'
+          ip.className = `${'comfy-multiline-input'} ${placeholder}`
+          div.style = `display: flex;
+            align-items: center; 
+            margin: 6px 8px;
+            margin-top: 0;`
+          ip.placeholder = placeholder
+          // ip.value = value
+
+          ip.style = `outline: none;
+            border: none;
+            padding: 4px;
+            width: 60%;cursor: pointer;
+            height: 32px;`
+          const label = document.createElement('label')
+          label.style = 'font-size: 10px;min-width:32px'
+          label.innerText = placeholder
+          div.appendChild(label)
+          div.appendChild(ip)
+
+          let that = this,
+            filename = new Date().getTime()
+
+          ip.addEventListener('change', async event => {
+            const file = event.target.files[0]
+            const reader = new FileReader()
+            filename = new Date().getTime()
+            // 读取文件内容
+            reader.onload = async e => {
+              const fileURL = URL.createObjectURL(file)
+              // console.log('文件URL: ', fileURL)
+              let html = `<model-viewer  src="${fileURL}" 
+                min-field-of-view="0deg" max-field-of-view="180deg"
+                 shadow-intensity="1" 
+                 camera-controls 
+                 touch-action="pan-y">
+                 
+                 <div class="controls">
+                  <div>Variant: <select class="variant"></select></div>
+                  <div>Material: <select class="material"></select></div>
+                  <div>Material: <div class="material_img"> </div></div>
+                  <div><button class="bg">BG</button></div>
+                </div></model-viewer>`
+
+              preview.innerHTML = html
+              if (that.size[1] < 400) {
+                that.setSize([that.size[0], that.size[1] + 300])
+                app.canvas.draw(true, true)
+              }
+
+              const modelViewerVariants = preview.querySelector('model-viewer')
+              const select = preview.querySelector('.variant')
+              const selectMaterial = preview.querySelector('.material')
+              const material_img = preview.querySelector('.material_img')
+              const bg = preview.querySelector('.bg')
+
+              if (modelViewerVariants) {
+                modelViewerVariants.style.width = `${that.size[0] - 24}px`
+                modelViewerVariants.style.height = `${that.size[1] - 48}px`
+              }
+
+              modelViewerVariants.addEventListener('load', async () => {
+                const names = modelViewerVariants.availableVariants
+
+                // 变量
+                for (const name of names) {
+                  const option = document.createElement('option')
+                  option.value = name
+                  option.textContent = name
+                  select.appendChild(option)
+                }
+                // Adds a default option.
+                if (names.length === 0) {
+                  const option = document.createElement('option')
+                  option.value = 'default'
+                  option.textContent = 'Default'
+                  select.appendChild(option)
+                }
+
+                // 材质
+                extractMaterial(
+                  modelViewerVariants,
+                  selectMaterial,
+                  material_img
+                )
+              })
+
+              let timer = null
+              const delay = 500 // 延迟时间，单位为毫秒
+
+              async function checkCameraChange () {
+                let dd = getLocalData(key)
+                let base64Data = modelViewerVariants.toDataURL()
+
+                const contentType = getContentTypeFromBase64(base64Data)
+
+                const blob = await base64ToBlobFromURL(base64Data, contentType)
+
+                //  const fileBlob = new Blob([e.target.result], { type: file.type });
+                let url = await uploadImage(blob, '.png')
+                // console.log(url)
+
+                //  材质贴图
+                let thumbUrl = material_img.getAttribute('src')
+                let tb = await base64ToBlobFromURL(thumbUrl)
+                let tUrl = await uploadImage(tb, '.png')
+
+                // console.log(tUrl)
+
+                let bg_blob = await base64ToBlobFromURL(
+                  'data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mN88uXrPQAFwwK/6xJ6CQAAAABJRU5ErkJggg=='
+                )
+                let url_bg = await uploadImage(bg_blob, '.png')
+
+                if (!dd[that.id])
+                  dd[that.id] = { url, bg: url_bg, material: tUrl }
+                dd[that.id] = { ...dd[that.id], url, material: tUrl }
+
+                setLocalDataOfWin(key, dd)
+              }
+
+              function startTimer () {
+                if (timer) clearTimeout(timer)
+                timer = setTimeout(checkCameraChange, delay)
+              }
+
+              modelViewerVariants.addEventListener('camera-change', startTimer)
+
+              select.addEventListener('input', event => {
+                modelViewerVariants.variantName =
+                  event.target.value === 'default' ? null : event.target.value
+                // 材质
+                extractMaterial(
+                  modelViewerVariants,
+                  selectMaterial,
+                  material_img
+                )
+                checkCameraChange()
+              })
+
+              selectMaterial.addEventListener('input', event => {
+                // console.log(selectMaterial.value)
+                material_img.setAttribute('src', selectMaterial.value)
+
+                if (selectMaterial.getAttribute('data-new-material')) {
+                  let index =
+                    ~~selectMaterial.selectedOptions[0].getAttribute(
+                      'data-index'
+                    )
+                  changeMaterial(
+                    modelViewerVariants,
+                    modelViewerVariants.model.materials[index],
+                    selectMaterial.getAttribute('data-new-material')
+                  )
+                }
+
+                checkCameraChange()
+              })
+
+              bg.addEventListener('click', () => {
+                // 创建一个input元素
+                var input = document.createElement('input')
+                input.type = 'file'
+
+                // 监听input的change事件
+                input.addEventListener('change', function () {
+                  // 获取上传的文件
+                  var file = input.files[0]
+
+                  // 创建一个FileReader对象来读取文件
+                  var reader = new FileReader()
+
+                  // 监听FileReader的load事件
+                  reader.addEventListener('load', async () => {
+                    let base64 = reader.result
+                    // 将读取的文件内容设置为div的背景
+                    preview.style.backgroundImage = 'url(' + base64 + ')'
+
+                    const contentType = getContentTypeFromBase64(base64)
+
+                    const blob = await base64ToBlobFromURL(base64, contentType)
+
+                    //  const fileBlob = new Blob([e.target.result], { type: file.type });
+                    let bg_url = await uploadImage(blob, '.png')
+                    let bg_img = await createImage(base64)
+
+                    let dd = getLocalData(key)
+                    // console.log(dd[that.id],bg_url)
+                    if (!dd[that.id]) dd[that.id] = { url: '', bg: bg_url }
+                    dd[that.id] = {
+                      ...dd[that.id],
+                      bg: bg_url,
+                      bg_w: bg_img.naturalWidth,
+                      bg_h: bg_img.naturalHeight
+                    }
+
+                    setLocalDataOfWin(key, dd)
+
+                    // 更新尺寸
+                    let w = that.size[0] - 24,
+                      h = (w * bg_img.naturalHeight) / bg_img.naturalWidth
+
+                    if (modelViewerVariants) {
+                      modelViewerVariants.style.width = `${w}px`
+                      modelViewerVariants.style.height = `${h}px`
+                    }
+                    preview.style.width = `${w}px`
+                  })
+
+                  // 读取文件
+                  reader.readAsDataURL(file)
+                })
+
+                // 触发input的点击事件
+                input.click()
+              })
+
+              uploadWidget.value = await uploadWidget.serializeValue()
+
+              // 更新尺寸
+              let dd = getLocalData(key)
+              // console.log(dd[that.id],bg_url)
+              if (dd[that.id]) {
+                const { bg_w, bg_h } = dd[that.id]
+                if (bg_h && bg_w) {
+                  let w = that.size[0] - 24,
+                    h = (w * bg_h) / bg_w
+
+                  if (modelViewerVariants) {
+                    modelViewerVariants.style.width = `${w}px`
+                    modelViewerVariants.style.height = `${h}px`
+                  }
+                  preview.style.width = `${w}px`
+                }
+              }
+            }
+
+            // 以文本形式读取文件
+            reader.readAsDataURL(file)
+          })
+          return div
+        }
+
+        let preview = document.createElement('div')
+        preview.className = 'preview'
+        preview.style = `margin-top: 12px;display: flex;
+          justify-content: center;
+          align-items: center;background-repeat: no-repeat;background-size: contain;`
+
+        let upload = inputDiv('_mixlab_3d_image', '3D Model', preview)
+
+        widget.div.appendChild(upload)
+        widget.div.appendChild(preview)
+        this.addCustomWidget(widget)
+
+        const onResize = this.onResize
+        let that = this
+        this.onResize = function () {
+          let modelViewerVariants = preview.querySelector('model-viewer')
+
+          // 更新尺寸
+          let dd = getLocalData('_mixlab_3d_image')
+          // console.log(dd[that.id],bg_url)
+          if (dd[that.id]) {
+            const { bg_w, bg_h } = dd[that.id]
+            if (bg_h && bg_w) {
+              let w = that.size[0] - 24,
+                h = (w * bg_h) / bg_w
+
+              if (modelViewerVariants) {
+                modelViewerVariants.style.width = `${w}px`
+                modelViewerVariants.style.height = `${h}px`
+              }
+              preview.style.width = `${w}px`
+            }
+          }
+
+          return onResize?.apply(this, arguments)
+        }
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => {
+          upload.remove()
+          preview.remove()
+          widget.div.remove()
+          return onRemoved?.()
+        }
+
+        if (this.onResize) {
+          this.onResize(this.size)
+        }
+        // this.isVirtualNode = true
+        this.serialize_widgets = false //需要保存参数
+      }
+
+      const onExecuted = nodeType.prototype.onExecuted
+      nodeType.prototype.onExecuted = function (message) {
+        const r = onExecuted?.apply?.(this, arguments)
+
+        let div = this.widgets.filter(d => d.div)[0]?.div
+        console.log('Test', this.widgets)
+
+        let material = message.material[0]
+        if (material) {
+          const { filename, subfolder, type } = material
+          let src = api.apiURL(
+            `/view?filename=${encodeURIComponent(
+              filename
+            )}&type=${type}&subfolder=${subfolder}${app.getPreviewFormatParam()}${app.getRandParam()}`
+          )
+
+          const modelViewerVariants = div.querySelector('model-viewer')
+
+          const selectMaterial = div.querySelector('.material')
+
+          let index =
+            ~~selectMaterial.selectedOptions[0].getAttribute('data-index')
+
+          selectMaterial.setAttribute('data-new-material', src)
+
+          changeMaterial(
+            modelViewerVariants,
+            modelViewerVariants.model.materials[index],
+            src
+          )
+        }
+
+        this.onResize?.(this.size)
+
+        return r
+      }
+    }
+  },
+  async loadedGraphNode (node, app) {
+    // Fires every time a node is constructed
+    // You can modify widgets/add handlers/etc here
+    const sleep = (t = 1000) => {
+      return new Promise((res, rej) => {
+        setTimeout(() => res(1), t)
+      })
+    }
+    if (node.type === '3DImage') {
+      // await sleep(0)
+      let widget = node.widgets.filter(w => w.name === 'upload-preview')[0]
+
+      let dd = getLocalData('_mixlab_3d_image')
+
+      let id = node.id
+      // console.log('3dImage load', node.widgets[0], node.widgets)
+      if (!dd[id]) return
+
+      let { url, bg } = dd[id]
+      if (!url) return
+      // let base64 = await parseImage(url)
+
+      let pre = widget.div.querySelector('.preview')
+      pre.style.width = `${node.size[0]}px`
+      pre.innerHTML = `
+        ${url ? `<img src="${url}" style="width:100%"/>` : ''}
+        `
+      pre.style.backgroundImage = 'url(' + bg + ')'
+
+      const uploadWidget = node.widgets.filter(w => w.name == 'upload')[0]
+      uploadWidget.value = await uploadWidget.serializeValue()
+    }
+  }
+})

web/javascript/audio_mixlab.js

@@ -105,6 +105,7 @@ const start = (element, id, startBtn) => {
       window.recognition = null;
       startBtn.className=''
       startBtn.innerText = 'START'
+      
 
       timeoutId = null
 
@@ -201,9 +202,12 @@ app.registerExtension({
           margin: 0px 8px 6px;`
 
           startBtn.style = `
-            outline: none;
-            border: none;
-            padding: 4px; `
+          background-color: var(--comfy-input-bg);
+          border-radius: 8px;
+          border-color: var(--border-color);
+          border-style: solid;
+          color: var(--descrip-text);
+          `
 
           startBtn.innerText = 'START'
 

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 = 'v0.3.1'
+const version = 'v0.4.2'
 
 fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
   .then(response => response.json())

web/javascript/image_mixlab.js

@@ -3,10 +3,13 @@ import { api } from '../../../scripts/api.js'
 import { ComfyWidgets } from '../../../scripts/widgets.js'
 import { $el } from '../../../scripts/ui.js'
 
-async function uploadImage (blob, fileType = '.svg') {
+async function uploadImage (blob, fileType = '.svg', filename) {
   // const blob = await (await fetch(src)).blob();
   const body = new FormData()
-  body.append('image', new File([blob], new Date().getTime() + fileType))
+  body.append(
+    'image',
+    new File([blob], (filename || new Date().getTime()) + fileType)
+  )
 
   const resp = await api.fetchApi('/upload/image', {
     method: 'POST',
@@ -228,6 +231,25 @@ const parseSvg = async svgContent => {
   return { data, image: base64, svgElement }
 }
 
+function exportModelViewerImage (
+  modelViewer,
+  width,
+  height,
+  format = 'image/png',
+  quality = 1.0
+) {
+  const canvas = document.createElement('canvas')
+  canvas.width = width
+  canvas.height = height
+  const context = canvas.getContext('2d')
+
+  return new Promise((resolve, reject) => {
+    context.drawImage(modelViewer, 0, 0, width, height)
+
+    resolve(canvas.toDataURL(format, quality))
+  })
+}
+
 app.registerExtension({
   name: 'Mixlab.image.SvgImage',
   async getCustomWidgets (app) {
@@ -410,250 +432,7 @@ app.registerExtension({
 
       const uploadWidget = node.widgets.filter(w => w.name == 'upload')[0]
       uploadWidget.value = await uploadWidget.serializeValue()
-
-      // let h=~~getComputedStyle(widget.div).height.replace('px','');
-      // let w=~~getComputedStyle(widget.div).width.replace('px','');
-      // // console.log('svg', w,h,node.size)
-      // node.setSize([
-      //   w,h
-      // ])
-      // app.graph.setDirtyCanvas(true)
-
-      // console.log(node.widgets_values)
+ 
     }
   }
-})
-
-app.registerExtension({
-  name: 'Mixlab.image.3DImage',
-  async getCustomWidgets (app) {
-    return {
-      THREED (node, inputName, inputData, app) {
-        // console.log('##node', node, inputName, inputData)
-        const widget = {
-          type: inputData[0], // the type, CHEESE
-          name: inputName, // the name, slice
-          size: [128, 88], // a default size
-          draw (ctx, node, width, y) {},
-          computeSize (...args) {
-            return [128, 88] // a method to compute the current size of the widget
-          },
-          async serializeValue (nodeId, widgetIndex) {
-            let d = getLocalData('_mixlab_3d_image')
-            // console.log('serializeValue',d)
-            if (d) {
-              let url = d[node.id]
-              let base64 = await parseImage(url)
-
-              return JSON.parse(JSON.stringify({ image: base64 }))
-            } else {
-              return {}
-            }
-          }
-        }
-        node.addCustomWidget(widget)
-        return widget
-      }
-    }
-  },
-
-  async beforeRegisterNodeDef (nodeType, nodeData, app) {
-    if (nodeType.comfyClass == '3DImage') {
-      const orig_nodeCreated = nodeType.prototype.onNodeCreated
-      nodeType.prototype.onNodeCreated = async function () {
-        orig_nodeCreated?.apply(this, arguments)
-
-        const uploadWidget = this.widgets.filter(w => w.name == 'upload')[0]
-        console.log('3d nodeData', this.inputs)
-
-        const widget = {
-          type: 'div',
-          name: 'upload-preview',
-          draw (ctx, node, widget_width, y, widget_height) {
-            Object.assign(
-              this.div.style,
-              get_position_style(ctx, widget_width, 44, node.size[1])
-            )
-          }
-        }
-
-        widget.div = $el('div', {})
-
-        document.body.appendChild(widget.div)
-
-        const inputDiv = (key, placeholder, preview) => {
-          let div = document.createElement('div')
-          const ip = document.createElement('input')
-          ip.type = 'file'
-          ip.className = `${'comfy-multiline-input'} ${placeholder}`
-          div.style = `display: flex;
-          align-items: center; 
-          margin: 6px 8px;
-          margin-top: 0;`
-          ip.placeholder = placeholder
-          // ip.value = value
-
-          ip.style = `outline: none;
-          border: none;
-          padding: 4px;
-          width: 60%;cursor: pointer;
-          height: 32px;`
-          const label = document.createElement('label')
-          label.style = 'font-size: 10px;min-width:32px'
-          label.innerText = placeholder
-          div.appendChild(label)
-          div.appendChild(ip)
-
-          let that = this
-
-          ip.addEventListener('change', event => {
-            const file = event.target.files[0]
-            const reader = new FileReader()
-
-            // 读取文件内容
-            reader.onload = async e => {
-              const fileURL = URL.createObjectURL(file)
-              // console.log('文件URL: ', fileURL)
-              let html = `<model-viewer 
-              alt="Neil Armstrong's Spacesuit from the Smithsonian Digitization Programs Office and National Air and Space Museum"
-               src="${fileURL}" 
-               ar 
-               shadow-intensity="1" 
-               camera-controls 
-               touch-action="pan-y">
-               
-               <div class="controls">
-                <div>Variant: <select class="variant"></select></div>
-                <div><button class="capture">Capture</button></div>
-              </div></model-viewer>`
-
-              preview.innerHTML = html;
-              that.setSize([that.size[0],that.size[1]+300])
-              app.canvas.draw(true, true)
-
-              const modelViewerVariants = preview.querySelector('model-viewer')
-              const select = preview.querySelector('.variant')
-              const capture = preview.querySelector('.capture')
-
-              modelViewerVariants.addEventListener('load', () => {
-                const names = modelViewerVariants.availableVariants
-                for (const name of names) {
-                  const option = document.createElement('option')
-                  option.value = name
-                  option.textContent = name
-                  select.appendChild(option)
-                }
-                // Adds a default option.
-                const option = document.createElement('option')
-                option.value = 'default'
-                option.textContent = 'Default'
-                select.appendChild(option)
-              })
-
-              select.addEventListener('input', event => {
-                modelViewerVariants.variantName =
-                  event.target.value === 'default' ? null : event.target.value
-              })
-
-              capture.addEventListener('click', async () => {
-                let base64Data = modelViewerVariants.toDataURL()
-
-                const contentType = getContentTypeFromBase64(base64Data)
-
-                const blob = await base64ToBlobFromURL(base64Data, contentType)
-
-                //  const fileBlob = new Blob([e.target.result], { type: file.type });
-                let url = await uploadImage(blob, '.png')
-                console.log(url)
-
-                let dd = getLocalData(key)
-                dd[that.id] = url
-
-                setLocalDataOfWin(key, dd)
-              })
-
-              uploadWidget.value = await uploadWidget.serializeValue()
-            }
-
-            // 以文本形式读取文件
-            reader.readAsDataURL(file)
-          })
-          return div
-        }
-
-        let preview = document.createElement('div')
-        preview.className = 'preview'
-        preview.style = `margin-top: 12px;display: flex;
-        justify-content: center;
-        align-items: center;`
-
-        let upload = inputDiv('_mixlab_3d_image', '3D Model', preview)
-
-        widget.div.appendChild(upload)
-        widget.div.appendChild(preview)
-        this.addCustomWidget(widget);
-
-        const onResize = this.onResize;
-				this.onResize = function () {
-          let m=preview.querySelector('model-viewer')
-          m.style.width=`${this.size[0]-24}px`
-          m.style.height=`${this.size[1]-48}px`
-          // console.log(this.size,preview)
-					return onResize?.apply(this, arguments);
-				};
-
-
-        const onRemoved = this.onRemoved
-        this.onRemoved = () => {
-          upload.remove()
-          preview.remove()
-          widget.div.remove()
-          return onRemoved?.()
-        }
-
-        if (this.onResize) {
-          this.onResize(this.size)
-        }
-
-        this.serialize_widgets = true //需要保存参数
-      }
-    }
-  },
-  async loadedGraphNode (node, app) {
-    // Fires every time a node is constructed
-    // You can modify widgets/add handlers/etc here
-    const sleep = (t = 1000) => {
-      return new Promise((res, rej) => {
-        setTimeout(() => res(1), t)
-      })
-    }
-    if (node.type === '3DImage') {
-      // await sleep(0)
-      let widget = node.widgets.filter(w => w.name === 'upload-preview')[0]
-
-      let dd = getLocalData('_mixlab_3d_image')
-
-      let id = node.id
-      console.log('3dImage load', node.widgets[0], node.widgets)
-      if (!dd[id]) return
-
-      let url = dd[id]
-      // let base64 = await parseImage(url)
-
-      widget.div.querySelector('.preview').innerHTML = `<img src="${url}"/>`
-
-      const uploadWidget = node.widgets.filter(w => w.name == 'upload')[0]
-      uploadWidget.value = await uploadWidget.serializeValue()
-
-      // let h=~~getComputedStyle(widget.div).height.replace('px','');
-      // let w=~~getComputedStyle(widget.div).width.replace('px','');
-      // // console.log('svg', w,h,node.size)
-      // node.setSize([
-      //   w,h
-      // ])
-      // app.graph.setDirtyCanvas(true)
-
-      // console.log(node.widgets_values)
-    }
-  }
-})
+})

web/javascript/layer_mixlab.js

@@ -69,12 +69,12 @@ const parseSvg = async svgContent => {
 
   Array.from(rectElements, (rectElement, i) => {
     // 获取rect元素的属性值
-    var x = ~~(rectElement.getAttribute('x')||0);
-    var y = ~~(rectElement.getAttribute('y')||0);
+    var x = ~~(rectElement.getAttribute('x') || 0)
+    var y = ~~(rectElement.getAttribute('y') || 0)
     var width = ~~rectElement.getAttribute('width')
     var height = ~~rectElement.getAttribute('height')
     // console.log('rectElements',rectElement,x,y,width,height)
-    if (x != undefined && y != undefined&&width&&height) {
+    if (x != undefined && y != undefined && width && height) {
       // 创建一个新的canvas元素
       var canvas = document.createElement('canvas')
       canvas.width = width
@@ -101,7 +101,7 @@ const parseSvg = async svgContent => {
         image: base64,
         mask: base64,
         type: 'base64',
-        _t:'rect'
+        _t: 'rect'
       }
 
       // 将处理后的数据添加到数组中
@@ -115,9 +115,9 @@ const parseSvg = async svgContent => {
   if (!(svgWidth && svgHeight)) {
     // viewBox
     let viewBox = svgElement.viewBox.baseVal
-     
-    svgWidth =viewBox.width
-    svgHeight =viewBox.height
+
+    svgWidth = viewBox.width
+    svgHeight = viewBox.height
   }
 
   // 创建一个新的canvas元素
@@ -147,15 +147,146 @@ const parseSvg = async svgContent => {
     image: base64,
     mask: base64,
     type: 'base64',
-    _t:'canvas'
+    _t: 'canvas'
   }
   data.push(rectData)
 
   // 打印处理后的数据
-  console.log('layers',{ data, image: base64, svgElement })
+  console.log('layers', { data, image: base64, svgElement })
   return { data, image: base64, svgElement }
 }
 
+async function setArea (cw, ch, base64, data, fn) {
+  let displayHeight = Math.round(window.screen.availHeight * 0.6)
+  let div = document.createElement('div')
+  div.innerHTML = `
+    <div id='ml_overlay' style='position: absolute;top:0;background: #251f1fc4;
+    height: 100vh;
+    z-index:999999;
+    width: 100%;'>
+      <img id='ml_video' style='position: absolute; 
+      height: ${displayHeight}px;user-select: none; 
+      -webkit-user-drag: none;
+      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>
+    </div>`
+  // document.body.querySelector('#ml_overlay')
+  document.body.appendChild(div)
+
+  // let canvas = document.createElement('canvas')
+  // canvas.width = cw
+  // canvas.height = ch
+
+  let img = div.querySelector('#ml_video')
+  let overlay = div.querySelector('#ml_overlay')
+  let selection = div.querySelector('#ml_selection')
+  let startX, startY, endX, endY
+  let start = false
+  // Set video source
+  img.src = base64
+  // canvas.toDataURL();
+
+  // init area
+  // const data = getSetAreaData()
+  let x = 0,
+    y = 0,
+    width = (cw * displayHeight) / ch,
+    height = displayHeight
+
+  let imgWidth = cw
+  let imgHeight = ch
+
+  if (data && data.width > 0 && data.height > 0) {
+    // 相同尺寸窗口，恢复选区
+    x = (width * data.x) / imgWidth
+    y = (height * data.y) / imgHeight
+    width = (width * data.width) / imgWidth
+    height = (height * data.height) / imgHeight
+  }
+
+  selection.style.left = x + 'px'
+  selection.style.top = y + 'px'
+  selection.style.width = width + 'px'
+  selection.style.height = height + 'px'
+
+  // Add mouse events
+  img.addEventListener('mousedown', startSelection)
+  img.addEventListener('mousemove', updateSelection)
+  img.addEventListener('mouseup', endSelection)
+  overlay.addEventListener('click', remove)
+
+  function remove () {
+    overlay.removeEventListener('click', remove)
+    img.removeEventListener('mousedown', startSelection)
+    img.removeEventListener('mousemove', updateSelection)
+    img.removeEventListener('mouseup', endSelection)
+    div.remove()
+  }
+
+  function startSelection (event) {
+    if (start == false) {
+      startX = event.clientX
+      startY = event.clientY
+      updateSelection(event)
+      start = true
+    } else {
+    }
+  }
+
+  function updateSelection (event) {
+    endX = event.clientX
+    endY = event.clientY
+
+    // Calculate width, height, and coordinates
+    let width = Math.abs(endX - startX)
+    let height = Math.abs(endY - startY)
+    let left = Math.min(startX, endX)
+    let top = Math.min(startY, endY)
+
+    // Set selection style
+    selection.style.left = left + 'px'
+    selection.style.top = top + 'px'
+    selection.style.width = width + 'px'
+    selection.style.height = height + 'px'
+  }
+
+  function endSelection (event) {
+    endX = event.clientX
+    endY = event.clientY
+
+    // 获取img元素的真实宽度和高度
+    let imgWidth = img.naturalWidth
+    let imgHeight = img.naturalHeight
+
+    // 换算起始坐标
+    let realStartX = (startX / img.offsetWidth) * imgWidth
+    let realStartY = (startY / img.offsetHeight) * imgHeight
+
+    // 换算起始坐标
+    let realEndX = (endX / img.offsetWidth) * imgWidth
+    let realEndY = (endY / img.offsetHeight) * imgHeight
+
+    startX = realStartX
+    startY = realStartY
+    endX = realEndX
+    endY = realEndY
+    // Calculate width, height, and coordinates
+    let width = Math.round(Math.abs(endX - startX))
+    let height = Math.round(Math.abs(endY - startY))
+    let left = Math.round(Math.min(startX, endX))
+    let top = Math.round(Math.min(startY, endY))
+
+    if (width <= 0 && height <= 0) return remove()
+
+    if (fn) fn(left, top, width, height)
+
+    remove()
+  }
+}
+
 app.registerExtension({
   name: 'Mixlab.layer.ShowLayer',
   async getCustomWidgets (app) {
@@ -199,8 +330,7 @@ app.registerExtension({
         const findNode = nodeId => {
           let node = app.graph._nodes_by_id[nodeId]
           if (node?.type == 'Reroute') {
-            
-            let linkId =node.inputs.filter(i=>i.type=='*')[0].link
+            let linkId = node.inputs.filter(i => i.type == '*')[0].link
             nodeId = app.graph.links.filter(link => link.id == linkId)[0]
               ?.origin_id
             return findNode(nodeId)
@@ -211,15 +341,17 @@ app.registerExtension({
 
         // 获取layers数据
         const getLayers = async () => {
-          console.log('getLayers1',this.inputs.filter(ip => ip.name === 'layers'))
+          console.log(
+            'getLayers1',
+            this.inputs.filter(ip => ip.name === 'layers')
+          )
           let linkId = this.inputs.filter(ip => ip.name === 'layers')[0].link
           let nodeId = app.graph.links?.filter(link => link.id == linkId)[0]
-            ?.origin_id;
+            ?.origin_id
 
-          if(nodeId){
+          if (nodeId) {
             nodeId = findNode(nodeId)
           }
-          
 
           //   let node = app.graph._nodes_by_id[nodeId]
           //   if (node?.type == 'Reroute') {
@@ -227,18 +359,18 @@ app.registerExtension({
           //     nodeId = app.graph.links.filter(link => link.id == linkId)[0]
           //       ?.origin_id
           //   }
-         
+
           let d = getLocalData('_mixlab_svg_image')
-          console.log('test',d[nodeId])
+          console.log('test', d[nodeId])
 
           if (d[nodeId]) {
             let url = d[nodeId]
             let dt = await fetch(url)
-           
+
             let svgStr = await dt.text()
-           
+
             const { data } = (await parseSvg(svgStr)) || {}
-            console.log('fetch',data)
+            console.log('fetch', data)
             return data
           } else {
             return []
@@ -350,3 +482,78 @@ app.registerExtension({
     }
   }
 })
+
+app.registerExtension({
+  name: 'Mixlab.layer.NewLayer',
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeData.name === 'NewLayer') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = async function () {
+        orig_nodeCreated?.apply(this, arguments)
+
+        let b = this.widgets.filter(w => w.type === 'button')[0]
+        // const [w, h, base64] = canvas
+
+        if (!b) {
+          const updateValue = (x1, y1, w1, h1) => {
+            if (this.widgets) {
+              for (const widget of this.widgets) {
+                if (widget.name === 'x') {
+                  widget.value = x1
+                }
+                if (widget.name === 'y') {
+                  widget.value = y1
+                }
+                if (widget.name === 'width') {
+                  widget.value = w1
+                }
+                if (widget.name === 'height') {
+                  widget.value = h1
+                }
+              }
+            }
+          }
+
+          this.addWidget('button', 'Set Area', '', () => {
+            let data = {}
+            for (const widget of this.widgets) {
+              if (widget.name === 'x') {
+                data.x = widget.value
+              }
+              if (widget.name === 'y') {
+                data.y = widget.value
+              }
+              if (widget.name === 'width') {
+                data.width = widget.value
+              }
+              if (widget.name === 'height') {
+                data.height = widget.value
+              }
+            }
+            try {
+              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)
+            } catch (error) {}
+          })
+        }
+      }
+
+      const onRemoved = this.onRemoved
+      this.onRemoved = () => {
+        // let b = this.widgets.filter(w => w.type === 'button')[0];
+
+        return onRemoved?.()
+      }
+
+      if (this.onResize) {
+        this.onResize(this.size)
+      }
+
+      this.serialize_widgets = true //需要保存参数
+    }
+  }
+})

web/javascript/main_mixlab.js

@@ -485,7 +485,7 @@ function get_position_style (ctx, widget_width, y, node_height) {
     // maxHeight: `${node_height - MARGIN * 2}px`, // we're assuming we have the whole height of the node
     width: `${widget_width - MARGIN * 2}px`,
     // height: `${node_height - MARGIN * 2}px`,
-    background: '#EEEEEE',
+    // background: '#EEEEEE',
     display: 'flex',
     flexDirection: 'column',
     // alignItems: 'center',
@@ -596,7 +596,7 @@ app.registerExtension({
           type: 'HTML', // whatever
           name: 'sreen_share', // whatever
           draw (ctx, node, widget_width, y, widget_height) {
-            console.log('ScreenSHare', y, widget_height)
+            // console.log('ScreenSHare', y, widget_height)
             Object.assign(
               this.card.style,
               get_position_style(
@@ -609,9 +609,15 @@ app.registerExtension({
           }
         }
 
-        widget.card = $el('div', {})
+        widget.card = $el('div', {
+          color: 'var(--descrip-text)',
+          backgroundColor: 'var(--comfy-input-bg)'
+        })
 
-        widget.previewCard = $el('div', {})
+        widget.previewCard = $el('div', {
+          color: 'var(--descrip-text)',
+          backgroundColor: 'var(--comfy-input-bg)'
+        })
 
         widget.preview = $el('video', {
           style: {
@@ -623,7 +629,10 @@ app.registerExtension({
         })
 
         widget.previewArea = $el('div', {
-          style: {}
+          style: {
+            color: 'var(--descrip-text)',
+            backgroundColor: 'var(--comfy-input-bg)'
+          }
         })
 
         widget.shareDiv = $el('div', {
@@ -631,7 +640,9 @@ app.registerExtension({
           style: {
             cursor: 'pointer',
             fontWeight: '300',
-            display: 'flex'
+            display: 'flex',
+            color: 'var(--descrip-text)',
+            backgroundColor: 'var(--comfy-input-bg)'
           }
         })
 
@@ -642,7 +653,12 @@ app.registerExtension({
             padding: '8px 0',
             fontWeight: '300',
             margin: '2px',
-            width: '100%'
+            width: '100%',
+            color: 'var(--descrip-text)',
+            backgroundColor: 'var(--comfy-input-bg)',
+            borderRadius: '8px',
+            borderColor: 'var(--border-color)',
+            borderStyle: 'solid'
           }
         })
 
@@ -653,7 +669,12 @@ app.registerExtension({
             padding: '8px 0',
             fontWeight: '300',
             margin: '2px',
-            width: '100%'
+            width: '100%',
+            color: 'var(--descrip-text)',
+            backgroundColor: 'var(--comfy-input-bg)',
+            borderRadius: '8px',
+            borderColor: 'var(--border-color)',
+            borderStyle: 'solid'
           }
         })
 
@@ -663,7 +684,12 @@ app.registerExtension({
             cursor: 'pointer',
             padding: '8px 0',
             fontWeight: '300',
-            margin: '2px'
+            margin: '2px',
+            color: 'var(--descrip-text)',
+            backgroundColor: 'var(--comfy-input-bg)',
+            borderRadius: '8px',
+            borderColor: 'var(--border-color)',
+            borderStyle: 'solid'
           }
         })
 
@@ -671,21 +697,30 @@ app.registerExtension({
           placeholder: '  Refresh rate:200 ms',
           type: 'number',
           min: 100,
-          step: 100,
+          step: 100, 
           style: {
             cursor: 'pointer',
-            padding: '8px 0',
+            padding: '8px 24px',
             fontWeight: '300',
-            margin: '2px'
+            margin: '2px',
+            color: 'var(--descrip-text)',
+            backgroundColor: 'var(--comfy-input-bg)'
           }
-        })
+        });
+        widget.refreshInput.className='comfy-multiline-input'
+        
         widget.liveBtn = $el('button', {
           innerText: 'Live Run',
           style: {
             cursor: 'pointer',
             padding: '8px 0',
             fontWeight: '300',
-            margin: '2px'
+            margin: '2px',
+            color: 'var(--descrip-text)',
+            backgroundColor: 'var(--comfy-input-bg)',
+            borderRadius: '8px',
+            borderColor: 'var(--border-color)',
+            borderStyle: 'solid'
           }
         })
 
@@ -890,7 +925,7 @@ app.registerExtension({
         })
         // console.log('widget.inputEl',widget.inputEl)
 
-        this.setSize([this.size[0],this.size[1]+450])
+        this.setSize([this.size[0], this.size[1] + 450])
         app.canvas.draw(true, true)
 
         /*
@@ -1001,6 +1036,7 @@ async function setArea (src) {
   div.innerHTML = `
     <div id='ml_overlay' style='position: absolute;top:0;background: #251f1fc4;
     height: 100vh;
+    z-index:999999;
     width: 100%;'>
       <img id='ml_video' style='position: absolute; 
       height: ${displayHeight}px;user-select: none; 
@@ -1032,12 +1068,7 @@ async function setArea (src) {
     height = displayHeight
   let imgWidth = im.naturalWidth
   let imgHeight = im.naturalHeight
-  // console.log(
-  //   '#screen_share::使用上一次选区 selection',
-  //   data,
-  //   imgWidth,
-  //   img.width
-  // )
+
   if (
     data &&
     data.width > 0 &&
@@ -1051,9 +1082,6 @@ async function setArea (src) {
     y = (img.height * data.y) / data.imgHeight
     width = (img.width * data.width) / data.imgWidth
     height = (img.height * data.height) / data.imgHeight
-    // imgWidth = data.imgWidth
-    // imgHeight = data.imgHeight;
-    // console.log('#screen_share::使用上一次选区 selection', x, y, width, height)
   }
 
   selection.style.left = x + 'px'
@@ -1118,9 +1146,6 @@ async function setArea (src) {
     let realEndX = (endX / img.offsetWidth) * imgWidth
     let realEndY = (endY / img.offsetHeight) * imgHeight
 
-    // 输出结果到控制台
-    // console.log('真实宽度: ' + realWidth)
-    // console.log('真实高度: ' + realHeight)
     startX = realStartX
     startY = realStartY
     endX = realEndX
@@ -1130,19 +1155,6 @@ async function setArea (src) {
     let height = Math.abs(endY - startY)
     let left = Math.min(startX, endX)
     let top = Math.min(startY, endY)
-    // Output results to console
-    // console.log('坐标位置: (' + left + ', ' + top + ')')
-    // console.log('宽度: ' + width)
-    // console.log('高度: ' + height)
-
-    // img.removeEventListener('mousedown', startSelection)
-    // img.removeEventListener('mousemove', updateSelection)
-    // img.removeEventListener('mouseup', endSelection)
-
-    // window._mixlab_screen_x = left
-    // window._mixlab_screen_y = top
-    // window._mixlab_screen_width = width
-    // window._mixlab_screen_height = height
 
     if (width <= 0 && height <= 0) return remove()
 
@@ -1154,7 +1166,6 @@ async function setArea (src) {
       window._mixlab_screen_webcamVideo,
       !window._mixlab_screen_live
     )
-
     remove()
   }
 }
@@ -1255,7 +1266,12 @@ app.registerExtension({
             cursor: 'pointer',
             padding: '8px 0',
             fontWeight: '300',
-            margin: '2px'
+            margin: '2px',
+            color: 'var(--descrip-text)',
+            backgroundColor: 'var(--comfy-input-bg)',
+            borderRadius: '8px',
+            borderColor: 'var(--border-color)',
+            borderStyle: 'solid'
           }
         })
 
@@ -1421,7 +1437,8 @@ app.registerExtension({
             )
 
             try {
-              pipWindow.document.querySelector('#info').innerText =window._mixlab_screen_seed_input
+              pipWindow.document.querySelector('#info').innerText =
+                window._mixlab_screen_seed_input
             } catch (error) {
               console.log(error)
             }

workflow/nodes_map.json

@@ -0,0 +1,828 @@
+{
+  "last_node_id": 23,
+  "last_link_id": 0,
+  "nodes": [
+    {
+      "id": 7,
+      "type": "ResizeImageMixlab",
+      "pos": [
+        1096.229866976564,
+        731.8207909156248
+      ],
+      "size": {
+        "0": 315,
+        "1": 106
+      },
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": null
+        }
+      ],
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ResizeImageMixlab"
+      },
+      "widgets_values": [
+        512,
+        512,
+        "width"
+      ]
+    },
+    {
+      "id": 8,
+      "type": "LoadImagesFromPath",
+      "pos": [
+        1101.229866976564,
+        900.8207909156248
+      ],
+      "size": {
+        "0": 315,
+        "1": 238
+      },
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": null,
+          "shape": 6
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null,
+          "shape": 6
+        },
+        {
+          "name": "STRING",
+          "type": "STRING",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "LoadImagesFromPath"
+      },
+      "widgets_values": [
+        "C:\\Users\\38957\\Documents\\GitHub\\extract-anything\\outputs",
+        "disable",
+        "enable",
+        0,
+        "disable",
+        null,
+        null
+      ]
+    },
+    {
+      "id": 3,
+      "type": "ShowTextForGPT",
+      "pos": [
+        1786,
+        252
+      ],
+      "size": {
+        "0": 315,
+        "1": 58
+      },
+      "flags": {},
+      "order": 2,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": null,
+          "widget": {
+            "name": "text"
+          }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "STRING",
+          "type": "STRING",
+          "links": null,
+          "shape": 6
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ShowTextForGPT"
+      },
+      "widgets_values": [
+        ""
+      ]
+    },
+    {
+      "id": 9,
+      "type": "TextImage",
+      "pos": [
+        1448.4608623625004,
+        735.0514200906249
+      ],
+      "size": {
+        "0": 315,
+        "1": 198
+      },
+      "flags": {},
+      "order": 3,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "IMAGE",
+          "type": "IMAGE",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "MASK",
+          "type": "MASK",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "TextImage"
+      },
+      "widgets_values": [
+        "龍馬精神迎新歲",
+        "C:\\Users\\38957\\Documents\\ai-lab\\ComfyUI_windows_portable\\ComfyUI\\custom_nodes\\comfyui-mixlab-nodes\\assets\\王汉宗颜楷体繁.ttf",
+        100,
+        12,
+        "#000000",
+        true
+      ]
+    },
+    {
+      "id": 2,
+      "type": "ChatGPTOpenAI",
+      "pos": [
+        1086,
+        235
+      ],
+      "size": {
+        "0": 400,
+        "1": 358
+      },
+      "flags": {},
+      "order": 4,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "messages",
+          "type": "STRING",
+          "links": null,
+          "shape": 3
+        },
+        {
+          "name": "session_history",
+          "type": "STRING",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ChatGPTOpenAI"
+      },
+      "widgets_values": [
+        null,
+        null,
+        "",
+        "You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.",
+        "gpt-3.5-turbo",
+        0,
+        "randomize",
+        1,
+        null
+      ]
+    },
+    {
+      "id": 16,
+      "type": "SpeechRecognition",
+      "pos": [
+        2892.502226325001,
+        724.176680771093
+      ],
+      "size": {
+        "0": 322.593505859375,
+        "1": 135.22850036621094
+      },
+      "flags": {},
+      "order": 5,
+      "mode": 0,
+      "outputs": [
+        {
+          "name": "prompt",
+          "type": "STRING",
+          "links": null,
+          "shape": 3
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "SpeechRecognition"
+      },
+      "widgets_values": [
+        null,
+        null
+      ]
+    },
+    {
+      "id": 17,
+      "type": "SpeechSynthesis",
+      "pos": [
+        2901.502226325001,
+        924.1766807710948
+      ],
+      "size": {
+        "0": 315,
+        "1": 58
+      },
+      "flags": {},
+      "order": 6,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "text",
+          "type": "STRING",
+          "link": null,
+          "widget": {
+            "name": "text"
+          }
+        }
+      ],
+      "outputs": [
+        {
+          "name": "STRING",
+          "type": "STRING",
+          "links": null,
+          "shape": 6
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "SpeechSynthesis"
+      },
+      "widgets_values": [
+        ""
+      ]
+    },
+    {
+      "id": 18,
+      "type": "ShowLayer",
+      "pos": [
+        2157.913220668749,
+        232.7887044208986
+      ],
+      "size": {
+        "0": 315,
+        "1": 226
+      },
+      "flags": {},
+      "order": 7,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "layers",
+          "type": "LAYER",
+          "link": null
+        }
+      ],
+      "properties": {
+        "Node name for S&R": "ShowLayer"
+      }
+    },
+    {
+      "id": 19,
+      "type": "NewLayer",
+      "pos": [
+        2494.913220668749,
+        232.7887044208986
+      ],
+      "size": {
+        "0": 315,
+        "1": 218
+      },
+      "flags": {},
+      "order": 8,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "image",
+          "type": "IMAGE",
+          "link": null
+        },
+        {
+          "name": "mask",
+          "type": "MASK",
+          "link": null
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+}