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@@ -1,15 +1,25 @@
|
||||
##
|
||||
v0.3.0 🚀🚗🚚🏃
|
||||
|
||||
v0.2.6 🚀🚗🚚🏃
|
||||
- Added support for setting proxies: HTTP_PROXY, HTTPS_PROXY, http_proxy, https_proxy ✅
|
||||
|
||||
- [Add getting camera video stream](./workflow/7-camera-workflow.json)
|
||||
- Add a slider to the floating window, which can be used as input for denoise
|
||||
- OSupport for calling multiple GPTs
|
||||
- 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 🌟
|
||||
|
||||
|
||||

|
||||
|
||||
|
||||
### SpeechRecognition & SpeechSynthesis
|
||||

|
||||
|
||||
[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! 💻🌐
|
||||
|
||||
@@ -33,7 +43,7 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
|
||||
|
||||
|
||||
### GPT
|
||||
>Support for calling multiple GPTs.ChatGPT、ChatGLM3 , Some code provided by rui. If you are using OpenAI's service, fill in https://api.openai.com/v1 . If you are using a local LLM service, fill in http://127.0.0.1:xxxx/v1 . Azure OpenAI:https://xxxx.openai.azure.com
|
||||
> 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
|
||||
|
||||
|
||||

|
||||
@@ -41,38 +51,14 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
|
||||
[workflow-5](./workflow/5-gpt-workflow.json)
|
||||
|
||||
|
||||
## Installation
|
||||
### 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.
|
||||
|
||||
manually install, simply clone the repo into the custom_nodes directory with this command:
|
||||

|
||||
|
||||
```
|
||||
cd ComfyUI/custom_nodes
|
||||

|
||||
|
||||
git clone https://github.com/shadowcz007/comfyui-mixlab-nodes.git
|
||||
|
||||
```
|
||||
|
||||
Install the requirements:
|
||||
|
||||
run directly:
|
||||
```
|
||||
cd ComfyUI_Mixlab
|
||||
install.bat
|
||||
```
|
||||
|
||||
or install the requirements using:
|
||||
```
|
||||
../../../python_embeded/python.exe -s -m pip install -r requirements.txt
|
||||
```
|
||||
|
||||
If you are using a venv, make sure you have it activated before installation and use:
|
||||
```
|
||||
pip3 install -r requirements.txt
|
||||
```
|
||||
|
||||
|
||||
|
||||
## Nodes
|
||||
## Other Nodes
|
||||
|
||||

|
||||

|
||||
@@ -88,9 +74,6 @@ pip3 install -r requirements.txt
|
||||

|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
> Consistency Decoder
|
||||
|
||||
[openai Consistency Decoder]( https://github.com/openai/consistencydecoder)
|
||||
@@ -120,6 +103,42 @@ An improvement has been made to directly redirect to GitHub to search for missin
|
||||
<!-- ### Workflow
|
||||
[Workflow](./workflow.md) -->
|
||||
|
||||
|
||||
|
||||
## Installation
|
||||
|
||||
manually install, simply clone the repo into the custom_nodes directory with this command:
|
||||
|
||||
```
|
||||
cd ComfyUI/custom_nodes
|
||||
|
||||
git clone https://github.com/shadowcz007/comfyui-mixlab-nodes.git
|
||||
|
||||
```
|
||||
|
||||
Install the requirements:
|
||||
|
||||
run directly:
|
||||
```
|
||||
cd ComfyUI/custom_nodes/comfyui-mixlab-nodes
|
||||
install.bat
|
||||
```
|
||||
|
||||
or install the requirements using:
|
||||
```
|
||||
../../../python_embeded/python.exe -s -m pip install -r requirements.txt
|
||||
```
|
||||
|
||||
If you are using a venv, make sure you have it activated before installation and use:
|
||||
```
|
||||
pip3 install -r requirements.txt
|
||||
```
|
||||
|
||||
#### Chinese community
|
||||
访问 [www.mixcomfy.com](https://www.mixcomfy.com),获得更多内测功能,关注微信公众号:Mixlab无界社区
|
||||
|
||||
|
||||
|
||||
#### Thanks:
|
||||
[ComfyUI-CLIPSeg](https://github.com/biegert/ComfyUI-CLIPSeg/tree/main)
|
||||
|
||||
@@ -127,5 +146,26 @@ An improvement has been made to directly redirect to GitHub to search for missin
|
||||
[discussions](https://github.com/shadowcz007/comfyui-mixlab-nodes/discussions)
|
||||
|
||||
### TODO:
|
||||
- 音频播放节点:带可视化、支持多音轨、可配置音轨音量
|
||||
- vector https://github.com/GeorgLegato/stable-diffusion-webui-vectorstudio
|
||||
|
||||
|
||||
<picture>
|
||||
<source
|
||||
media="(prefers-color-scheme: dark)"
|
||||
srcset="
|
||||
https://api.star-history.com/svg?repos=shadowcz007/comfyui-mixlab-nodes&type=Date&theme=dark
|
||||
"
|
||||
/>
|
||||
<source
|
||||
media="(prefers-color-scheme: light)"
|
||||
srcset="
|
||||
https://api.star-history.com/svg?repos=shadowcz007/comfyui-mixlab-nodes&type=Date
|
||||
"
|
||||
/>
|
||||
<img
|
||||
alt="Star History Chart"
|
||||
src="https://api.star-history.com/svg?repos=shadowcz007/comfyui-mixlab-nodes&type=Date"
|
||||
/>
|
||||
</picture>
|
||||
|
||||
|
||||
+70
-3
@@ -168,8 +168,44 @@ def save_workflow_json(data):
|
||||
json.dump(data, file)
|
||||
return workflow_path
|
||||
|
||||
|
||||
def get_nodes_map():
|
||||
# print("#####path::", current_path)
|
||||
data_path=os.path.join(current_path, "data")
|
||||
print('data_path: ',data_path)
|
||||
# if not os.path.exists(data_path):
|
||||
# # 使用mkdir()方法创建新目录
|
||||
# os.mkdir(data_path)
|
||||
json_data={}
|
||||
nodes_map=os.path.join(current_path, "data/extension-node-map.json")
|
||||
if os.path.exists(nodes_map):
|
||||
with open(nodes_map) as json_file:
|
||||
json_data = json.load(json_file)
|
||||
|
||||
return json_data
|
||||
|
||||
|
||||
# 保存原始的 get 方法
|
||||
_original_request = aiohttp.ClientSession._request
|
||||
|
||||
# 定义新的 get 方法
|
||||
async def new_request(self, method, url, *args, **kwargs):
|
||||
# 检查环境变量以确定是否使用代理
|
||||
proxy = os.environ.get('HTTP_PROXY') or os.environ.get('HTTPS_PROXY') or os.environ.get('http_proxy') or os.environ.get('https_proxy')
|
||||
# print('Proxy Config:',proxy)
|
||||
if proxy and 'proxy' not in kwargs:
|
||||
kwargs['proxy'] = proxy
|
||||
print('Use Proxy:',proxy)
|
||||
# 调用原始的 _request 方法
|
||||
return await _original_request(self, method, url, *args, **kwargs)
|
||||
|
||||
# 应用 Monkey Patch
|
||||
aiohttp.ClientSession._request = new_request
|
||||
|
||||
# https
|
||||
async def new_start(self, address, port, verbose=True, call_on_start=None):
|
||||
|
||||
|
||||
runner = web.AppRunner(self.app, access_log=None)
|
||||
await runner.setup()
|
||||
site = web.TCPSite(runner, address, port)
|
||||
@@ -239,6 +275,20 @@ async def mixlab_workflow_hander(request):
|
||||
|
||||
return web.json_response(result)
|
||||
|
||||
@routes.post('/mixlab/nodes_map')
|
||||
async def nodes_map_hander(request):
|
||||
data = await request.json()
|
||||
result={}
|
||||
try:
|
||||
result={
|
||||
'data':get_nodes_map(),
|
||||
'status':'success',
|
||||
}
|
||||
except Exception as e:
|
||||
print(e)
|
||||
|
||||
return web.json_response(result)
|
||||
|
||||
def new_add_routes(self):
|
||||
import nodes
|
||||
self.app.add_routes(routes)
|
||||
@@ -268,11 +318,14 @@ PromptServer.add_routes=new_add_routes
|
||||
|
||||
# 导入节点
|
||||
from .nodes.PromptNode import RandomPrompt
|
||||
from .nodes.ImageNode import TransparentImage,LoadImagesFromPath,AreaToMask,SmoothMask,FeatheredMask,SplitLongMask,ImageCropByAlpha,EnhanceImage,FaceToMask
|
||||
from .nodes.ImageNode import TransparentImage,LoadImagesFromPath,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
|
||||
from .nodes.ChatGPT import ChatGPTNode,ShowTextForGPT,CharacterInText
|
||||
from .nodes.Audio import SpeechRecognition,SpeechSynthesis
|
||||
from .nodes.Utils import ColorInput,FontInput
|
||||
|
||||
|
||||
# 要导出的所有节点及其名称的字典
|
||||
# 注意:名称应全局唯一
|
||||
@@ -280,7 +333,14 @@ NODE_CLASS_MAPPINGS = {
|
||||
"RandomPrompt":RandomPrompt,
|
||||
"TransparentImage":TransparentImage,
|
||||
"LoadImagesFromPath":LoadImagesFromPath,
|
||||
"TextImage":TextImage,
|
||||
"EnhanceImage":EnhanceImage,
|
||||
"SvgImage":SvgImage,
|
||||
"3DImage":Image3D,
|
||||
"EmptyLayer":EmptyLayer,
|
||||
"ShowLayer":ShowLayer,
|
||||
"NewLayer":NewLayer,
|
||||
"MergeLayers":MergeLayers,
|
||||
"SplitLongMask":SplitLongMask,
|
||||
"FeatheredMask":FeatheredMask,
|
||||
"SmoothMask":SmoothMask,
|
||||
@@ -295,7 +355,11 @@ NODE_CLASS_MAPPINGS = {
|
||||
"CombineMasks_":CombineMasks,
|
||||
"ChatGPTOpenAI":ChatGPTNode,
|
||||
"ShowTextForGPT":ShowTextForGPT,
|
||||
"CharacterInText":CharacterInText
|
||||
"CharacterInText":CharacterInText,
|
||||
"SpeechRecognition":SpeechRecognition,
|
||||
"SpeechSynthesis":SpeechSynthesis,
|
||||
"Color":ColorInput,
|
||||
"Font":FontInput
|
||||
}
|
||||
|
||||
# 一个包含节点友好/可读的标题的字典
|
||||
@@ -307,7 +371,10 @@ NODE_DISPLAY_NAME_MAPPINGS = {
|
||||
"ScreenShare":"ScreenShare ♾️Mixlab",
|
||||
"FloatingVideo":"FloatingVideo ♾️Mixlab",
|
||||
"ChatGPTOpenAI":"ChatGPT ♾️Mixlab",
|
||||
"ShowTextForGPT":"ShowTextForGPT ♾️Mixlab"
|
||||
"ShowTextForGPT":"ShowTextForGPT ♾️Mixlab",
|
||||
"MergeLayers":"MergeLayers ♾️Mixlab",
|
||||
"SpeechSynthesis":"SpeechSynthesis ♾️Mixlab",
|
||||
"SpeechRecognition":"SpeechRecognition ♾️Mixlab"
|
||||
}
|
||||
|
||||
# web ui的节点功能
|
||||
|
||||
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Load Diff
@@ -0,0 +1,46 @@
|
||||
|
||||
|
||||
|
||||
|
||||
class SpeechRecognition:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": {
|
||||
"upload":("AUDIOINPUTMIX",), },
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("STRING",)
|
||||
RETURN_NAMES = ("prompt",)
|
||||
|
||||
FUNCTION = "run"
|
||||
|
||||
CATEGORY = "♾️Mixlab/audio"
|
||||
|
||||
INPUT_IS_LIST = False
|
||||
OUTPUT_IS_LIST = (False,)
|
||||
|
||||
def run(self,upload):
|
||||
return (upload,)
|
||||
|
||||
|
||||
class SpeechSynthesis:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {
|
||||
"required": {
|
||||
"text": ("STRING", {"forceInput": True}),
|
||||
}
|
||||
}
|
||||
|
||||
INPUT_IS_LIST = True
|
||||
RETURN_TYPES = ("STRING",)
|
||||
FUNCTION = "run"
|
||||
OUTPUT_NODE = True
|
||||
OUTPUT_IS_LIST = (True,)
|
||||
|
||||
CATEGORY = "♾️Mixlab/audio"
|
||||
|
||||
def run(self, text):
|
||||
# print(session_history)
|
||||
return {"ui": {"text": text}, "result": (text,)}
|
||||
|
||||
+1
-1
@@ -46,7 +46,7 @@ def chat(client, model_name,messages ):
|
||||
except (urllib.error.HTTPError, openai.OpenAIError) as ex:
|
||||
if try_count >= 3:
|
||||
raise ex
|
||||
time.sleep(5)
|
||||
time.sleep(3)
|
||||
continue
|
||||
|
||||
finish_reason = response.choices[0].finish_reason
|
||||
|
||||
+7
-4
@@ -1,3 +1,6 @@
|
||||
#### Thanks:
|
||||
# [ComfyUI-CLIPSeg](https://github.com/biegert/ComfyUI-CLIPSeg/tree/main)
|
||||
|
||||
from transformers import CLIPSegProcessor, CLIPSegForImageSegmentation
|
||||
|
||||
from PIL import Image
|
||||
@@ -252,7 +255,7 @@ class CombineMasks:
|
||||
|
||||
# A dictionary that contains all nodes you want to export with their names
|
||||
# NOTE: names should be globally unique
|
||||
NODE_CLASS_MAPPINGS = {
|
||||
"CLIPSeg": CLIPSeg,
|
||||
"CombineSegMasks": CombineMasks,
|
||||
}
|
||||
# NODE_CLASS_MAPPINGS = {
|
||||
# "CLIPSeg": CLIPSeg,
|
||||
# "CombineSegMasks": CombineMasks,
|
||||
# }
|
||||
|
||||
+516
-3
@@ -1,17 +1,18 @@
|
||||
import numpy as np
|
||||
import torch
|
||||
from PIL import Image, ImageOps,ImageFilter,ImageEnhance,ImageDraw,ImageSequence
|
||||
from PIL import Image, ImageOps,ImageFilter,ImageEnhance,ImageDraw,ImageSequence, ImageFont
|
||||
from PIL.PngImagePlugin import PngInfo
|
||||
import base64,os
|
||||
from io import BytesIO
|
||||
import folder_paths
|
||||
import json
|
||||
import json,io
|
||||
from comfy.cli_args import args
|
||||
import cv2
|
||||
|
||||
from .Watcher import FolderWatcher
|
||||
|
||||
|
||||
FONT_PATH= os.path.abspath(os.path.join(os.path.dirname(__file__),'../assets/王汉宗颜楷体繁.ttf'))
|
||||
|
||||
MAX_RESOLUTION=8192
|
||||
|
||||
@@ -322,6 +323,117 @@ def areaToMask(x,y,w,h,image):
|
||||
return mask
|
||||
|
||||
|
||||
# def merge_images(bg_image, layer_image,mask, x, y, width, height):
|
||||
# # 打开底图
|
||||
# # bg_image = Image.open(background)
|
||||
# bg_image=bg_image.convert("RGBA")
|
||||
|
||||
# # 打开图层
|
||||
# layer_image=layer_image.convert("RGBA")
|
||||
# layer_image = layer_image.resize((width, height))
|
||||
# # mask = Image.new("L", layer_image.size, 255)
|
||||
# mask = mask.resize((width, height))
|
||||
# # 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
|
||||
# # bg_image.save("output.jpg")
|
||||
# return bg_image
|
||||
|
||||
def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option):
|
||||
# 打开底图
|
||||
bg_image = bg_image.convert("RGBA")
|
||||
|
||||
# 打开图层
|
||||
layer_image = layer_image.convert("RGBA")
|
||||
# layer_image = layer_image.resize((width, height))
|
||||
|
||||
# 根据缩放选项调整图像大小
|
||||
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))
|
||||
|
||||
# 调整mask的大小
|
||||
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)
|
||||
|
||||
# 输出合成后的图片
|
||||
return bg_image
|
||||
|
||||
|
||||
|
||||
def generate_text_image(text_list, font_path, font_size, text_color, vertical=True, spacing=0):
|
||||
# Load Chinese font
|
||||
font = ImageFont.truetype(font_path, font_size)
|
||||
|
||||
# Calculate image size based on the number of characters and orientation
|
||||
if vertical:
|
||||
width = font_size + 100
|
||||
height = font_size * len(text_list) + (len(text_list) - 1) * spacing + 100
|
||||
else:
|
||||
width = font_size * len(text_list) + (len(text_list) - 1) * spacing + 100
|
||||
height = font_size + 100
|
||||
|
||||
# Create a blank image
|
||||
image = Image.new('RGBA', (width, height), (255, 255, 255,0))
|
||||
draw = ImageDraw.Draw(image)
|
||||
|
||||
# Draw text
|
||||
if vertical:
|
||||
for i, char in enumerate(text_list):
|
||||
char_position = (50, 50 + i * font_size)
|
||||
draw.text(char_position, char, font=font, fill=text_color)
|
||||
else:
|
||||
for i, char in enumerate(text_list):
|
||||
char_position = (50 + i * (font_size + spacing), 50)
|
||||
draw.text(char_position, char, font=font, fill=text_color)
|
||||
|
||||
# Save the image
|
||||
# image.save(output_image_path)
|
||||
|
||||
# 分离alpha通道
|
||||
alpha_channel = image.split()[3]
|
||||
|
||||
# 创建一个只有alpha通道的新图像
|
||||
alpha_image = Image.new('L', image.size)
|
||||
alpha_image.putdata(alpha_channel.getdata())
|
||||
|
||||
image=image.convert('RGB')
|
||||
|
||||
return (image,alpha_image)
|
||||
|
||||
|
||||
def base64_to_image(base64_string):
|
||||
# 去除前缀
|
||||
prefix, base64_data = base64_string.split(",", 1)
|
||||
|
||||
# 从base64字符串中解码图像数据
|
||||
image_data = base64.b64decode(base64_data)
|
||||
|
||||
# 创建一个内存流对象
|
||||
image_stream = io.BytesIO(image_data)
|
||||
|
||||
# 使用PIL的Image模块打开图像数据
|
||||
image = Image.open(image_stream)
|
||||
|
||||
return image
|
||||
|
||||
|
||||
|
||||
class SmoothMask:
|
||||
@classmethod
|
||||
@@ -494,6 +606,7 @@ class TransparentImage:
|
||||
}
|
||||
|
||||
RETURN_TYPES = ('STRING','IMAGE','RGBA')
|
||||
RETURN_NAMES = ("file_path","IMAGE","RGBA",)
|
||||
|
||||
OUTPUT_NODE = True
|
||||
|
||||
@@ -671,7 +784,7 @@ class LoadImagesFromPath:
|
||||
imgs=[imgs[index_variable]] if index_variable < len(imgs) else None
|
||||
masks=[masks[index_variable]] if index_variable < len(masks) else None
|
||||
|
||||
print('#prompt::::',prompt)
|
||||
# print('#prompt::::',prompt)
|
||||
return (imgs,masks,prompt,)
|
||||
|
||||
|
||||
@@ -708,6 +821,117 @@ class ImageCropByAlpha:
|
||||
return (img,)
|
||||
|
||||
|
||||
|
||||
class TextImage:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": {
|
||||
|
||||
"text": ("STRING",{"multiline": False,"default": "龍馬精神迎新歲"}),
|
||||
"font_path": ("STRING",{"multiline": False,"default": FONT_PATH}),
|
||||
"font_size": ("INT",{
|
||||
"default":100,
|
||||
"min": 100, #Minimum value
|
||||
"max": 1000, #Maximum value
|
||||
"step": 1, #Slider's step
|
||||
"display": "number" # Cosmetic only: display as "number" or "slider"
|
||||
}),
|
||||
"spacing": ("INT",{
|
||||
"default":12,
|
||||
"min": 1, #Minimum value
|
||||
"max": 200, #Maximum value
|
||||
"step": 1, #Slider's step
|
||||
"display": "number" # Cosmetic only: display as "number" or "slider"
|
||||
}),
|
||||
"text_color":("STRING",{"multiline": False,"default": "#000000"}),
|
||||
"vertical":("BOOLEAN", {"default": True},),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("IMAGE","MASK")
|
||||
# RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
|
||||
|
||||
FUNCTION = "run"
|
||||
|
||||
CATEGORY = "♾️Mixlab/image"
|
||||
|
||||
INPUT_IS_LIST = False
|
||||
OUTPUT_IS_LIST = (False,False,)
|
||||
|
||||
def run(self,text,font_path,font_size,spacing,text_color,vertical):
|
||||
|
||||
text_list=list(text)
|
||||
|
||||
img,mask=generate_text_image(text_list,font_path,font_size,text_color,vertical,spacing)
|
||||
|
||||
img=pil2tensor(img)
|
||||
mask=pil2tensor(mask)
|
||||
|
||||
return (img,mask,)
|
||||
|
||||
|
||||
|
||||
class SvgImage:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": {
|
||||
"upload":("SVG",),},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("IMAGE","LAYER")
|
||||
RETURN_NAMES = ("IMAGE","layers",)
|
||||
|
||||
FUNCTION = "run"
|
||||
|
||||
CATEGORY = "♾️Mixlab/image"
|
||||
|
||||
INPUT_IS_LIST = False
|
||||
OUTPUT_IS_LIST = (False,True,)
|
||||
|
||||
def run(self,upload):
|
||||
layers=[]
|
||||
|
||||
image = base64_to_image(upload['image'])
|
||||
image=image.convert('RGB')
|
||||
image=pil2tensor(image)
|
||||
|
||||
for layer in upload['data']:
|
||||
layers.append(layer)
|
||||
|
||||
return (image,layers,)
|
||||
|
||||
|
||||
|
||||
class Image3D:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": {
|
||||
"upload":("THREED",), },
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("IMAGE","MASK",)
|
||||
# RETURN_NAMES = ("IMAGE",)
|
||||
|
||||
FUNCTION = "run"
|
||||
|
||||
CATEGORY = "♾️Mixlab/image"
|
||||
|
||||
INPUT_IS_LIST = False
|
||||
OUTPUT_IS_LIST = (False,False,)
|
||||
|
||||
def run(self,upload):
|
||||
# print(upload['image'])
|
||||
image = base64_to_image(upload['image'])
|
||||
image=image.convert('RGB')
|
||||
mask=image.convert('L')
|
||||
|
||||
mask=pil2tensor(mask)
|
||||
image=pil2tensor(image)
|
||||
|
||||
return (image,mask,)
|
||||
|
||||
|
||||
|
||||
class AreaToMask:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
@@ -770,3 +994,292 @@ class FaceToMask:
|
||||
|
||||
return (mask,)
|
||||
|
||||
|
||||
class EmptyLayer:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {
|
||||
"required": {
|
||||
"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"
|
||||
}),
|
||||
},
|
||||
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("LAYER",)
|
||||
RETURN_NAMES = ("layers",)
|
||||
|
||||
FUNCTION = "run"
|
||||
|
||||
CATEGORY = "♾️Mixlab/layer"
|
||||
|
||||
OUTPUT_IS_LIST = (True,)
|
||||
|
||||
def run(self, width,height):
|
||||
blank_image = Image.new("RGB", (width, height))
|
||||
|
||||
mask=blank_image.convert('L')
|
||||
|
||||
blank_image=pil2tensor(blank_image)
|
||||
mask=pil2tensor(mask)
|
||||
|
||||
layer_n=[{
|
||||
"x":0,
|
||||
"y":0,
|
||||
"width":width,
|
||||
"height":height,
|
||||
"z_index":0,
|
||||
"scale_option":'width',
|
||||
"image":blank_image,
|
||||
"mask":mask
|
||||
}]
|
||||
return (layer_n,)
|
||||
|
||||
|
||||
class NewLayer:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {
|
||||
|
||||
"required": {
|
||||
"x": ("INT",{
|
||||
"default": 0,
|
||||
"min": -100, #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
|
||||
"max": 8192, #Maximum value
|
||||
"step": 1, #Slider's step
|
||||
"display": "number" # Cosmetic only: display as "number" or "slider"
|
||||
}),
|
||||
"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"
|
||||
}),
|
||||
"z_index": ("INT",{
|
||||
"default": 0,
|
||||
"min":0, #Minimum value
|
||||
"max": 100, #Maximum value
|
||||
"step": 1, #Slider's step
|
||||
"display": "number" # Cosmetic only: display as "number" or "slider"
|
||||
}),
|
||||
"scale_option": (["width","height",'overall'],),
|
||||
"image": ("IMAGE",),
|
||||
},
|
||||
"optional":{
|
||||
"mask": ("MASK",{"default": None}),
|
||||
"layers": ("LAYER",{"default": None}),
|
||||
}
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("LAYER",)
|
||||
RETURN_NAMES = ("layers",)
|
||||
|
||||
FUNCTION = "run"
|
||||
|
||||
CATEGORY = "♾️Mixlab/layer"
|
||||
|
||||
INPUT_IS_LIST = True
|
||||
OUTPUT_IS_LIST = (True,)
|
||||
|
||||
def run(self,x,y,width,height,z_index,scale_option,image,mask,layers):
|
||||
# print(x,y,width,height,z_index,image,mask)
|
||||
|
||||
if mask==None:
|
||||
im=tensor2pil(image)
|
||||
mask=im.convert('L')
|
||||
mask=pil2tensor(mask)
|
||||
else:
|
||||
mask=mask[0]
|
||||
|
||||
layer_n=[{
|
||||
"x":x[0],
|
||||
"y":y[0],
|
||||
"width":width[0],
|
||||
"height":height[0],
|
||||
"z_index":z_index[0],
|
||||
"scale_option":scale_option[0],
|
||||
"image":image[0],
|
||||
"mask":mask
|
||||
}]
|
||||
|
||||
if layers!=None:
|
||||
layer_n=layer_n+layers
|
||||
|
||||
return (layer_n,)
|
||||
|
||||
|
||||
class ShowLayer:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {
|
||||
|
||||
"required": {
|
||||
"edit": ("EDIT",),
|
||||
|
||||
"x": ("INT",{
|
||||
"default": 0,
|
||||
"min": -100, #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
|
||||
"max": 8192, #Maximum value
|
||||
"step": 1, #Slider's step
|
||||
"display": "number" # Cosmetic only: display as "number" or "slider"
|
||||
}),
|
||||
"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"
|
||||
}),
|
||||
"z_index": ("INT",{
|
||||
"default": 0,
|
||||
"min":0, #Minimum value
|
||||
"max": 100, #Maximum value
|
||||
"step": 1, #Slider's step
|
||||
"display": "number" # Cosmetic only: display as "number" or "slider"
|
||||
}),
|
||||
"scale_option": (["width","height",'overall'],),
|
||||
# "image": ("IMAGE",),
|
||||
},
|
||||
"optional":{
|
||||
# "mask": ("MASK",{"default": None}),
|
||||
"layers": ("LAYER",{"default": None}),
|
||||
}
|
||||
}
|
||||
|
||||
RETURN_TYPES = ( )
|
||||
RETURN_NAMES = ( )
|
||||
|
||||
FUNCTION = "run"
|
||||
|
||||
CATEGORY = "♾️Mixlab/layer"
|
||||
|
||||
INPUT_IS_LIST = True
|
||||
# OUTPUT_IS_LIST = (True,)
|
||||
|
||||
def run(self,edit,x,y,width,height,z_index,scale_option,layers):
|
||||
# print(x,y,width,height,z_index,image,mask)
|
||||
|
||||
# if mask==None:
|
||||
# im=tensor2pil(image)
|
||||
# mask=im.convert('L')
|
||||
# mask=pil2tensor(mask)
|
||||
# else:
|
||||
# mask=mask[0]
|
||||
|
||||
# layers[edit[0]]={
|
||||
# "x":x[0],
|
||||
# "y":y[0],
|
||||
# "width":width[0],
|
||||
# "height":height[0],
|
||||
# "z_index":z_index[0],
|
||||
# "scale_option":scale_option[0],
|
||||
# "image":image[0],
|
||||
# "mask":mask
|
||||
# }
|
||||
|
||||
return ( )
|
||||
|
||||
|
||||
class MergeLayers:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": {
|
||||
"layers": ("LAYER",),
|
||||
"image": ("IMAGE",),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("IMAGE",)
|
||||
# RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
|
||||
|
||||
FUNCTION = "run"
|
||||
|
||||
CATEGORY = "♾️Mixlab/layer"
|
||||
|
||||
INPUT_IS_LIST = True
|
||||
# OUTPUT_IS_LIST = (False,)
|
||||
|
||||
def run(self,layers,image):
|
||||
# print(len(layers),len(image))
|
||||
bg_image=image[0]
|
||||
bg_image=tensor2pil(bg_image)
|
||||
# 按z-index排序
|
||||
layers_new = sorted(layers, key=lambda x: x["z_index"])
|
||||
|
||||
for layer in layers_new:
|
||||
image=layer['image']
|
||||
mask=layer['mask']
|
||||
if 'type' in layer and layer['type']=='base64' and type(image) == str:
|
||||
im=base64_to_image(image)
|
||||
im=im.convert('RGB')
|
||||
image=pil2tensor(im)
|
||||
|
||||
mask=base64_to_image(mask)
|
||||
mask=mask.convert('L')
|
||||
mask=pil2tensor(mask)
|
||||
|
||||
|
||||
layer_image=tensor2pil(image)
|
||||
layer_mask=tensor2pil(mask)
|
||||
bg_image=merge_images(bg_image,
|
||||
layer_image,
|
||||
layer_mask,
|
||||
layer['x'],
|
||||
layer['y'],
|
||||
layer['width'],
|
||||
layer['height'],
|
||||
layer['scale_option']
|
||||
)
|
||||
|
||||
mask=bg_image.convert('RGBA')
|
||||
mask=pil2tensor(mask)
|
||||
|
||||
bg_image=bg_image.convert('RGB')
|
||||
bg_image=pil2tensor(bg_image)
|
||||
|
||||
channels = ["red", "green", "blue", "alpha"]
|
||||
# print(mask,mask.shape)
|
||||
mask = mask[:, :, :, channels.index("green")]
|
||||
|
||||
return (bg_image,mask,)
|
||||
@@ -83,11 +83,12 @@ class ScreenShareNode:
|
||||
"optional":{
|
||||
"prompt": ("PROMPT",),
|
||||
"slide": ("SLIDE",),
|
||||
"seed": ("SEED",),
|
||||
# "seed": ("INT", {"default": 1, "min": 0, "max": 0xffffffffffffffff}),
|
||||
} }
|
||||
|
||||
RETURN_TYPES = ('IMAGE','STRING','FLOAT')
|
||||
RETURN_NAMES = ("IMAGE","PROMPT","FLOAT",)
|
||||
RETURN_TYPES = ('IMAGE','STRING','FLOAT',"INT")
|
||||
RETURN_NAMES = ("IMAGE","PROMPT","FLOAT","INT")
|
||||
FUNCTION = "run"
|
||||
|
||||
CATEGORY = "♾️Mixlab/image"
|
||||
@@ -96,10 +97,10 @@ class ScreenShareNode:
|
||||
OUTPUT_IS_LIST = (False,False,False,False)
|
||||
|
||||
# 运行的函数
|
||||
def run(self,image_base64,prompt,slide):
|
||||
def run(self,image_base64,prompt,slide,seed):
|
||||
im,mask=base64_save(image_base64)
|
||||
# print('##########prompt',prompt)
|
||||
return (im,prompt,slide)
|
||||
return (im,prompt,slide,seed)
|
||||
|
||||
|
||||
class FloatingVideo:
|
||||
|
||||
@@ -0,0 +1,83 @@
|
||||
import os
|
||||
|
||||
# FONT_PATH= os.path.abspath(os.path.join(os.path.dirname(__file__),'../assets/王汉宗颜楷体繁.ttf'))
|
||||
|
||||
import matplotlib.font_manager as fm
|
||||
|
||||
def get_font_files(directory):
|
||||
font_files = {}
|
||||
|
||||
# 从指定目录加载字体
|
||||
for file in os.listdir(directory):
|
||||
if file.endswith('.ttf') or file.endswith('.otf'):
|
||||
font_name = os.path.splitext(file)[0]
|
||||
font_path = os.path.join(directory, file)
|
||||
font_files[font_name] = os.path.abspath(font_path)
|
||||
|
||||
# 尝试获取系统字体
|
||||
try:
|
||||
font_paths = fm.findSystemFonts()
|
||||
for path in font_paths:
|
||||
try:
|
||||
font_prop = fm.FontProperties(fname=path)
|
||||
font_name = font_prop.get_name()
|
||||
font_files[font_name] = path
|
||||
except Exception as e:
|
||||
print(f"Error processing font {path}: {e}")
|
||||
except Exception as e:
|
||||
print(f"Error finding system fonts: {e}")
|
||||
|
||||
return font_files
|
||||
|
||||
r_directory = os.path.join(os.path.dirname(__file__), '../assets/')
|
||||
|
||||
font_files = get_font_files(r_directory)
|
||||
# print(font_files)
|
||||
|
||||
|
||||
class ColorInput:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": {
|
||||
|
||||
"color":("TCOLOR",),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("STRING",)
|
||||
# RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
|
||||
|
||||
FUNCTION = "run"
|
||||
|
||||
CATEGORY = "♾️Mixlab/utils"
|
||||
|
||||
INPUT_IS_LIST = False
|
||||
OUTPUT_IS_LIST = (False,False,)
|
||||
|
||||
def run(self,color):
|
||||
return (color,)
|
||||
|
||||
|
||||
|
||||
class FontInput:
|
||||
@classmethod
|
||||
def INPUT_TYPES(s):
|
||||
return {"required": {
|
||||
|
||||
"font": (list(font_files.keys()),),
|
||||
},
|
||||
}
|
||||
|
||||
RETURN_TYPES = ("STRING",)
|
||||
# RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
|
||||
|
||||
FUNCTION = "run"
|
||||
|
||||
CATEGORY = "♾️Mixlab/utils"
|
||||
|
||||
INPUT_IS_LIST = False
|
||||
OUTPUT_IS_LIST = (False,False,)
|
||||
|
||||
def run(self,font):
|
||||
|
||||
return (font_files[font],)
|
||||
@@ -0,0 +1,311 @@
|
||||
import { app } from '../../../scripts/app.js'
|
||||
// import { api } from '../../../scripts/api.js'
|
||||
import { ComfyWidgets } from '../../../scripts/widgets.js'
|
||||
import { $el } from '../../../scripts/ui.js'
|
||||
|
||||
function get_position_style (ctx, widget_width, y, node_height) {
|
||||
const MARGIN = 4 // the margin around the html element
|
||||
|
||||
/* Create a transform that deals with all the scrolling and zooming */
|
||||
const elRect = ctx.canvas.getBoundingClientRect()
|
||||
const transform = new DOMMatrix()
|
||||
.scaleSelf(
|
||||
elRect.width / ctx.canvas.width,
|
||||
elRect.height / ctx.canvas.height
|
||||
)
|
||||
.multiplySelf(ctx.getTransform())
|
||||
.translateSelf(MARGIN, MARGIN + y)
|
||||
|
||||
return {
|
||||
transformOrigin: '0 0',
|
||||
transform: transform,
|
||||
left: `0`,
|
||||
top: `0`,
|
||||
cursor: 'pointer',
|
||||
position: 'absolute',
|
||||
maxWidth: `${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'
|
||||
}
|
||||
}
|
||||
|
||||
const getLocalData = key => {
|
||||
let data = {}
|
||||
try {
|
||||
data = JSON.parse(localStorage.getItem(key)) || {}
|
||||
} catch (error) {
|
||||
return {}
|
||||
}
|
||||
return data
|
||||
}
|
||||
|
||||
function speakText (text) {
|
||||
const speechMsg = new SpeechSynthesisUtterance()
|
||||
speechMsg.text = text
|
||||
|
||||
// 语音合成结束时触发的事件
|
||||
speechMsg.onend = function (event) {
|
||||
console.log('语音播放结束')
|
||||
window._mixlab_speech_synthesis_onend = true
|
||||
}
|
||||
|
||||
// 语音合成错误时触发的事件
|
||||
speechMsg.onerror = function (event) {
|
||||
console.error('语音播放错误:', event.error)
|
||||
}
|
||||
|
||||
// 使用浏览器默认语音合成器进行语音播放
|
||||
speechSynthesis.speak(speechMsg)
|
||||
}
|
||||
|
||||
// 调用方法,将文字转换为语音播放
|
||||
// speakText('Hello, how are you?');
|
||||
// #MixCopilot
|
||||
|
||||
const start = (element, id, startBtn) => {
|
||||
|
||||
startBtn.className='loading_mixlab'
|
||||
|
||||
window.recognition = new webkitSpeechRecognition()
|
||||
|
||||
window.recognition.continuous = true
|
||||
window.recognition.interimResults = true
|
||||
window.recognition.lang = navigator.language
|
||||
|
||||
let timeoutId, intervalId
|
||||
|
||||
window.recognition.onstart = () => {
|
||||
console.log('开始语音输入', window._mixlab_speech_synthesis_onend)
|
||||
window._mixlab_speech_synthesis_onend = false
|
||||
}
|
||||
|
||||
window.recognition.onresult = function (event) {
|
||||
const result = event.results[event.results.length - 1][0].transcript
|
||||
console.log('识别结果:', result)
|
||||
element.value = result
|
||||
|
||||
let data = getLocalData('_mixlab_speech_recognition')
|
||||
data[id] = result.trim()
|
||||
localStorage.setItem('_mixlab_speech_recognition', JSON.stringify(data))
|
||||
|
||||
if (timeoutId) clearTimeout(timeoutId)
|
||||
|
||||
if (!window.recognition) return
|
||||
|
||||
timeoutId = setTimeout(function () {
|
||||
console.log('结果传递::', result)
|
||||
app.queuePrompt(0, 1)
|
||||
window.recognition?.stop()
|
||||
window.recognition = null;
|
||||
startBtn.className=''
|
||||
startBtn.innerText = 'START'
|
||||
|
||||
timeoutId = null
|
||||
|
||||
intervalId = setInterval(() => {
|
||||
if (
|
||||
app.ui.lastQueueSize === 0 &&
|
||||
!window.recognition &&
|
||||
window._mixlab_speech_synthesis_onend
|
||||
) {
|
||||
start(element, id, startBtn)
|
||||
startBtn.innerText = 'STOP'
|
||||
if (intervalId) {
|
||||
clearInterval(intervalId)
|
||||
}
|
||||
}
|
||||
}, 2200)
|
||||
}, 2000)
|
||||
}
|
||||
|
||||
window.recognition.onend = function () {
|
||||
console.log('语音输入结束')
|
||||
}
|
||||
|
||||
window.recognition.onspeechend = function () {
|
||||
console.log('onspeechend')
|
||||
}
|
||||
|
||||
window.recognition.onerror = function (event) {
|
||||
console.log('Error occurred in recognition: ' + event.error)
|
||||
}
|
||||
|
||||
window.recognition.start()
|
||||
}
|
||||
|
||||
app.registerExtension({
|
||||
name: 'Mixlab.audio.SpeechRecognition',
|
||||
async getCustomWidgets (app) {
|
||||
return {
|
||||
AUDIOINPUTMIX (node, inputName, inputData, app) {
|
||||
// console.log('##node', node)
|
||||
const widget = {
|
||||
type: inputData[0], // the type, CHEESE
|
||||
name: inputName, // the name, slice
|
||||
size: [128, 32], // a default size
|
||||
draw (ctx, node, width, y) {},
|
||||
computeSize (...args) {
|
||||
return [128, 32] // a method to compute the current size of the widget
|
||||
},
|
||||
async serializeValue (nodeId, widgetIndex) {
|
||||
let data = getLocalData('_mixlab_speech_recognition')
|
||||
return data[node.id] || 'Hello Mixlab'
|
||||
}
|
||||
}
|
||||
// widget.something = something; // maybe adds stuff to it
|
||||
node.addCustomWidget(widget) // adds it to the node
|
||||
return widget // and returns it.
|
||||
}
|
||||
}
|
||||
},
|
||||
|
||||
async beforeRegisterNodeDef (nodeType, nodeData, app) {
|
||||
if (nodeType.comfyClass == 'SpeechRecognition') {
|
||||
const orig_nodeCreated = nodeType.prototype.onNodeCreated
|
||||
nodeType.prototype.onNodeCreated = function () {
|
||||
orig_nodeCreated?.apply(this, arguments)
|
||||
|
||||
const widget = {
|
||||
type: 'div',
|
||||
name: 'chatgptdiv',
|
||||
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 = $el('div', {})
|
||||
|
||||
document.body.appendChild(widget.div)
|
||||
|
||||
const inputDiv = (key, placeholder) => {
|
||||
let div = document.createElement('div')
|
||||
const startBtn = document.createElement('button')
|
||||
const textArea = document.createElement('textarea')
|
||||
|
||||
textArea.className = `${'comfy-multiline-input'} ${placeholder}`
|
||||
|
||||
textArea.style = `margin-top: 14px;
|
||||
height: 44px;`
|
||||
|
||||
div.style = `flex-direction: column;
|
||||
display: flex;
|
||||
margin: 0px 8px 6px;`
|
||||
|
||||
startBtn.style = `
|
||||
outline: none;
|
||||
border: none;
|
||||
padding: 4px; `
|
||||
|
||||
startBtn.innerText = 'START'
|
||||
|
||||
div.appendChild(startBtn)
|
||||
div.appendChild(textArea)
|
||||
|
||||
startBtn.addEventListener('click', () => {
|
||||
if (window.recognition) {
|
||||
window.recognition.stop()
|
||||
window.recognition = null
|
||||
startBtn.innerText = 'START'
|
||||
startBtn.className=''
|
||||
} else {
|
||||
start(textArea, this.id, startBtn)
|
||||
startBtn.innerText = 'STOP'
|
||||
}
|
||||
})
|
||||
|
||||
return div
|
||||
}
|
||||
|
||||
let inputAudio = inputDiv('_mixlab_speech_recognition', 'audio')
|
||||
widget.div.appendChild(inputAudio)
|
||||
|
||||
this.addCustomWidget(widget)
|
||||
|
||||
const onRemoved = this.onRemoved
|
||||
this.onRemoved = () => {
|
||||
inputAudio.remove()
|
||||
widget.div.remove()
|
||||
return onRemoved?.()
|
||||
}
|
||||
|
||||
this.serialize_widgets = true //需要保存参数
|
||||
}
|
||||
}
|
||||
},
|
||||
async loadedGraphNode (node, app) {
|
||||
if (node.type === 'SpeechRecognition') {
|
||||
let data = getLocalData('_mixlab_speech_recognition')
|
||||
// console.log('_mixlab_speech_recognition', node.widgets)
|
||||
let div = node.widgets.filter(f => f.type === 'div')[0]
|
||||
if (div && data[node.id]) {
|
||||
div.div.querySelector('textarea').value = data[node.id]
|
||||
}
|
||||
}
|
||||
}
|
||||
})
|
||||
|
||||
app.registerExtension({
|
||||
name: 'Mixlab.audio.SpeechSynthesis',
|
||||
async beforeRegisterNodeDef (nodeType, nodeData, app) {
|
||||
if (nodeData.name === 'SpeechSynthesis') {
|
||||
function populate (text) {
|
||||
// console.log('SpeechSynthesis',this.widgets)
|
||||
|
||||
if (this.widgets) {
|
||||
const pos = this.widgets.findIndex(w => w.name === 'text')
|
||||
if (pos !== -1) {
|
||||
for (let i = pos; i < this.widgets.length; i++) {
|
||||
this.widgets[i].onRemove?.()
|
||||
}
|
||||
this.widgets.length = pos
|
||||
}
|
||||
}
|
||||
|
||||
for (let list of text) {
|
||||
const w = ComfyWidgets['STRING'](
|
||||
this,
|
||||
'text',
|
||||
['STRING', { multiline: true }],
|
||||
app
|
||||
).widget
|
||||
w.inputEl.readOnly = true
|
||||
w.inputEl.style.opacity = 0.6
|
||||
w.value = list
|
||||
}
|
||||
|
||||
speakText(text.join('\n'))
|
||||
|
||||
// console.log('ShowTextForGPT',this.widgets.length)
|
||||
requestAnimationFrame(() => {
|
||||
const sz = this.computeSize()
|
||||
if (sz[0] < this.size[0]) {
|
||||
sz[0] = this.size[0]
|
||||
}
|
||||
if (sz[1] < this.size[1]) {
|
||||
sz[1] = this.size[1]
|
||||
}
|
||||
this.onResize?.(sz)
|
||||
app.graph.setDirtyCanvas(true, false)
|
||||
})
|
||||
}
|
||||
|
||||
// When the node is executed we will be sent the input text, display this in the widget
|
||||
const onExecuted = nodeType.prototype.onExecuted
|
||||
nodeType.prototype.onExecuted = function (message) {
|
||||
onExecuted?.apply(this, arguments)
|
||||
populate.call(this, message.text)
|
||||
}
|
||||
|
||||
this.serialize_widgets = true //需要保存参数
|
||||
}
|
||||
}
|
||||
})
|
||||
@@ -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 = 'v0.2.6'
|
||||
const version = 'v0.3.1'
|
||||
|
||||
fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
|
||||
.then(response => response.json())
|
||||
|
||||
@@ -65,10 +65,10 @@ app.registerExtension({
|
||||
const widget = {
|
||||
type: inputData[0], // the type, CHEESE
|
||||
name: inputName, // the name, slice
|
||||
size: [128, 24], // a default size
|
||||
size: [128, 32], // a default size
|
||||
draw (ctx, node, width, y) {},
|
||||
computeSize (...args) {
|
||||
return [128, 24] // a method to compute the current size of the widget
|
||||
return [128,32] // a method to compute the current size of the widget
|
||||
},
|
||||
async serializeValue (nodeId, widgetIndex) {
|
||||
let data = getLocalData('_mixlab_api_key')
|
||||
@@ -84,12 +84,12 @@ app.registerExtension({
|
||||
const widget = {
|
||||
type: inputData[0], // the type, CHEESE
|
||||
name: inputName, // the name, slice
|
||||
size: [128, 24], // a default size
|
||||
size: [128, 32], // a default size
|
||||
draw (ctx, node, width, y) {
|
||||
// a method to draw the widget (ctx is a CanvasRenderingContext2D)
|
||||
},
|
||||
computeSize (...args) {
|
||||
return [128, 24] // a method to compute the current size of the widget
|
||||
return [128, 32] // a method to compute the current size of the widget
|
||||
},
|
||||
async serializeValue (nodeId, widgetIndex) {
|
||||
let data = getLocalData('_mixlab_api_url')
|
||||
@@ -192,7 +192,7 @@ app.registerExtension({
|
||||
|
||||
let id = node.id
|
||||
|
||||
console.log('ChatGPTOpenAI serialize_widgets', this)
|
||||
// console.log('ChatGPTOpenAI serialize_widgets', this)
|
||||
|
||||
widget.div.querySelector('.Key').value = apiKey[id] || 'by Mixlab'
|
||||
widget.div.querySelector('.URL').value =
|
||||
@@ -216,12 +216,27 @@ app.registerExtension({
|
||||
this.widgets.length = pos;
|
||||
}
|
||||
}
|
||||
// console.log('ShowTextForGPT',this.widgets.length)
|
||||
for (const list of text) {
|
||||
// console.log('ShowTextForGPT',text)
|
||||
for (let list of text) {
|
||||
const w = ComfyWidgets["STRING"](this, "text", ["STRING", { multiline: true }], app).widget;
|
||||
w.inputEl.readOnly = true;
|
||||
w.inputEl.style.opacity = 0.6;
|
||||
w.value = list;
|
||||
|
||||
try {
|
||||
let data=JSON.parse(list);
|
||||
data=Array.from(data,d=>{
|
||||
return {
|
||||
...d,
|
||||
content:decodeURIComponent(d.content)
|
||||
}
|
||||
})
|
||||
list=JSON.stringify(data,null,2)
|
||||
} catch (error) {
|
||||
// console.log(error)
|
||||
}
|
||||
|
||||
w.value =list;
|
||||
|
||||
}
|
||||
// console.log('ShowTextForGPT',this.widgets.length)
|
||||
requestAnimationFrame(() => {
|
||||
|
||||
@@ -0,0 +1,659 @@
|
||||
import { app } from '../../../scripts/app.js'
|
||||
import { api } from '../../../scripts/api.js'
|
||||
import { ComfyWidgets } from '../../../scripts/widgets.js'
|
||||
import { $el } from '../../../scripts/ui.js'
|
||||
|
||||
async function uploadImage (blob, fileType = '.svg') {
|
||||
// const blob = await (await fetch(src)).blob();
|
||||
const body = new FormData()
|
||||
body.append('image', new File([blob], new Date().getTime() + fileType))
|
||||
|
||||
const resp = await api.fetchApi('/upload/image', {
|
||||
method: 'POST',
|
||||
body
|
||||
})
|
||||
|
||||
// console.log(resp)
|
||||
let data = await resp.json()
|
||||
let { name, subfolder } = data
|
||||
let src = api.apiURL(
|
||||
`/view?filename=${encodeURIComponent(
|
||||
name
|
||||
)}&type=input&subfolder=${subfolder}${app.getPreviewFormatParam()}${app.getRandParam()}`
|
||||
)
|
||||
|
||||
return src
|
||||
}
|
||||
|
||||
function base64ToBlobFromURL (base64URL, contentType) {
|
||||
return fetch(base64URL).then(response => response.blob())
|
||||
}
|
||||
|
||||
function getContentTypeFromBase64 (base64Data) {
|
||||
const regex = /^data:(.+);base64,/
|
||||
const matches = base64Data.match(regex)
|
||||
if (matches && matches.length >= 2) {
|
||||
return matches[1]
|
||||
}
|
||||
return null
|
||||
}
|
||||
|
||||
// 示例用法
|
||||
// const base64Data = 'data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAAAAAAAD/...'; // 替换为实际的base64图片数据
|
||||
// const contentType = getContentTypeFromBase64(base64Data);
|
||||
// console.log(contentType);
|
||||
|
||||
// // 示例用法
|
||||
// const base64Data = '...'; // 替换为实际的base64图片数据
|
||||
// const contentType = 'image/jpeg'; // 替换为实际的图片类型
|
||||
|
||||
// const blob = base64ToBlob(base64Data, contentType);
|
||||
// console.log(blob);
|
||||
|
||||
function get_position_style (ctx, widget_width, y, node_height) {
|
||||
const MARGIN = 4 // the margin around the html element
|
||||
|
||||
/* Create a transform that deals with all the scrolling and zooming */
|
||||
const elRect = ctx.canvas.getBoundingClientRect()
|
||||
const transform = new DOMMatrix()
|
||||
.scaleSelf(
|
||||
elRect.width / ctx.canvas.width,
|
||||
elRect.height / ctx.canvas.height
|
||||
)
|
||||
.multiplySelf(ctx.getTransform())
|
||||
.translateSelf(MARGIN, MARGIN + y)
|
||||
|
||||
return {
|
||||
transformOrigin: '0 0',
|
||||
transform: transform,
|
||||
left: `0`,
|
||||
top: `0`,
|
||||
cursor: 'pointer',
|
||||
position: 'absolute',
|
||||
maxWidth: `${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'
|
||||
}
|
||||
}
|
||||
|
||||
const getLocalData = key => {
|
||||
let data = {}
|
||||
try {
|
||||
data = JSON.parse(localStorage.getItem(key)) || {}
|
||||
} catch (error) {
|
||||
return {}
|
||||
}
|
||||
return data
|
||||
}
|
||||
|
||||
const setLocalDataOfWin = (key, value) => {
|
||||
localStorage.setItem(key, JSON.stringify(value))
|
||||
// window[key] = value
|
||||
}
|
||||
|
||||
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)
|
||||
})
|
||||
})
|
||||
}
|
||||
|
||||
const parseSvg = async svgContent => {
|
||||
let scale = 2
|
||||
// 创建一个临时的DOM元素来解析SVG
|
||||
const tempContainer = document.createElement('div')
|
||||
tempContainer.innerHTML = svgContent
|
||||
|
||||
// 提取SVG元素
|
||||
const svgElement = tempContainer.querySelector('svg')
|
||||
if (!svgElement) return
|
||||
// 获取SVG中 rect元素
|
||||
var rectElements = svgElement?.querySelectorAll('rect') || []
|
||||
// console.log(rectElements,svgElement)
|
||||
// 定义一个数组来存储处理后的数据
|
||||
var data = []
|
||||
|
||||
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 width = ~~rectElement.getAttribute('width')
|
||||
var height = ~~rectElement.getAttribute('height')
|
||||
// console.log('rectElements',rectElement,x,y,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
|
||||
canvas.height = height
|
||||
var context = canvas.getContext('2d')
|
||||
|
||||
// 填充颜色到canvas
|
||||
var fill = rectElement.getAttribute('fill')
|
||||
context.fillStyle = fill
|
||||
context.fillRect(0, 0, width, height)
|
||||
|
||||
// 将canvas转换为base64格式
|
||||
var base64 = canvas.toDataURL()
|
||||
|
||||
// 将数据转化为指定的JSON格式
|
||||
|
||||
var rectData = {
|
||||
x: parseInt(x),
|
||||
y: parseInt(y),
|
||||
width: parseInt(width),
|
||||
height: parseInt(height),
|
||||
z_index: i + 1,
|
||||
scale_option: 'width',
|
||||
image: base64,
|
||||
mask: base64,
|
||||
type: 'base64',
|
||||
_t: 'rect'
|
||||
}
|
||||
|
||||
// 将处理后的数据添加到数组中
|
||||
data.push(rectData)
|
||||
}
|
||||
})
|
||||
|
||||
var svgWidth = svgElement.getAttribute('width')
|
||||
var svgHeight = svgElement.getAttribute('height')
|
||||
|
||||
if (!(svgWidth && svgHeight)) {
|
||||
// viewBox
|
||||
let viewBox = svgElement.viewBox.baseVal
|
||||
|
||||
svgWidth = viewBox.width
|
||||
svgHeight = viewBox.height
|
||||
}
|
||||
|
||||
// 创建一个新的canvas元素
|
||||
var canvas = document.createElement('canvas')
|
||||
canvas.width = svgWidth
|
||||
canvas.height = svgHeight
|
||||
var context = canvas.getContext('2d')
|
||||
// 绘制SVG到canvas
|
||||
var svgString = new XMLSerializer().serializeToString(svgElement)
|
||||
var DOMURL = window.URL || window.webkitURL || window
|
||||
|
||||
var svgBlob = new Blob([svgString], { type: 'image/svg+xml;charset=utf-8' })
|
||||
var url = DOMURL.createObjectURL(svgBlob)
|
||||
|
||||
let img = await createImage(url)
|
||||
context.drawImage(img, 0, 0)
|
||||
|
||||
let base64 = canvas.toDataURL()
|
||||
|
||||
var rectData = {
|
||||
x: 0,
|
||||
y: 0,
|
||||
width: parseInt(svgWidth),
|
||||
height: parseInt(svgHeight),
|
||||
z_index: 0,
|
||||
scale_option: 'width',
|
||||
image: base64,
|
||||
mask: base64,
|
||||
type: 'base64',
|
||||
_t: 'canvas'
|
||||
}
|
||||
data.push(rectData)
|
||||
|
||||
// 打印处理后的数据
|
||||
console.log('layers', { data, image: base64, svgElement })
|
||||
return { data, image: base64, svgElement }
|
||||
}
|
||||
|
||||
app.registerExtension({
|
||||
name: 'Mixlab.image.SvgImage',
|
||||
async getCustomWidgets (app) {
|
||||
return {
|
||||
SVG (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_svg_image')
|
||||
// console.log('serializeValue',d)
|
||||
if (d) {
|
||||
let url = d[node.id]
|
||||
let dt = await fetch(url)
|
||||
let svgStr = await dt.text()
|
||||
const { data, image } = (await parseSvg(svgStr)) || {}
|
||||
// console.log(data, image)
|
||||
return JSON.parse(JSON.stringify({ data, image }))
|
||||
} else {
|
||||
return
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// console.log('##node',node.serialize)
|
||||
// widget.something = something; // maybe adds stuff to it
|
||||
node.addCustomWidget(widget) // adds it to the node
|
||||
|
||||
return widget // and returns it.
|
||||
}
|
||||
}
|
||||
},
|
||||
|
||||
async beforeRegisterNodeDef (nodeType, nodeData, app) {
|
||||
if (nodeType.comfyClass == 'SvgImage') {
|
||||
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('SvgImage nodeData',await uploadWidget.serializeValue())
|
||||
|
||||
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 = $el('div', {})
|
||||
|
||||
document.body.appendChild(widget.div)
|
||||
|
||||
const inputDiv = (key, placeholder, svgContainer) => {
|
||||
let div = document.createElement('div')
|
||||
const ip = document.createElement('input')
|
||||
ip.type = 'file'
|
||||
ip.className = `${'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 svgContent = e.target.result
|
||||
|
||||
var blob = new Blob([svgContent], { type: 'image/svg+xml' })
|
||||
let url = await uploadImage(blob)
|
||||
// console.log(url)
|
||||
const { svgElement, data, image } = await parseSvg(svgContent)
|
||||
// 将提取的SVG元素显示在页面上
|
||||
let dd = getLocalData(key)
|
||||
dd[that.id] = url
|
||||
setLocalDataOfWin(key, dd)
|
||||
// console.log(this.id, ip.value.trim())
|
||||
|
||||
svgElement.style = `width: 90%;padding: 5%;`
|
||||
// 将提取的SVG元素显示在页面上
|
||||
|
||||
svgContainer.innerHTML = ''
|
||||
svgContainer.appendChild(svgElement)
|
||||
let h = ~~getComputedStyle(svgElement).height.replace('px', '')
|
||||
if (that.size && that.size[1] < h) {
|
||||
that.setSize([that.size[0], that.size[1] + h])
|
||||
app.canvas.draw(true, true)
|
||||
}
|
||||
// console.log(that.size,~~getComputedStyle(svgElement).height.replace('px',''))
|
||||
|
||||
uploadWidget.value = await uploadWidget.serializeValue()
|
||||
}
|
||||
|
||||
// 以文本形式读取文件
|
||||
reader.readAsText(file)
|
||||
})
|
||||
return div
|
||||
}
|
||||
|
||||
let svg = document.createElement('div')
|
||||
svg.className = 'preview'
|
||||
svg.style = `background:#eee;margin-top: 12px;`
|
||||
|
||||
let upload = inputDiv('_mixlab_svg_image', 'Svg', svg)
|
||||
|
||||
widget.div.appendChild(upload)
|
||||
widget.div.appendChild(svg)
|
||||
this.addCustomWidget(widget)
|
||||
|
||||
const onRemoved = this.onRemoved
|
||||
this.onRemoved = () => {
|
||||
upload.remove()
|
||||
svg.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 === 'SvgImage') {
|
||||
// await sleep(0)
|
||||
let widget = node.widgets.filter(w => w.name === 'upload-preview')[0]
|
||||
|
||||
let dd = getLocalData('_mixlab_svg_image')
|
||||
|
||||
let id = node.id
|
||||
console.log('SvgImage load', node.widgets[0], node.widgets)
|
||||
if (!dd[id]) return
|
||||
let dt = await fetch(dd[id])
|
||||
let svgStr = await dt.text()
|
||||
|
||||
const { svgElement, data, image } = await parseSvg(svgStr)
|
||||
svgElement.style = `width: 90%;padding: 5%;`
|
||||
// 将提取的SVG元素显示在页面上
|
||||
|
||||
widget.div.querySelector('.preview').innerHTML = ''
|
||||
widget.div.querySelector('.preview').appendChild(svgElement)
|
||||
|
||||
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)
|
||||
}
|
||||
}
|
||||
})
|
||||
@@ -0,0 +1,352 @@
|
||||
import { app } from '../../../scripts/app.js'
|
||||
// import { api } from '../../../scripts/api.js'
|
||||
import { ComfyWidgets } from '../../../scripts/widgets.js'
|
||||
import { $el } from '../../../scripts/ui.js'
|
||||
|
||||
function get_position_style (ctx, widget_width, y, node_height) {
|
||||
const MARGIN = 4 // the margin around the html element
|
||||
|
||||
/* Create a transform that deals with all the scrolling and zooming */
|
||||
const elRect = ctx.canvas.getBoundingClientRect()
|
||||
const transform = new DOMMatrix()
|
||||
.scaleSelf(
|
||||
elRect.width / ctx.canvas.width,
|
||||
elRect.height / ctx.canvas.height
|
||||
)
|
||||
.multiplySelf(ctx.getTransform())
|
||||
.translateSelf(MARGIN, MARGIN + y)
|
||||
|
||||
return {
|
||||
transformOrigin: '0 0',
|
||||
transform: transform,
|
||||
left: `0`,
|
||||
top: `0`,
|
||||
cursor: 'pointer',
|
||||
position: 'absolute',
|
||||
maxWidth: `${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'
|
||||
}
|
||||
}
|
||||
|
||||
const getLocalData = key => {
|
||||
let data = {}
|
||||
try {
|
||||
data = JSON.parse(localStorage.getItem(key)) || {}
|
||||
} catch (error) {
|
||||
return {}
|
||||
}
|
||||
return data
|
||||
}
|
||||
|
||||
function createImage (url) {
|
||||
let im = new Image()
|
||||
return new Promise((res, rej) => {
|
||||
im.onload = () => res(im)
|
||||
im.src = url
|
||||
})
|
||||
}
|
||||
|
||||
const parseSvg = async svgContent => {
|
||||
// 创建一个临时的DOM元素来解析SVG
|
||||
const tempContainer = document.createElement('div')
|
||||
tempContainer.innerHTML = svgContent
|
||||
|
||||
// 提取SVG元素
|
||||
const svgElement = tempContainer.querySelector('svg')
|
||||
if (!svgElement) return
|
||||
// 获取SVG中 rect元素
|
||||
var rectElements = svgElement?.querySelectorAll('rect') || []
|
||||
// console.log(rectElements,svgElement)
|
||||
// 定义一个数组来存储处理后的数据
|
||||
var data = []
|
||||
|
||||
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 width = ~~rectElement.getAttribute('width')
|
||||
var height = ~~rectElement.getAttribute('height')
|
||||
// console.log('rectElements',rectElement,x,y,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
|
||||
canvas.height = height
|
||||
var context = canvas.getContext('2d')
|
||||
|
||||
// 填充颜色到canvas
|
||||
var fill = rectElement.getAttribute('fill')
|
||||
context.fillStyle = fill
|
||||
context.fillRect(0, 0, width, height)
|
||||
|
||||
// 将canvas转换为base64格式
|
||||
var base64 = canvas.toDataURL()
|
||||
|
||||
// 将数据转化为指定的JSON格式
|
||||
|
||||
var rectData = {
|
||||
x: parseInt(x),
|
||||
y: parseInt(y),
|
||||
width: parseInt(width),
|
||||
height: parseInt(height),
|
||||
z_index: i + 1,
|
||||
scale_option: 'width',
|
||||
image: base64,
|
||||
mask: base64,
|
||||
type: 'base64',
|
||||
_t:'rect'
|
||||
}
|
||||
|
||||
// 将处理后的数据添加到数组中
|
||||
data.push(rectData)
|
||||
}
|
||||
})
|
||||
|
||||
var svgWidth = svgElement.getAttribute('width')
|
||||
var svgHeight = svgElement.getAttribute('height')
|
||||
|
||||
if (!(svgWidth && svgHeight)) {
|
||||
// viewBox
|
||||
let viewBox = svgElement.viewBox.baseVal
|
||||
|
||||
svgWidth =viewBox.width
|
||||
svgHeight =viewBox.height
|
||||
}
|
||||
|
||||
// 创建一个新的canvas元素
|
||||
var canvas = document.createElement('canvas')
|
||||
canvas.width = svgWidth
|
||||
canvas.height = svgHeight
|
||||
var context = canvas.getContext('2d')
|
||||
// 绘制SVG到canvas
|
||||
var svgString = new XMLSerializer().serializeToString(svgElement)
|
||||
var DOMURL = window.URL || window.webkitURL || window
|
||||
|
||||
var svgBlob = new Blob([svgString], { type: 'image/svg+xml;charset=utf-8' })
|
||||
var url = DOMURL.createObjectURL(svgBlob)
|
||||
|
||||
let img = await createImage(url)
|
||||
context.drawImage(img, 0, 0)
|
||||
|
||||
let base64 = canvas.toDataURL()
|
||||
|
||||
var rectData = {
|
||||
x: 0,
|
||||
y: 0,
|
||||
width: parseInt(svgWidth),
|
||||
height: parseInt(svgHeight),
|
||||
z_index: 0,
|
||||
scale_option: 'width',
|
||||
image: base64,
|
||||
mask: base64,
|
||||
type: 'base64',
|
||||
_t:'canvas'
|
||||
}
|
||||
data.push(rectData)
|
||||
|
||||
// 打印处理后的数据
|
||||
console.log('layers',{ data, image: base64, svgElement })
|
||||
return { data, image: base64, svgElement }
|
||||
}
|
||||
|
||||
app.registerExtension({
|
||||
name: 'Mixlab.layer.ShowLayer',
|
||||
async getCustomWidgets (app) {
|
||||
return {
|
||||
EDIT (node, inputName, inputData, app) {
|
||||
// console.log('EditLayer##node', node,inputName, inputData)
|
||||
const widget = {
|
||||
type: inputData[0], // the type, CHEESE
|
||||
name: inputName, // the name, slice
|
||||
size: [128, 44], // a default size
|
||||
draw (ctx, node, widget_width, y, widget_height) {
|
||||
// console.log('EditLayer', this)
|
||||
if (this.input)
|
||||
Object.assign(
|
||||
this.input.style,
|
||||
get_position_style(ctx, widget_width, 32, node.size[1])
|
||||
)
|
||||
},
|
||||
computeSize (...args) {
|
||||
return [128, 44] // a method to compute the current size of the widget
|
||||
},
|
||||
async serializeValue (nodeId, widgetIndex) {
|
||||
let d = getLocalData('_mixlab_edit_layer')
|
||||
// console.log('EditLayer',d[node.id])
|
||||
return d[node.id]
|
||||
}
|
||||
}
|
||||
// widget.something = something; // maybe adds stuff to it
|
||||
node.addCustomWidget(widget) // adds it to the node
|
||||
return widget // and returns it.
|
||||
}
|
||||
}
|
||||
},
|
||||
|
||||
async beforeRegisterNodeDef (nodeType, nodeData, app) {
|
||||
if (nodeType.comfyClass == 'ShowLayer') {
|
||||
const orig_nodeCreated = nodeType.prototype.onNodeCreated
|
||||
nodeType.prototype.onNodeCreated = async function () {
|
||||
orig_nodeCreated?.apply(this, arguments)
|
||||
|
||||
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
|
||||
nodeId = app.graph.links.filter(link => link.id == linkId)[0]
|
||||
?.origin_id
|
||||
return findNode(nodeId)
|
||||
} else {
|
||||
return nodeId
|
||||
}
|
||||
}
|
||||
|
||||
// 获取layers数据
|
||||
const getLayers = async () => {
|
||||
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;
|
||||
|
||||
if(nodeId){
|
||||
nodeId = findNode(nodeId)
|
||||
}
|
||||
|
||||
|
||||
// let node = app.graph._nodes_by_id[nodeId]
|
||||
// if (node?.type == 'Reroute') {
|
||||
// linkId = node.inputs[0].link
|
||||
// nodeId = app.graph.links.filter(link => link.id == linkId)[0]
|
||||
// ?.origin_id
|
||||
// }
|
||||
|
||||
let d = getLocalData('_mixlab_svg_image')
|
||||
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)
|
||||
return data
|
||||
} else {
|
||||
return []
|
||||
}
|
||||
}
|
||||
|
||||
// 修改layers数据
|
||||
const setLayer = async (editIndex, layers = null) => {
|
||||
// let editIndex = 0
|
||||
let lys = layers || (await getLayers())
|
||||
let layer = lys[editIndex]
|
||||
// console.log(layer)
|
||||
|
||||
const updateValue = name => {
|
||||
const x = this.widgets.filter(w => w.name == name)[0]
|
||||
x.value = layer[name]
|
||||
}
|
||||
if (layer) {
|
||||
Array.from(['x', 'y', 'width', 'height', 'z_index'], n =>
|
||||
updateValue(n)
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
let that = this
|
||||
const save_edit_layer_index = i => {
|
||||
let data = getLocalData('_mixlab_edit_layer')
|
||||
data[that.id] = i
|
||||
localStorage.setItem('_mixlab_edit_layer', JSON.stringify(data))
|
||||
}
|
||||
|
||||
await setLayer(0)
|
||||
save_edit_layer_index(0)
|
||||
|
||||
const edit = this.widgets.filter(w => w.name == 'edit')[0]
|
||||
|
||||
edit.input = $el('div', {})
|
||||
edit.input.style = `
|
||||
display: flex;
|
||||
flex-direction:row;
|
||||
align-items: center;
|
||||
margin-top: 0;`
|
||||
|
||||
const ip = $el('input', {})
|
||||
ip.className = 'comfy-multiline-input'
|
||||
ip.type = 'number'
|
||||
ip.min = 0
|
||||
ip.step = 1
|
||||
ip.max = Math.max(0, (await getLayers()).length - 1)
|
||||
// ip.className = `${'comfy-multiline-input'} `
|
||||
|
||||
ip.value = 0
|
||||
|
||||
ip.style = `
|
||||
background-color: var(--comfy-input-bg);
|
||||
color: var(--input-text);
|
||||
outline: none;
|
||||
border: none;
|
||||
padding: 4px;
|
||||
width: 60%;
|
||||
cursor: pointer;
|
||||
height: 24px;`
|
||||
const label = document.createElement('label')
|
||||
label.style = 'font-size: 10px;min-width:32px'
|
||||
label.innerText = 'Layer Index'
|
||||
edit.input.appendChild(label)
|
||||
edit.input.appendChild(ip)
|
||||
|
||||
document.body.appendChild(edit.input)
|
||||
|
||||
ip.addEventListener('click', async event => {
|
||||
console.log(await getLayers())
|
||||
ip.max = Math.max(0, (await getLayers()).length - 1)
|
||||
})
|
||||
|
||||
ip.addEventListener('change', async event => {
|
||||
let index = ~~ip.value
|
||||
let lys = await getLayers()
|
||||
await setLayer(index, lys)
|
||||
app.graph.setDirtyCanvas(true, true)
|
||||
save_edit_layer_index(index)
|
||||
})
|
||||
|
||||
// console.log('EditLayer nodeData', edit)
|
||||
|
||||
const onRemoved = this.onRemoved
|
||||
this.onRemoved = () => {
|
||||
edit.input.remove()
|
||||
return onRemoved?.()
|
||||
}
|
||||
|
||||
if (this.onResize) {
|
||||
this.onResize(this.size)
|
||||
}
|
||||
|
||||
this.serialize_widgets = false //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
|
||||
if (node.type === 'SvgImage') {
|
||||
let widget = node.widgets.filter(w => w.div)[0]
|
||||
let data = getLocalData('_mixlab_svg_image')
|
||||
let id = node.id
|
||||
|
||||
// widget.div.querySelector('.Svg').value = data[id] || '#000000'
|
||||
}
|
||||
}
|
||||
})
|
||||
@@ -560,6 +560,26 @@ app.registerExtension({
|
||||
// console.log('###widget', widget)
|
||||
node.addCustomWidget(widget) // adds it to the node
|
||||
return widget // and returns it.
|
||||
},
|
||||
SEED (node, inputName, inputData, app) {
|
||||
// We return an object containing a field CHEESE which has a function (taking node, name, data, app)
|
||||
const widget = {
|
||||
type: inputData[0], // the type, CHEESE
|
||||
name: inputName, // the name, slice
|
||||
size: [128, 12], // a default size
|
||||
draw (ctx, node, width, y) {
|
||||
// a method to draw the widget (ctx is a CanvasRenderingContext2D)
|
||||
},
|
||||
computeSize (...args) {
|
||||
return [128, 12] // a method to compute the current size of the widget
|
||||
},
|
||||
async serializeValue (nodeId, widgetIndex) {
|
||||
return window._mixlab_screen_seed_input || 0
|
||||
}
|
||||
}
|
||||
// console.log('###widget', widget)
|
||||
node.addCustomWidget(widget) // adds it to the node
|
||||
return widget // and returns it.
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -576,9 +596,15 @@ app.registerExtension({
|
||||
type: 'HTML', // whatever
|
||||
name: 'sreen_share', // whatever
|
||||
draw (ctx, node, widget_width, y, widget_height) {
|
||||
console.log('ScreenSHare', y, widget_height)
|
||||
Object.assign(
|
||||
this.card.style,
|
||||
get_position_style(ctx, widget_width, y, node.size[1])
|
||||
get_position_style(
|
||||
ctx,
|
||||
widget_width,
|
||||
widget_height * 5,
|
||||
node.size[1]
|
||||
)
|
||||
)
|
||||
}
|
||||
}
|
||||
@@ -864,6 +890,9 @@ app.registerExtension({
|
||||
})
|
||||
// console.log('widget.inputEl',widget.inputEl)
|
||||
|
||||
this.setSize([this.size[0],this.size[1]+450])
|
||||
app.canvas.draw(true, true)
|
||||
|
||||
/*
|
||||
Add the widget, make sure we clean up nicely, and we do not want to be serialized!
|
||||
*/
|
||||
@@ -1305,13 +1334,38 @@ app.registerExtension({
|
||||
|
||||
// inputDiv.style = ``
|
||||
let infoDiv = document.createElement('div')
|
||||
infoDiv.style = ` width: 100%;
|
||||
infoDiv.style = `width: 100%;
|
||||
display: flex;
|
||||
justify-content: space-between;
|
||||
height: 16px;
|
||||
color: white;
|
||||
margin-bottom: 4px;
|
||||
font-size: 12px;
|
||||
text-shadow: 1px 1px gray;`
|
||||
infoDiv.id = 'info'
|
||||
text-shadow: gray 1px 1px;
|
||||
align-items: center;`
|
||||
|
||||
let infoText = document.createElement('div')
|
||||
infoText.id = 'info'
|
||||
|
||||
let hideBtn = document.createElement('button')
|
||||
hideBtn.innerText = '🤖'
|
||||
hideBtn.style = `
|
||||
border: none;
|
||||
background: none;
|
||||
cursor: pointer; height: 24px; margin: 4px; color: red;`
|
||||
|
||||
hideBtn.addEventListener('click', () => {
|
||||
if (fnDiv.style.display == 'none') {
|
||||
fnDiv.style.display = 'flex'
|
||||
} else {
|
||||
fnDiv.style.display = 'none'
|
||||
}
|
||||
try {
|
||||
pipWindow.document.querySelector('#info').innerText = ''
|
||||
} catch (error) {
|
||||
console.log(error)
|
||||
}
|
||||
})
|
||||
|
||||
// Move the player to the Picture-in-Picture window.
|
||||
let input = document.createElement('textarea')
|
||||
@@ -1356,21 +1410,25 @@ app.registerExtension({
|
||||
font-size: 16px;
|
||||
margin-right: 6px;user-select: none;`
|
||||
|
||||
let btn = document.createElement('butotn')
|
||||
btn.innerText = '❤'
|
||||
btn.style = `cursor: pointer;height: 24px;margin:4px;
|
||||
let seedBtn = document.createElement('butotn')
|
||||
seedBtn.innerText = '🎲'
|
||||
seedBtn.style = `cursor: pointer;height: 24px;margin:4px;
|
||||
color: red;`
|
||||
btn.addEventListener('click', () => {
|
||||
if (inputDiv.style.display == 'none') {
|
||||
inputDiv.style.display = 'block'
|
||||
} else {
|
||||
inputDiv.style.display = 'none'
|
||||
}
|
||||
|
||||
seedBtn.addEventListener('click', () => {
|
||||
window._mixlab_screen_seed_input = Math.round(
|
||||
Math.floor(Math.random() * 0xffffffffffffffff)
|
||||
)
|
||||
|
||||
try {
|
||||
pipWindow.document.querySelector('#info').innerText = ''
|
||||
pipWindow.document.querySelector('#info').innerText =window._mixlab_screen_seed_input
|
||||
} catch (error) {
|
||||
console.log(error)
|
||||
}
|
||||
|
||||
// console.log(window._mixlab_screen_seed_input)
|
||||
if (window._mixlab_screen_imagePath)
|
||||
document.querySelector('#queue-button').click()
|
||||
})
|
||||
|
||||
// TODO 需要判断是否有screenshare节点,没有的话,不需要添加
|
||||
@@ -1428,7 +1486,9 @@ app.registerExtension({
|
||||
console.log('##更新Prompt')
|
||||
window._mixlab_screen_prompt =
|
||||
window._mixlab_screen_prompt_input || window._mixlab_screen_prompt
|
||||
document.querySelector('#queue-button').click()
|
||||
|
||||
if (window._mixlab_screen_imagePath)
|
||||
document.querySelector('#queue-button').click()
|
||||
|
||||
try {
|
||||
pipWindow.document.querySelector('#info').innerText =
|
||||
@@ -1490,7 +1550,8 @@ app.registerExtension({
|
||||
window._mixlab_screen_slide_input = ~~slideInp.value / 100
|
||||
try {
|
||||
pipWindow.document.querySelector('#info').innerText =
|
||||
window._mixlab_screen_slide_input;
|
||||
window._mixlab_screen_slide_input
|
||||
if (window._mixlab_screen_imagePath)
|
||||
document.querySelector('#queue-button').click()
|
||||
} catch (error) {
|
||||
console.log(error)
|
||||
@@ -1505,9 +1566,12 @@ app.registerExtension({
|
||||
div.appendChild(infoDiv)
|
||||
div.appendChild(fnDiv)
|
||||
|
||||
fnDiv.appendChild(btnDiv)
|
||||
infoDiv.appendChild(infoText)
|
||||
infoDiv.appendChild(hideBtn)
|
||||
|
||||
btnDiv.appendChild(btn)
|
||||
fnDiv.appendChild(btnDiv)
|
||||
// 按钮区域
|
||||
btnDiv.appendChild(seedBtn)
|
||||
btnDiv.appendChild(pauseBtn)
|
||||
btnDiv.appendChild(promptFinishBtn)
|
||||
|
||||
@@ -1538,7 +1602,9 @@ app.registerExtension({
|
||||
window._mixlab_screen_prompt =
|
||||
window._mixlab_screen_prompt_input ||
|
||||
window._mixlab_screen_prompt
|
||||
document.querySelector('#queue-button').click()
|
||||
|
||||
if (window._mixlab_screen_imagePath)
|
||||
document.querySelector('#queue-button').click()
|
||||
|
||||
try {
|
||||
pipWindow.document.querySelector('#info').innerText =
|
||||
|
||||
@@ -0,0 +1 @@
|
||||
export const closeIcon = '<svg xmlns="http://www.w3.org/2000/svg" height="24" viewBox="0 -960 960 960" width="24"><path d="m256-200-56-56 224-224-224-224 56-56 224 224 224-224 56 56-224 224 224 224-56 56-224-224-224 224Z"/></svg>'
|
||||
+671
-22
@@ -1,4 +1,99 @@
|
||||
import { app } from '../../../scripts/app.js'
|
||||
import { api } from '../../../scripts/api.js'
|
||||
import { ComfyWidgets } from '../../../scripts/widgets.js'
|
||||
import { $el } from '../../../scripts/ui.js'
|
||||
import {closeIcon} from './svg_icons.js'
|
||||
|
||||
function deepEqual (obj1, obj2) {
|
||||
if (typeof obj1 !== typeof obj2) {
|
||||
return false
|
||||
}
|
||||
|
||||
if (typeof obj1 !== 'object' || obj1 === null || obj2 === null) {
|
||||
return obj1 === obj2
|
||||
}
|
||||
|
||||
const keys1 = Object.keys(obj1)
|
||||
const keys2 = Object.keys(obj2)
|
||||
|
||||
if (keys1.length !== keys2.length) {
|
||||
return false
|
||||
}
|
||||
|
||||
for (let key of keys1) {
|
||||
if (!deepEqual(obj1[key], obj2[key])) {
|
||||
return false
|
||||
}
|
||||
}
|
||||
|
||||
return true
|
||||
}
|
||||
|
||||
async function get_nodes_map () {
|
||||
let api_host = `${window.location.hostname}:${window.location.port}`
|
||||
let api_base = ''
|
||||
let url = `${window.location.protocol}//${api_host}${api_base}`
|
||||
|
||||
const res = await fetch(`${url}/mixlab/nodes_map`, {
|
||||
method: 'POST',
|
||||
body: JSON.stringify({
|
||||
data: 'json'
|
||||
})
|
||||
})
|
||||
return await res.json()
|
||||
}
|
||||
|
||||
function loadCSS(url) {
|
||||
var link = document.createElement('link');
|
||||
link.rel = 'stylesheet';
|
||||
link.type = 'text/css';
|
||||
link.href = url;
|
||||
document.getElementsByTagName('head')[0].appendChild(link);
|
||||
}
|
||||
|
||||
var cssURL = 'https://cdnjs.cloudflare.com/ajax/libs/github-markdown-css/5.5.0/github-markdown-light.min.css';
|
||||
loadCSS(cssURL);
|
||||
|
||||
function injectCSS (css) {
|
||||
// 检查页面中是否已经存在具有相同内容的style标签
|
||||
const existingStyle = document.querySelector('style')
|
||||
if (existingStyle && existingStyle.textContent === css) {
|
||||
return // 如果已经存在相同的样式,则不进行注入
|
||||
}
|
||||
|
||||
// 创建一个新的style标签,并将CSS内容注入其中
|
||||
const style = document.createElement('style')
|
||||
style.textContent = css
|
||||
|
||||
// 将style标签插入到页面的head元素中
|
||||
const head = document.querySelector('head')
|
||||
head.appendChild(style)
|
||||
}
|
||||
|
||||
injectCSS(`::-webkit-scrollbar {
|
||||
width: 2px;
|
||||
}
|
||||
|
||||
@keyframes loading_mixlab {
|
||||
0% {
|
||||
background-color: green;
|
||||
}
|
||||
|
||||
50% {
|
||||
background-color: lightgreen;
|
||||
}
|
||||
|
||||
100% {
|
||||
background-color: green;
|
||||
}
|
||||
}
|
||||
|
||||
.loading_mixlab {
|
||||
background-color: green;
|
||||
animation-name: loading_mixlab;
|
||||
animation-duration: 2s;
|
||||
animation-iteration-count: infinite;
|
||||
}`)
|
||||
|
||||
async function getCustomnodeMappings (mode = 'url') {
|
||||
// mode = "local";
|
||||
@@ -6,18 +101,39 @@ async function getCustomnodeMappings (mode = 'url') {
|
||||
let api_base = ''
|
||||
let url = `${window.location.protocol}//${api_host}${api_base}`
|
||||
|
||||
const response = await fetch(`${url}/customnode/getmappings?mode=${mode}`)
|
||||
const data = await response.json()
|
||||
|
||||
let nodes = {}
|
||||
try {
|
||||
for (let url in data) {
|
||||
let n = data[url]
|
||||
for (let node of n[0]) {
|
||||
nodes[node] = { url, title: n[1].title_aux }
|
||||
}
|
||||
|
||||
const data = (await get_nodes_map()).data
|
||||
|
||||
for (let url in data) {
|
||||
let n = data[url]
|
||||
for (let node of n[0]) {
|
||||
// if(node=='CLIPSeg')console.log('#CLIPSeg',n)
|
||||
nodes[node] = { url, title: n[1].title_aux }
|
||||
}
|
||||
} catch (error) {}
|
||||
}
|
||||
|
||||
// try {
|
||||
// const response = await fetch(`${url}/customnode/getmappings?mode=${mode}`)
|
||||
// const data = await response.json()
|
||||
// for (let url in data) {
|
||||
// let n = data[url]
|
||||
// for (let node of n[0]) {
|
||||
// // if(node=='CLIPSeg')console.log('#CLIPSeg',n)
|
||||
// nodes[node] = { url, title: n[1].title_aux }
|
||||
// }
|
||||
// }
|
||||
// } catch (error) {
|
||||
// const data = (await get_nodes_map()).data
|
||||
|
||||
// for (let url in data) {
|
||||
// let n = data[url]
|
||||
// for (let node of n[0]) {
|
||||
// // if(node=='CLIPSeg')console.log('#CLIPSeg',n)
|
||||
// nodes[node] = { url, title: n[1].title_aux }
|
||||
// }
|
||||
// }
|
||||
// }
|
||||
|
||||
return nodes
|
||||
}
|
||||
@@ -55,13 +171,51 @@ const missingNodeGithub = (missingNodeTypes, nodesMap) => {
|
||||
})
|
||||
}
|
||||
|
||||
let nodesMap
|
||||
|
||||
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'
|
||||
}
|
||||
}
|
||||
|
||||
app.showMissingNodesError = async function (
|
||||
missingNodeTypes,
|
||||
hasAddedNodes = true
|
||||
) {
|
||||
const nodesMap = await getCustomnodeMappings()
|
||||
console.log('#nodesMap', nodesMap)
|
||||
// console.log('###MIXLAB', missingNodeTypes, hasAddedNodes)
|
||||
nodesMap =
|
||||
nodesMap && Object.keys(nodesMap).length > 0
|
||||
? nodesMap
|
||||
: await getCustomnodeMappings('url')
|
||||
|
||||
// console.log('#nodesMap', nodesMap)
|
||||
// console.log('###MIXLAB', missingNodeTypes, hasAddedNodes)
|
||||
this.ui.dialog.show(
|
||||
`When loading the graph, the following node types were not found: <ul>${missingNodeGithub(
|
||||
missingNodeTypes,
|
||||
@@ -77,12 +231,507 @@ app.showMissingNodesError = async function (
|
||||
})
|
||||
}
|
||||
|
||||
// app.ui.dialog.show = function (html) {
|
||||
// console.log('###MIXLAB', html)
|
||||
// if (typeof html === 'string') {
|
||||
// this.textElement.innerHTML = html
|
||||
// } else {
|
||||
// this.textElement.replaceChildren(html)
|
||||
// }
|
||||
// this.element.style.display = 'flex'
|
||||
// }
|
||||
// app.registerExtension({
|
||||
// name: 'Comfy.MDNote',
|
||||
// registerCustomNodes () {
|
||||
// class NoteNode {
|
||||
// // color = LGraphCanvas.node_colors.yellow.color
|
||||
// // bgcolor = LGraphCanvas.node_colors.yellow.bgcolor
|
||||
// // groupcolor = LGraphCanvas.node_colors.yellow.groupcolor
|
||||
// constructor () {
|
||||
// if (!this.properties) {
|
||||
// this.properties = {}
|
||||
// this.properties.text = ''
|
||||
// }
|
||||
// console.log('NoteNode1', this)
|
||||
|
||||
// const widget = {
|
||||
// type: 'div',
|
||||
// name: 'input_color',
|
||||
// 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 = $el('div', {});
|
||||
// widget.div.innerText='1111'
|
||||
|
||||
// document.body.appendChild(widget.div)
|
||||
|
||||
// this.addCustomWidget(widget)
|
||||
|
||||
// this.serialize_widgets = true
|
||||
// this.isVirtualNode = true
|
||||
// }
|
||||
// }
|
||||
|
||||
// // Load default visibility
|
||||
|
||||
// LiteGraph.registerNodeType(
|
||||
// 'MDNote',
|
||||
// Object.assign(NoteNode, {
|
||||
// title_mode: LiteGraph.NORMAL_TITLE,
|
||||
// title: 'MDNote',
|
||||
// collapsable: true
|
||||
// })
|
||||
// )
|
||||
|
||||
// NoteNode.category = '♾️Mixlab/utils'
|
||||
// },
|
||||
|
||||
// })
|
||||
|
||||
async function fetchReadmeContent (url) {
|
||||
try {
|
||||
// var repo = 'owner/repo'; // 仓库的拥有者和名称
|
||||
var match = url.match(/github.com\/([^/]+\/[^/]+)/)
|
||||
var repo = match[1]
|
||||
var url = `https://api.github.com/repos/${repo}/readme`
|
||||
var response = await fetch(url)
|
||||
var data = await response.json()
|
||||
var readmeUrl = data.download_url
|
||||
|
||||
var readmeResponse = await fetch(readmeUrl)
|
||||
var content = await readmeResponse.text()
|
||||
// console.log(content) // 在控制台输出readme.md文件的内容
|
||||
|
||||
return content
|
||||
} catch (error) {
|
||||
console.log('获取readme.md文件信息失败:', error)
|
||||
}
|
||||
}
|
||||
|
||||
function createModal (url, markdown,title) {
|
||||
|
||||
// Create modal element
|
||||
var div =
|
||||
document.querySelector('#mix-modal') || document.createElement('div')
|
||||
div.id = 'mix-modal'
|
||||
div.innerHTML = ''
|
||||
div.style.cssText = `width: 100%;
|
||||
z-index: 9990;
|
||||
height: 100vh;
|
||||
display: flex;
|
||||
color: var(--descrip-text);
|
||||
position: fixed;
|
||||
top: 0;
|
||||
left: 0;
|
||||
`
|
||||
|
||||
var modal = document.createElement('div')
|
||||
|
||||
div.appendChild(modal)
|
||||
modal.classList.add("modal-body")
|
||||
// Set modal styles
|
||||
modal.style.cssText = `
|
||||
background: white;
|
||||
height: 80vh;
|
||||
position: fixed;
|
||||
overflow:hidden;
|
||||
top: 50%;
|
||||
left: 50%;
|
||||
transform: translate(-50%, -50%);
|
||||
z-index: 9999;
|
||||
border-radius: 4px;
|
||||
box-shadow: 4px 4px 14px rgba(255,255,255,0.5);
|
||||
|
||||
`
|
||||
// Create modal content area
|
||||
var modalContent = document.createElement('div')
|
||||
modalContent.classList.add('modal-content')
|
||||
// Create modal header
|
||||
const headerElement = document.createElement('div')
|
||||
headerElement.classList.add('modal-header')
|
||||
headerElement.style.cssText = `
|
||||
display: flex;
|
||||
padding: 20px 24px 8px 24px;
|
||||
justify-content: space-between;
|
||||
`
|
||||
|
||||
const headTitleElement = document.createElement('a')
|
||||
headTitleElement.classList.add('header-title')
|
||||
headTitleElement.style.cssText=`
|
||||
color: var(--descrip-text);
|
||||
font-size: 18px;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
flex: 1;
|
||||
overflow: hidden;
|
||||
text-decoration: none;
|
||||
font-weight: bold;
|
||||
`
|
||||
headTitleElement.onmouseenter = function(){
|
||||
headTitleElement.style.color = 'var(--comfy-menu-bg)'
|
||||
}
|
||||
headTitleElement.onmouseleave = function(){
|
||||
headTitleElement.style.color = 'var(--descrip-text)'
|
||||
}
|
||||
headTitleElement.textContent= title ||'';
|
||||
headTitleElement.href = url
|
||||
headTitleElement.target='_blank'
|
||||
const linkIcon = document.createElement('small')
|
||||
linkIcon.textContent = '🔗'
|
||||
headTitleElement.appendChild(linkIcon);
|
||||
headerElement.appendChild(headTitleElement)
|
||||
|
||||
|
||||
|
||||
// Create close button
|
||||
const closeButton = document.createElement('span')
|
||||
closeButton.classList.add('close')
|
||||
closeButton.innerHTML = closeIcon
|
||||
// Set close button styles
|
||||
closeButton.style.cssText = `
|
||||
padding: 4px;
|
||||
cursor: pointer;
|
||||
width: 32px;
|
||||
height: 32px;
|
||||
display: flex;
|
||||
justify-content: center;
|
||||
align-items: center;
|
||||
user-select: none;
|
||||
fill: var(--descrip-text);
|
||||
`
|
||||
closeButton.onmouseenter = function(){
|
||||
closeButton.style.fill = 'var(--comfy-menu-bg)';
|
||||
}
|
||||
closeButton.onmouseleave = function(){
|
||||
closeButton.style.fill = 'var(--descrip-text)';
|
||||
}
|
||||
|
||||
headerElement.appendChild(closeButton)
|
||||
|
||||
|
||||
// Click event to close the modal
|
||||
function closeMixModal(){
|
||||
div.style.display = 'none'
|
||||
window.removeEventListener('keydown',MixModalEscKeyEvent)
|
||||
}
|
||||
closeButton.onclick = function () {
|
||||
closeMixModal()
|
||||
}
|
||||
|
||||
// Set modal content area styles
|
||||
modalContent.style.cssText = `
|
||||
position: relative;
|
||||
padding: 0px;
|
||||
overflow: hidden scroll;;
|
||||
height: 100%;
|
||||
min-width:300px
|
||||
`
|
||||
|
||||
// Append close button to modal content area
|
||||
modal.appendChild(headerElement)
|
||||
|
||||
// Create element for displaying Markdown content
|
||||
var markdownContent = document.createElement('div')
|
||||
markdownContent.classList.add('markdown-content','markdown-body')
|
||||
markdownContent.style.cssText = `max-width: 50vw;padding: 0px 24px 100px 24px;`
|
||||
|
||||
showdown.setFlavor('github');
|
||||
var converter = new showdown.Converter()
|
||||
|
||||
var html = converter.makeHtml(markdown)
|
||||
|
||||
// Hide images in the markdown when they fail to load
|
||||
var regex = /<img[^>]+src="?([^"\s]+)"?[^>]*>/g
|
||||
html = html.replace(regex, function (match, src) {
|
||||
return `<img src="${src}" onerror="this.style.display='none'">`
|
||||
})
|
||||
|
||||
// Open links in a new tab or window
|
||||
html = html.replace(/<a/g, '<a target="_blank"')
|
||||
|
||||
// Fix href attribute to absolute path
|
||||
html = html.replace(
|
||||
/<a([^>]+href=["'])(?!https?:\/\/)([^"'>]+)/g,
|
||||
function (match, prefix, path) {
|
||||
var absolutePath = url + '/' + path
|
||||
return '<a' + prefix + absolutePath
|
||||
}
|
||||
)
|
||||
|
||||
markdownContent.innerHTML = html
|
||||
|
||||
// Append Markdown content element to modal content area
|
||||
modalContent.appendChild(markdownContent)
|
||||
|
||||
// Append modal content area to modal element
|
||||
modal.appendChild(modalContent)
|
||||
|
||||
const footerElement = document.createElement('div')
|
||||
footerElement.style.cssText=`
|
||||
position: absolute;
|
||||
left: 0;
|
||||
right: 0;
|
||||
text-align: right;
|
||||
padding:10px;
|
||||
font-size:12px
|
||||
`
|
||||
|
||||
const footerText = document.createElement('a')
|
||||
footerText.href ="https://github.com/shadowcz007/comfyui-mixlab-nodes"
|
||||
footerText.innerText = "Support by Mixlab"
|
||||
footerText.style.cssText=`color:inherit`
|
||||
footerText.target = "_blank"
|
||||
footerText.onmouseenter=function(){
|
||||
footerText.style.color = 'var(--input-text)'
|
||||
}
|
||||
footerText.onmouseleave=function(){
|
||||
footerText.style.color = 'inherit'
|
||||
}
|
||||
|
||||
|
||||
footerText.onclick = function(e){
|
||||
e.stopPropagation()
|
||||
}
|
||||
footerElement.appendChild(footerText)
|
||||
|
||||
div.appendChild(footerElement)
|
||||
|
||||
|
||||
// Append modal element to the page
|
||||
if (!document.querySelector('#mix-modal')) {
|
||||
document.body.appendChild(div)
|
||||
}
|
||||
function MixModalEscKeyEvent(event){
|
||||
if(event.key == "Escape"){
|
||||
closeMixModal()
|
||||
}
|
||||
}
|
||||
window.removeEventListener('keydown',MixModalEscKeyEvent)
|
||||
window.addEventListener('keydown',MixModalEscKeyEvent)
|
||||
|
||||
const bgElement = document.createElement('div')
|
||||
bgElement.classList.add('mix-modal-bg')
|
||||
bgElement.style.cssText = `
|
||||
width:100%;
|
||||
height:100%;
|
||||
background-color: rgba(0,0,0,0.8);
|
||||
`
|
||||
bgElement.onclick = function( ){
|
||||
closeMixModal()
|
||||
}
|
||||
|
||||
div.appendChild(bgElement)
|
||||
|
||||
|
||||
}
|
||||
|
||||
app.registerExtension({
|
||||
name: 'Comfy.Mixlab.ui',
|
||||
init () {
|
||||
LGraphCanvas.prototype.helpAboutNode = async function (node) {
|
||||
nodesMap =
|
||||
nodesMap && Object.keys(nodesMap).length > 0
|
||||
? nodesMap
|
||||
: await getCustomnodeMappings('url')
|
||||
|
||||
console.log('node & node map', node, nodesMap, nodesMap[node.type])
|
||||
let repo = nodesMap[node.type]
|
||||
if (repo) {
|
||||
let markdown = await fetchReadmeContent(repo.url)
|
||||
createModal(repo.url,markdown,repo.title)
|
||||
}
|
||||
}
|
||||
|
||||
const getNodeMenuOptions = LGraphCanvas.prototype.getNodeMenuOptions // store the existing method
|
||||
LGraphCanvas.prototype.getNodeMenuOptions = function (node) {
|
||||
// replace it
|
||||
const options = getNodeMenuOptions.apply(this, arguments) // start by calling the stored one
|
||||
node.setDirtyCanvas(true, true) // force a redraw of (foreground, background)
|
||||
// options.splice(
|
||||
// options.length - 1,
|
||||
// 0, // splice a new option in at the end
|
||||
// {
|
||||
// content: '♾️Mixlab', // with a name
|
||||
// callback: () => {
|
||||
// LGraphCanvas.prototype.helpAboutNode(node)
|
||||
// } // and the callback
|
||||
// },
|
||||
// null // a divider
|
||||
// )
|
||||
return [
|
||||
{
|
||||
content: 'Help ♾️Mixlab', // with a name
|
||||
callback: () => {
|
||||
LGraphCanvas.prototype.helpAboutNode(node)
|
||||
} // and the callback
|
||||
},
|
||||
null,
|
||||
...options
|
||||
] // and return the options
|
||||
}
|
||||
},
|
||||
async setup () {
|
||||
|
||||
// Add canvas menu options
|
||||
const orig = LGraphCanvas.prototype.getCanvasMenuOptions;
|
||||
LGraphCanvas.prototype.getCanvasMenuOptions = function () {
|
||||
const options = orig.apply(this, arguments);
|
||||
|
||||
options.push(null, {
|
||||
content: `Find ♾️Mixlab`,
|
||||
disabled: false, // or a function determining whether to disable
|
||||
callback: async () => {
|
||||
nodesMap =
|
||||
nodesMap && Object.keys(nodesMap).length > 0
|
||||
? nodesMap
|
||||
: await getCustomnodeMappings('url')
|
||||
|
||||
const nodesDiv = document.createDocumentFragment()
|
||||
const nodes = (await app.graphToPrompt()).output
|
||||
|
||||
// console.log('[Mixlab]', 'loaded graph node: ', app)
|
||||
let div =
|
||||
document.querySelector('#mixlab_find_the_node') ||
|
||||
document.createElement('div')
|
||||
div.id = 'mixlab_find_the_node'
|
||||
div.style = `
|
||||
flex-direction: column;
|
||||
align-items: end;
|
||||
display:flex;position: absolute;
|
||||
top: 50px; left: 50px; width: 200px;
|
||||
color: var(--descrip-text);
|
||||
background-color: var(--comfy-menu-bg);
|
||||
padding: 10px;
|
||||
border: 1px solid black;z-index: 999999999;padding-top: 0;`
|
||||
|
||||
div.innerHTML = ''
|
||||
|
||||
let btn = document.createElement('div')
|
||||
btn.style=`display: flex;
|
||||
width: calc(100% - 24px);
|
||||
justify-content: space-between;
|
||||
align-items: center;
|
||||
padding: 0 12px;
|
||||
height: 32px;`
|
||||
let btnB = document.createElement('button')
|
||||
let textB = document.createElement('p')
|
||||
btn.appendChild(textB)
|
||||
btn.appendChild(btnB)
|
||||
textB.innerText = `Find The Node`
|
||||
|
||||
btnB.style = `float: right; border: none; color: var(--input-text);
|
||||
background-color: var(--comfy-input-bg); border-color: var(--border-color);cursor: pointer;`
|
||||
btnB.addEventListener('click', () => {
|
||||
div.style.display = 'none'
|
||||
})
|
||||
btnB.innerText = 'X'
|
||||
|
||||
// 悬浮框拖动事件
|
||||
div.addEventListener('mousedown', function (e) {
|
||||
var startX = e.clientX
|
||||
var startY = e.clientY
|
||||
var offsetX = div.offsetLeft
|
||||
var offsetY = div.offsetTop
|
||||
|
||||
function moveBox (e) {
|
||||
var newX = e.clientX
|
||||
var newY = e.clientY
|
||||
var deltaX = newX - startX
|
||||
var deltaY = newY - startY
|
||||
div.style.left = offsetX + deltaX + 'px'
|
||||
div.style.top = offsetY + deltaY + 'px'
|
||||
}
|
||||
|
||||
function stopMoving () {
|
||||
document.removeEventListener('mousemove', moveBox)
|
||||
document.removeEventListener('mouseup', stopMoving)
|
||||
}
|
||||
|
||||
document.addEventListener('mousemove', moveBox)
|
||||
document.addEventListener('mouseup', stopMoving)
|
||||
})
|
||||
|
||||
div.appendChild(btn)
|
||||
|
||||
const updateNodes = (ns, nd) => {
|
||||
for (let nodeId in ns) {
|
||||
let n = ns[nodeId].class_type
|
||||
const { url, title } = nodesMap[n]
|
||||
let d = document.createElement('button')
|
||||
d.style = `text-align: left;margin:6px;color: var(--input-text);
|
||||
background-color: var(--comfy-input-bg); border-color: var(--border-color);cursor: pointer;`
|
||||
d.addEventListener('click', () => {
|
||||
const node = app.graph.getNodeById(nodeId)
|
||||
if (!node) return
|
||||
app.canvas.centerOnNode(node)
|
||||
app.canvas.setZoom(1)
|
||||
})
|
||||
d.addEventListener('mouseover', async () => {
|
||||
// console.log('mouseover')
|
||||
let n = (await app.graphToPrompt()).output
|
||||
if (!deepEqual(n, ns)) {
|
||||
nd.innerHTML = ''
|
||||
updateNodes(n, nd)
|
||||
}
|
||||
})
|
||||
|
||||
d.innerHTML = `
|
||||
<span>${'#' + nodeId} ${n}</span>
|
||||
<a href="${url}" target="_blank" style="text-decoration: none;">🔗</a>
|
||||
`
|
||||
d.title = title
|
||||
|
||||
nd.appendChild(d)
|
||||
}
|
||||
}
|
||||
|
||||
let nodesDivv = document.createElement('div')
|
||||
|
||||
for (let nodeId in nodes) {
|
||||
let n = nodes[nodeId].class_type
|
||||
const { url, title } = nodesMap[n]
|
||||
let d = document.createElement('button')
|
||||
d.style = `text-align: left;margin:6px;color: var(--input-text);
|
||||
background-color: var(--comfy-input-bg); border-color: var(--border-color);cursor: pointer;`
|
||||
d.addEventListener('click', () => {
|
||||
const node = app.graph.getNodeById(nodeId)
|
||||
if (!node) return
|
||||
app.canvas.centerOnNode(node)
|
||||
app.canvas.setZoom(1)
|
||||
})
|
||||
d.addEventListener('mouseover', async () => {
|
||||
console.log('mouseover')
|
||||
let n = (await app.graphToPrompt()).output
|
||||
if (!deepEqual(n, nodes)) {
|
||||
nodesDivv.innerHTML = ''
|
||||
updateNodes(n, nodesDivv)
|
||||
}
|
||||
})
|
||||
|
||||
d.innerHTML = `
|
||||
<span>${'#' + nodeId} ${n}</span>
|
||||
<a href="${url}" target="_blank" style="text-decoration: none;">🔗</a>
|
||||
`
|
||||
d.title = title
|
||||
|
||||
nodesDiv.appendChild(d)
|
||||
}
|
||||
|
||||
nodesDivv.appendChild(nodesDiv)
|
||||
nodesDivv.style=`overflow: scroll;
|
||||
height: 70vh;width: 100%;`
|
||||
|
||||
div.appendChild(nodesDivv)
|
||||
|
||||
if (!document.querySelector('#mixlab_find_the_node'))
|
||||
document.body.appendChild(div)
|
||||
}
|
||||
});
|
||||
return options;
|
||||
};
|
||||
|
||||
|
||||
|
||||
}
|
||||
})
|
||||
|
||||
@@ -0,0 +1,168 @@
|
||||
|
||||
import { app } from '../../../scripts/app.js'
|
||||
import { api } from '../../../scripts/api.js'
|
||||
import { ComfyWidgets } from '../../../scripts/widgets.js'
|
||||
import { $el } from '../../../scripts/ui.js'
|
||||
|
||||
|
||||
|
||||
const getLocalData = key => {
|
||||
let data = {}
|
||||
try {
|
||||
data = JSON.parse(localStorage.getItem(key)) || {}
|
||||
} catch (error) {
|
||||
return {}
|
||||
}
|
||||
return data
|
||||
}
|
||||
function get_position_style (ctx, widget_width, y, node_height) {
|
||||
const MARGIN = 4 // the margin around the html element
|
||||
|
||||
/* Create a transform that deals with all the scrolling and zooming */
|
||||
const elRect = ctx.canvas.getBoundingClientRect()
|
||||
const transform = new DOMMatrix()
|
||||
.scaleSelf(
|
||||
elRect.width / ctx.canvas.width,
|
||||
elRect.height / ctx.canvas.height
|
||||
)
|
||||
.multiplySelf(ctx.getTransform())
|
||||
.translateSelf(MARGIN, MARGIN + y)
|
||||
|
||||
return {
|
||||
transformOrigin: '0 0',
|
||||
transform: transform,
|
||||
left: `0`,
|
||||
top: `0`,
|
||||
cursor: 'pointer',
|
||||
position: 'absolute',
|
||||
maxWidth: `${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'
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
app.registerExtension({
|
||||
name: 'Mixlab.utils.Color',
|
||||
async getCustomWidgets (app) {
|
||||
return {
|
||||
TCOLOR (node, inputName, inputData, app) {
|
||||
// console.log('##node', node)
|
||||
const widget = {
|
||||
type: inputData[0], // the type, CHEESE
|
||||
name: inputName, // the name, slice
|
||||
size: [128, 32], // a default size
|
||||
draw (ctx, node, width, y) {},
|
||||
computeSize (...args) {
|
||||
return [128, 32] // a method to compute the current size of the widget
|
||||
},
|
||||
async serializeValue (nodeId, widgetIndex) {
|
||||
let data = getLocalData('_mixlab_utils_color')
|
||||
return data[node.id] || '#000000'
|
||||
}
|
||||
}
|
||||
// widget.something = something; // maybe adds stuff to it
|
||||
node.addCustomWidget(widget) // adds it to the node
|
||||
return widget // and returns it.
|
||||
}
|
||||
}
|
||||
},
|
||||
|
||||
async beforeRegisterNodeDef (nodeType, nodeData, app) {
|
||||
if (nodeType.comfyClass == 'Color') {
|
||||
const orig_nodeCreated = nodeType.prototype.onNodeCreated
|
||||
nodeType.prototype.onNodeCreated = function () {
|
||||
orig_nodeCreated?.apply(this, arguments)
|
||||
|
||||
console.log('Color nodeData', this.widgets)
|
||||
|
||||
const widget = {
|
||||
type: 'div',
|
||||
name: 'input_color',
|
||||
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 = $el('div', {})
|
||||
|
||||
document.body.appendChild(widget.div)
|
||||
|
||||
const inputDiv = (key, placeholder, value) => {
|
||||
let div = document.createElement('div')
|
||||
const ip = document.createElement('input')
|
||||
ip.type = 'color'
|
||||
ip.className = `${'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: 100%;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)
|
||||
|
||||
ip.addEventListener('change', () => {
|
||||
let data = getLocalData(key)
|
||||
data[this.id] = ip.value.trim()
|
||||
localStorage.setItem(key, JSON.stringify(data))
|
||||
// console.log(this.id, ip.value.trim())
|
||||
})
|
||||
return div
|
||||
}
|
||||
|
||||
let inputColor = inputDiv('_mixlab_utils_color', 'Color', '#000000')
|
||||
|
||||
widget.div.appendChild(inputColor)
|
||||
|
||||
this.addCustomWidget(widget)
|
||||
|
||||
const onRemoved = this.onRemoved
|
||||
this.onRemoved = () => {
|
||||
inputColor.remove()
|
||||
widget.div.remove()
|
||||
return onRemoved?.()
|
||||
}
|
||||
|
||||
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
|
||||
|
||||
if (node.type === 'Color') {
|
||||
let widget = node.widgets.filter(w => w.div)[0]
|
||||
|
||||
let data = getLocalData('_mixlab_utils_color')
|
||||
|
||||
let id = node.id
|
||||
|
||||
widget.div.querySelector('.Color').value = data[id] || '#000000'
|
||||
}
|
||||
}
|
||||
})
|
||||
Vendored
+1077
File diff suppressed because one or more lines are too long
Vendored
+3
File diff suppressed because one or more lines are too long
+23
-2
@@ -1,3 +1,24 @@
|
||||
::-webkit-scrollbar {
|
||||
width: 2px;
|
||||
}
|
||||
width: 2px;
|
||||
}
|
||||
|
||||
@keyframes loading_mixlab {
|
||||
0% {
|
||||
background-color: green;
|
||||
}
|
||||
|
||||
50% {
|
||||
background-color: lightgreen;
|
||||
}
|
||||
|
||||
100% {
|
||||
background-color: green;
|
||||
}
|
||||
}
|
||||
|
||||
.loading_mixlab {
|
||||
background-color: green;
|
||||
animation-name: loading_mixlab;
|
||||
animation-duration: 2s;
|
||||
animation-iteration-count: infinite;
|
||||
}
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"last_node_id": 22,
|
||||
"last_link_id": 48,
|
||||
"last_node_id": 23,
|
||||
"last_link_id": 51,
|
||||
"nodes": [
|
||||
{
|
||||
"id": 7,
|
||||
@@ -105,7 +105,7 @@
|
||||
{
|
||||
"name": "text",
|
||||
"type": "STRING",
|
||||
"link": 48,
|
||||
"link": 51,
|
||||
"widget": {
|
||||
"name": "text"
|
||||
}
|
||||
@@ -316,13 +316,13 @@
|
||||
"1": 246
|
||||
},
|
||||
"flags": {},
|
||||
"order": 6,
|
||||
"order": 7,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "images",
|
||||
"type": "IMAGE",
|
||||
"link": 46
|
||||
"link": 50
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
@@ -445,13 +445,13 @@
|
||||
"1": 58
|
||||
},
|
||||
"flags": {},
|
||||
"order": 7,
|
||||
"order": 6,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "image",
|
||||
"type": "IMAGE",
|
||||
"link": 47
|
||||
"link": 49
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
@@ -472,45 +472,6 @@
|
||||
512
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 22,
|
||||
"type": "ScreenShare",
|
||||
"pos": [
|
||||
-63,
|
||||
483
|
||||
],
|
||||
"size": {
|
||||
"0": 315,
|
||||
"1": 98
|
||||
},
|
||||
"flags": {},
|
||||
"order": 3,
|
||||
"mode": 0,
|
||||
"outputs": [
|
||||
{
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": [
|
||||
46,
|
||||
47
|
||||
],
|
||||
"shape": 3,
|
||||
"slot_index": 0
|
||||
},
|
||||
{
|
||||
"name": "STRING",
|
||||
"type": "STRING",
|
||||
"links": [
|
||||
48
|
||||
],
|
||||
"shape": 3,
|
||||
"slot_index": 1
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "ScreenShare"
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 20,
|
||||
"type": "FloatingVideo",
|
||||
@@ -518,10 +479,10 @@
|
||||
1928,
|
||||
295
|
||||
],
|
||||
"size": [
|
||||
315,
|
||||
58
|
||||
],
|
||||
"size": {
|
||||
"0": 315,
|
||||
"1": 58
|
||||
},
|
||||
"flags": {},
|
||||
"order": 12,
|
||||
"mode": 0,
|
||||
@@ -534,7 +495,68 @@
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "FloatingVideo"
|
||||
}
|
||||
},
|
||||
"widgets_values": [
|
||||
null
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 23,
|
||||
"type": "ScreenShare",
|
||||
"pos": [
|
||||
-65,
|
||||
446
|
||||
],
|
||||
"size": {
|
||||
"0": 315,
|
||||
"1": 170
|
||||
},
|
||||
"flags": {},
|
||||
"order": 3,
|
||||
"mode": 0,
|
||||
"outputs": [
|
||||
{
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": [
|
||||
49,
|
||||
50
|
||||
],
|
||||
"shape": 3,
|
||||
"slot_index": 0
|
||||
},
|
||||
{
|
||||
"name": "PROMPT",
|
||||
"type": "STRING",
|
||||
"links": [
|
||||
51
|
||||
],
|
||||
"shape": 3,
|
||||
"slot_index": 1
|
||||
},
|
||||
{
|
||||
"name": "FLOAT",
|
||||
"type": "FLOAT",
|
||||
"links": null,
|
||||
"shape": 3
|
||||
},
|
||||
{
|
||||
"name": "INT",
|
||||
"type": "INT",
|
||||
"links": null,
|
||||
"shape": 3
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "ScreenShare"
|
||||
},
|
||||
"widgets_values": [
|
||||
null,
|
||||
null,
|
||||
null,
|
||||
null,
|
||||
null
|
||||
]
|
||||
}
|
||||
],
|
||||
"links": [
|
||||
@@ -787,24 +809,24 @@
|
||||
"CLIP"
|
||||
],
|
||||
[
|
||||
46,
|
||||
22,
|
||||
0,
|
||||
2,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
47,
|
||||
22,
|
||||
49,
|
||||
23,
|
||||
0,
|
||||
18,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
48,
|
||||
22,
|
||||
50,
|
||||
23,
|
||||
0,
|
||||
2,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
51,
|
||||
23,
|
||||
1,
|
||||
8,
|
||||
1,
|
||||
|
||||
+142
-135
@@ -1,13 +1,13 @@
|
||||
{
|
||||
"last_node_id": 23,
|
||||
"last_link_id": 54,
|
||||
"last_node_id": 24,
|
||||
"last_link_id": 59,
|
||||
"nodes": [
|
||||
{
|
||||
"id": 7,
|
||||
"type": "CLIPTextEncode",
|
||||
"pos": [
|
||||
495,
|
||||
307
|
||||
515,
|
||||
130
|
||||
],
|
||||
"size": {
|
||||
"0": 400,
|
||||
@@ -45,8 +45,8 @@
|
||||
"id": 8,
|
||||
"type": "CLIPTextEncode",
|
||||
"pos": [
|
||||
504,
|
||||
33
|
||||
515,
|
||||
1268
|
||||
],
|
||||
"size": {
|
||||
"0": 400,
|
||||
@@ -64,7 +64,7 @@
|
||||
{
|
||||
"name": "text",
|
||||
"type": "STRING",
|
||||
"link": 48,
|
||||
"link": 59,
|
||||
"widget": {
|
||||
"name": "text"
|
||||
}
|
||||
@@ -92,8 +92,8 @@
|
||||
"id": 6,
|
||||
"type": "LoraLoader",
|
||||
"pos": [
|
||||
112,
|
||||
5
|
||||
515,
|
||||
460
|
||||
],
|
||||
"size": {
|
||||
"0": 315,
|
||||
@@ -140,58 +140,17 @@
|
||||
1
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 23,
|
||||
"type": "VAEEncode",
|
||||
"pos": [
|
||||
563,
|
||||
663
|
||||
],
|
||||
"size": {
|
||||
"0": 210,
|
||||
"1": 46
|
||||
},
|
||||
"flags": {},
|
||||
"order": 5,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "pixels",
|
||||
"type": "IMAGE",
|
||||
"link": 52
|
||||
},
|
||||
{
|
||||
"name": "vae",
|
||||
"type": "VAE",
|
||||
"link": 53
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "LATENT",
|
||||
"type": "LATENT",
|
||||
"links": [
|
||||
54
|
||||
],
|
||||
"shape": 3,
|
||||
"slot_index": 0
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "VAEEncode"
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 5,
|
||||
"type": "KSampler",
|
||||
"pos": [
|
||||
1085,
|
||||
49
|
||||
],
|
||||
"size": [
|
||||
315,
|
||||
262
|
||||
1015,
|
||||
130
|
||||
],
|
||||
"size": {
|
||||
"0": 315,
|
||||
"1": 262
|
||||
},
|
||||
"flags": {},
|
||||
"order": 7,
|
||||
"mode": 0,
|
||||
@@ -219,7 +178,7 @@
|
||||
{
|
||||
"name": "denoise",
|
||||
"type": "FLOAT",
|
||||
"link": 49,
|
||||
"link": 56,
|
||||
"widget": {
|
||||
"name": "denoise"
|
||||
}
|
||||
@@ -253,8 +212,8 @@
|
||||
"id": 11,
|
||||
"type": "VAEDecode",
|
||||
"pos": [
|
||||
1451,
|
||||
59
|
||||
1430,
|
||||
130
|
||||
],
|
||||
"size": {
|
||||
"0": 210,
|
||||
@@ -294,13 +253,13 @@
|
||||
"id": 20,
|
||||
"type": "FloatingVideo",
|
||||
"pos": [
|
||||
1464,
|
||||
243
|
||||
],
|
||||
"size": [
|
||||
315,
|
||||
58
|
||||
1740,
|
||||
130
|
||||
],
|
||||
"size": {
|
||||
"0": 315,
|
||||
"1": 58
|
||||
},
|
||||
"flags": {},
|
||||
"order": 9,
|
||||
"mode": 0,
|
||||
@@ -318,12 +277,78 @@
|
||||
null
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 2,
|
||||
"type": "PreviewImage",
|
||||
"pos": [
|
||||
515,
|
||||
716
|
||||
],
|
||||
"size": {
|
||||
"0": 210,
|
||||
"1": 246
|
||||
},
|
||||
"flags": {},
|
||||
"order": 4,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "images",
|
||||
"type": "IMAGE",
|
||||
"link": 55
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "PreviewImage"
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 23,
|
||||
"type": "VAEEncode",
|
||||
"pos": [
|
||||
515,
|
||||
1092
|
||||
],
|
||||
"size": {
|
||||
"0": 210,
|
||||
"1": 46
|
||||
},
|
||||
"flags": {},
|
||||
"order": 5,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "pixels",
|
||||
"type": "IMAGE",
|
||||
"link": 57
|
||||
},
|
||||
{
|
||||
"name": "vae",
|
||||
"type": "VAE",
|
||||
"link": 58
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "LATENT",
|
||||
"type": "LATENT",
|
||||
"links": [
|
||||
54
|
||||
],
|
||||
"shape": 3,
|
||||
"slot_index": 0
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "VAEEncode"
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": 10,
|
||||
"type": "CheckpointLoaderSimple",
|
||||
"pos": [
|
||||
80,
|
||||
238
|
||||
100,
|
||||
130
|
||||
],
|
||||
"size": {
|
||||
"0": 315,
|
||||
@@ -358,7 +383,7 @@
|
||||
"type": "VAE",
|
||||
"links": [
|
||||
34,
|
||||
53
|
||||
58
|
||||
],
|
||||
"shape": 3,
|
||||
"slot_index": 2
|
||||
@@ -372,15 +397,15 @@
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 22,
|
||||
"id": 24,
|
||||
"type": "ScreenShare",
|
||||
"pos": [
|
||||
103,
|
||||
412
|
||||
100,
|
||||
358
|
||||
],
|
||||
"size": {
|
||||
"0": 315,
|
||||
"1": 146
|
||||
"1": 170
|
||||
},
|
||||
"flags": {},
|
||||
"order": 1,
|
||||
@@ -390,17 +415,17 @@
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": [
|
||||
46,
|
||||
52
|
||||
55,
|
||||
57
|
||||
],
|
||||
"shape": 3,
|
||||
"slot_index": 0
|
||||
},
|
||||
{
|
||||
"name": "STRING",
|
||||
"name": "PROMPT",
|
||||
"type": "STRING",
|
||||
"links": [
|
||||
48
|
||||
59
|
||||
],
|
||||
"shape": 3,
|
||||
"slot_index": 1
|
||||
@@ -409,10 +434,16 @@
|
||||
"name": "FLOAT",
|
||||
"type": "FLOAT",
|
||||
"links": [
|
||||
49
|
||||
56
|
||||
],
|
||||
"shape": 3,
|
||||
"slot_index": 2
|
||||
},
|
||||
{
|
||||
"name": "INT",
|
||||
"type": "INT",
|
||||
"links": null,
|
||||
"shape": 3
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
@@ -422,33 +453,9 @@
|
||||
null,
|
||||
null,
|
||||
null,
|
||||
null,
|
||||
null
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 2,
|
||||
"type": "PreviewImage",
|
||||
"pos": [
|
||||
-501,
|
||||
918
|
||||
],
|
||||
"size": {
|
||||
"0": 210,
|
||||
"1": 246
|
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Reference in New Issue
Block a user