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15 changed files with 227 additions and 265 deletions
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@@ -0,0 +1 @@
mixlabnodes.com
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@@ -167,6 +167,9 @@ pip install llama-cpp-python \
> 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.
> The composite images node overlays a foreground image onto a background image at specified positions and scales, with optional blending modes and masking capabilities. position : 'overall',"center_center","left_bottom","center_bottom","right_bottom","left_top","center_top","right_top"
![layers](./assets/layers-workflow.svg)
![poster](./assets/poster-workflow.svg)
@@ -198,6 +201,12 @@ pip install llama-cpp-python \
> Conveniently load images from a fixed address on the internet to ensure that default images in the workflow can be executed.
#### TextImage
> [下载字体](https://drxie.github.io/OSFCC/)放到 ```custom_nodes/comfyui-mixlab-nodes/assets/fonts```
### Style
> Apply VisualStyle Prompting , Modified from [ComfyUI_VisualStylePrompting](https://github.com/ExponentialML/ComfyUI_VisualStylePrompting)
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@@ -939,6 +939,10 @@ NODE_CLASS_MAPPINGS = {
# 一个包含节点友好/可读的标题的字典
NODE_DISPLAY_NAME_MAPPINGS = {
"AppInfo":"App Info ♾️MixlabApp",
"ScreenShare":"Screen Share ♾️Mixlab",
"FloatingVideo":"Floating Video ♾️Mixlab",
"TextImage":"Text Image ♾️Mixlab",
"Color":"Color Input ♾️MixlabApp",
"TextInput_":"Text Input ♾️MixlabApp",
"FloatSlider":"Float Slider Input ♾️MixlabApp",
@@ -952,8 +956,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"SplitLongMask":"Splitting a long image into sections",
"VAELoaderConsistencyDecoder":"Consistency Decoder Loader",
"VAEDecodeConsistencyDecoder":"Consistency Decoder Decode",
"ScreenShare":"Screen Share ♾️Mixlab",
"FloatingVideo":"FloatingVideo ♾️Mixlab",
"MergeLayers":"Merge Layers ♾️Mixlab",
"SpeechSynthesis":"SpeechSynthesis ♾️Mixlab",
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@@ -15,7 +15,7 @@ import cv2
import string
import math,glob
from .Watcher import FolderWatcher
import hashlib
@@ -29,142 +29,99 @@ def opencv_to_pil(image):
pil_image = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))
return pil_image
# 列出目录下面的所有文件
def get_files_with_extension(directory, extension):
file_list = []
for root, dirs, files in os.walk(directory):
for file in files:
if file.endswith(extension):
file = os.path.splitext(file)[0]
file_path = os.path.join(root, file)
file_name = os.path.relpath(file_path, directory)
file_list.append(file_name)
return file_list
def composite_images(foreground, background, mask,is_multiply_blend=False,position="overall"):
width,height=foreground.size
bg_image=background
def composite_images(foreground, background, mask, is_multiply_blend=False, position="overall", scale=0.25):
width, height = foreground.size
bg_image = background
bwidth, bheight = bg_image.size
bwidth,bheight=bg_image.size
def determine_scale_option(width, height):
return 'height' if height > width else 'width'
# 按z-index排序
if position=="overall":
if position == "overall":
layer = {
"x":0,
"y":0,
"width":bwidth,
"height":bheight,
"z_index":88,
"scale_option":'overall',
"image":foreground,
"mask":mask
"x": 0,
"y": 0,
"width": bwidth,
"height": bheight,
"z_index": 88,
"scale_option": 'overall',
"image": foreground,
"mask": mask
}
else:
scale_option = determine_scale_option(width, height)
if scale_option == 'height':
scale = int(bheight * scale) / height
else:
scale = int(bwidth * scale) / width
elif position=='center_bottom':
scale = int(bwidth*0.25) / width
new_width = int(width * scale)
new_height = int(height * scale)
layer = {
"x":int(bwidth*0.75*0.5),
"y":bheight-new_height-24,
"width":int(bwidth*0.25),
"height":int(bheight*0.25),
"z_index":88,
"scale_option":'width',
"image":foreground,
"mask":mask
}
elif position=='right_bottom':
scale = int(bwidth*0.25) / width
new_height = int(height * scale)
if position == 'center_bottom':
x_position = int((bwidth - new_width) * 0.5)
y_position = bheight - new_height - 24
elif position == 'right_bottom':
x_position = bwidth - new_width - 24
y_position = bheight - new_height - 24
elif position == 'center_top':
x_position = int((bwidth - new_width) * 0.5)
y_position = 24
elif position == 'right_top':
x_position = bwidth - new_width - 24
y_position = 24
elif position == 'left_top':
x_position = 24
y_position = 24
elif position == 'left_bottom':
x_position = 24
y_position = bheight - new_height - 24
elif position == 'center_center':
x_position = int((bwidth - new_width) * 0.5)
y_position = int((bheight - new_height) * 0.5)
layer = {
"x":bwidth-int(bwidth*0.25)-24,
"y":bheight-new_height-24,
"width":int(bwidth*0.25),
"height":int(bheight*0.25),
"z_index":88,
"scale_option":'width',
"image":foreground,
"mask":mask
"x": x_position,
"y": y_position,
"width": new_width,
"height": new_height,
"z_index": 88,
"scale_option": scale_option,
"image": foreground,
"mask": mask
}
layer_image = layer['image']
layer_mask = layer['mask']
elif position=='center_top':
scale = int(bwidth*0.25) / width
new_height = int(height * scale)
bg_image = merge_images(bg_image,
layer_image,
layer_mask,
layer['x'],
layer['y'],
layer['width'],
layer['height'],
layer['scale_option'],
is_multiply_blend)
layer = {
"x":int( bwidth*0.75*0.5),
"y":24,
"width":int(bwidth*0.25),
"height":int(bheight*0.25),
"z_index":88,
"scale_option":'width',
"image":foreground,
"mask":mask
}
bg_image = bg_image.convert('RGB')
elif position=='right_top':
scale = int(bwidth*0.25) / width
new_height = int(height * scale)
layer = {
"x":bwidth-int(bwidth*0.25)-24,
"y":24,
"width":int(bwidth*0.25),
"height":int(bheight*0.25),
"z_index":88,
"scale_option":'width',
"image":foreground,
"mask":mask
}
elif position=='left_top':
scale = int(bwidth*0.25) / width
new_height = int(height * scale)
layer = {
"x":24,
"y":24,
"width":int(bwidth*0.25),
"height":int(bheight*0.25),
"z_index":88,
"scale_option":'width',
"image":foreground,
"mask":mask
}
elif position=='left_bottom':
scale = int(bwidth*0.25) / width
new_height = int(height * scale)
layer = {
"x":24,
"y":bheight-new_height-24,
"width":int(bwidth*0.25),
"height":int(bheight*0.25),
"z_index":88,
"scale_option":'width',
"image":foreground,
"mask":mask
}
# width, height = bg_image.size
layer_image=layer['image']
layer_mask=layer['mask']
bg_image=merge_images(bg_image,
layer_image,
layer_mask,
layer['x'],
layer['y'],
layer['width'],
layer['height'],
layer['scale_option'],
is_multiply_blend )
bg_image=bg_image.convert('RGB')
return bg_image
def count_files_in_directory(directory):
file_count = 0
for _, _, files in os.walk(directory):
@@ -201,7 +158,8 @@ class AnyType(str):
any_type = AnyType("*")
FONT_PATH= os.path.abspath(os.path.join(os.path.dirname(__file__),'../assets/王汉宗颜楷体繁.ttf'))
FONT_PATH= os.path.abspath(os.path.join(os.path.dirname(__file__),'../assets/fonts'))
MAX_RESOLUTION=8192
@@ -803,85 +761,78 @@ def multiply_blend(image1, image2):
# cv2.imwrite('result.jpg', result)
# 使用gpt4o优化代码
# 为了消除图像合并时出现的灰色描边,可以使用以下方法:
# 调整透明度:确保透明像素不会引入不需要的颜色。
# 预处理图像:在缩放图像之前,可以先将图像的边缘进行预处理,例如扩展边缘颜色,减少抗锯齿带来的过渡效果。
def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option,is_multiply_blend=False):
def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option, is_multiply_blend=False):
# 打开底图
bg_image = bg_image.convert("RGBA")
# 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))
layer_image = layer_image.resize((new_width, height), Image.NEAREST)
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))
layer_image = layer_image.resize((width, new_height), Image.NEAREST)
elif scale_option == "overall":
# 整体缩放
layer_image = layer_image.resize((width, height))
layer_image = layer_image.resize((width, height), Image.NEAREST)
elif scale_option == "longest":
original_width, original_height = layer_image.size
if original_width > original_height:
new_width=width
new_width = width
scale = width / original_width
new_height = int(original_height * scale)
x=0
y=int((height-new_height)*0.5)
x = 0
y = int((height - new_height) * 0.5)
else:
new_height=height
new_height = height
scale = height / original_height
new_width = int(original_height * scale)
x=int((width-new_width)*0.5)
y=0
# elif side == "shortest":
# if width < height:
#
# else:
#
x = int((width - new_width) * 0.5)
y = 0
# 调整mask的大小
nw, nh = layer_image.size
mask = mask.resize((nw, nh))
mask = mask.resize((nw, nh), Image.NEAREST)
# # 分离出a通道
# r, g, b, alpha = layer_image.split()
# alpha = ImageOps.invert(alpha)
# # 创建一个新的RGB图像
# new_rgb_image = Image.new("RGB", layer_image.size)
# # 将透明通道粘贴到新的RGB图像上
# new_rgb_image.paste(layer_image, (0, 0), mask=alpha)
# new_rgb_image.paste(layer_image, (x, y), mask=mask)
# mask=new_rgb_image.convert('L')
# mask = ImageOps.invert(mask)
# 预处理图像边缘以减少灰色描边
layer_image = layer_image.filter(ImageFilter.SMOOTH)
if is_multiply_blend:
bg_image_white=Image.new("RGB", bg_image.size,(255, 255, 255))
bg_image_white = Image.new("RGB", bg_image.size, (255, 255, 255))
bg_image_white.paste(layer_image, (x, y), mask=mask)
bg_image=multiply_blend(bg_image_white,bg_image)
bg_image=bg_image.convert("RGBA")
bg_image = multiply_blend(bg_image_white, bg_image)
bg_image = bg_image.convert("RGBA")
else:
transparent_img = Image.new("RGBA",layer_image.size, (255, 255, 255, 0))
transparent_img.paste(layer_image,(0, 0), mask)
# transparent_img.save('test.png')
bg_image.paste(transparent_img, (x, y), transparent_img)
transparent_img = Image.new("RGBA", layer_image.size, (255, 255, 255, 0))
# 调整透明度处理
for i in range(transparent_img.size[0]):
for j in range(transparent_img.size[1]):
r, g, b, a = transparent_img.getpixel((i, j))
if a > 0:
transparent_img.putpixel((i, j), (r, g, b, 255))
transparent_img.paste(layer_image, (0, 0), mask)
bg_image.paste(transparent_img, (x, y), transparent_img)
# 输出合成后的图片
return bg_image
#MixCopilot
def resize_2(img):
# 检查图像的高度是否是2的倍数,如果不是,则调整高度
@@ -955,53 +906,13 @@ def resize_image(layer_image, scale_option, width, height,color="white"):
return layer_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 generate_text_image(text, font_path, font_size, text_color, vertical=True, stroke=False, stroke_color=(0, 0, 0), stroke_width=1, spacing=0):
def generate_text_image(text, font_path, font_size, text_color, vertical=True, stroke=False, stroke_color=(0, 0, 0), stroke_width=1, spacing=0, padding=4):
# Split text into lines based on line breaks
lines = text.split("\n")
# Load font
font = ImageFont.truetype(font_path, font_size)
# 1. Determine layout direction
if vertical:
layout = "vertical"
@@ -1010,44 +921,41 @@ def generate_text_image(text, font_path, font_size, text_color, vertical=True, s
# 2. Calculate absolute coordinates for each character
char_coordinates = []
if layout == "vertical":
x = 0
y = 0
for i in range(len(lines)):
line = lines[i]
for char in line:
char_coordinates.append((x, y))
y += font_size + spacing
x += font_size + spacing
y = 0
else:
x = 0
y = 0
for line in lines:
for char in line:
char_coordinates.append((x, y))
x += font_size + spacing
y += font_size + spacing
x = 0
x, y = padding, padding
max_width, max_height = 0, 0
# 3. Calculate image width and height
if layout == "vertical":
width = (len(lines) * (font_size + spacing)) - spacing
height = ((len(max(lines, key=len)) + 1) * (font_size + spacing)) + spacing
for line in lines:
max_char_width = max(font.getsize(char)[0] for char in line)
for char in line:
char_width, char_height = font.getsize(char)
char_coordinates.append((x, y))
y += char_height + spacing
max_height = max(max_height, y + padding)
x += max_char_width + spacing
y = padding
max_width = x
else:
width = (len(max(lines, key=len)) * (font_size + spacing)) - spacing
height = ((len(lines) - 1) * (font_size + spacing)) + font_size
for line in lines:
line_width, line_height = font.getsize(line)
for char in line:
char_width, char_height = font.getsize(char)
char_coordinates.append((x, y))
x += char_width + spacing
max_width = max(max_width, x + padding)
y += line_height + spacing
x = padding
max_height = y
# 3. Create image with calculated width and height
image = Image.new('RGBA', (max_width, max_height), (255, 255, 255, 0))
draw = ImageDraw.Draw(image)
# 4. Draw each character on the image
image = Image.new('RGBA', (width, height), (255, 255, 255, 0))
draw = ImageDraw.Draw(image)
font = ImageFont.truetype(font_path, font_size)
index = 0
for i, line in enumerate(lines):
for j, char in enumerate(line):
for line in lines:
for char in line:
x, y = char_coordinates[index]
if stroke:
draw.text((x-stroke_width, y), char, font=font, fill=stroke_color)
draw.text((x+stroke_width, y), char, font=font, fill=stroke_color)
@@ -1579,7 +1487,7 @@ class ImageCropByAlpha:
# get_files_with_extension(FONT_PATH,'.ttf')
class TextImage:
@classmethod
@@ -1587,7 +1495,7 @@ class TextImage:
return {"required": {
"text": ("STRING",{"multiline": True,"default": "龍馬精神迎新歲","dynamicPrompts": False}),
"font_path": ("STRING",{"multiline": False,"default": FONT_PATH,"dynamicPrompts": False}),
"font": (get_files_with_extension(FONT_PATH,'.ttf'),),#后缀为 ttf
"font_size": ("INT",{
"default":100,
"min": 100, #Minimum value
@@ -1602,6 +1510,13 @@ class TextImage:
"step": 1, #Slider's step
"display": "number" # Cosmetic only: display as "number" or "slider"
}),
"padding": ("INT",{
"default":8,
"min": 0, #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","dynamicPrompts": False}),
"vertical":("BOOLEAN", {"default": True},),
"stroke":("BOOLEAN", {"default": False},),
@@ -1609,7 +1524,7 @@ class TextImage:
}
RETURN_TYPES = ("IMAGE","MASK",)
# RETURN_NAMES = ("WIDTH","HEIGHT","X","Y",)
RETURN_NAMES = ("image","mask",)
FUNCTION = "run"
@@ -1618,11 +1533,14 @@ class TextImage:
INPUT_IS_LIST = False
OUTPUT_IS_LIST = (False,False,)
def run(self,text,font_path,font_size,spacing,text_color,vertical,stroke):
def run(self,text,font,font_size,spacing,padding,text_color,vertical,stroke):
# text_list=list(text)
font_path=os.path.join(FONT_PATH,font+'.ttf')
if text=="":
text=" "
# stroke=False, stroke_color=(0, 0, 0), stroke_width=1, spacing=0
img,mask=generate_text_image(text,font_path,font_size,text_color,vertical,stroke,(0, 0, 0),1,spacing)
img,mask=generate_text_image(text,font_path,font_size,text_color,vertical,stroke,(0, 0, 0),1,spacing,padding)
img=pil2tensor(img)
mask=pil2tensor(mask)
@@ -1855,10 +1773,16 @@ class CompositeImages:
"mask":("MASK",),
"background": ("IMAGE",),
},
"optional":{
"optional":{
"is_multiply_blend": ("BOOLEAN", {"default": False}),
"position": (['overall',"center_bottom","center_top","right_bottom","left_bottom","right_top","left_top"],),
"position": (['overall',"center_center","left_bottom","center_bottom","right_bottom","left_top","center_top","right_top"],),
"scale": ("FLOAT",{
"default":0,
"min": 0.01, #Minimum value
"max": 1, #Maximum value
"step": 0.01, #Slider's step
"display": "number" # Cosmetic only: display as "number" or "slider"
}),
}
}
@@ -1871,11 +1795,11 @@ class CompositeImages:
# OUTPUT_IS_LIST = (True,)
def run(self, foreground,mask,background,is_multiply_blend,position):
def run(self, foreground,mask,background,is_multiply_blend,position,scale):
foreground= tensor2pil(foreground)
mask= tensor2pil(mask)
background= tensor2pil(background)
res=composite_images(foreground,background,mask,is_multiply_blend,position)
res=composite_images(foreground,background,mask,is_multiply_blend,position,scale)
return (pil2tensor(res),)
+6 -6
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@@ -90,7 +90,7 @@ class ScreenShareNode:
} }
RETURN_TYPES = ('IMAGE','STRING','FLOAT',"INT")
RETURN_NAMES = ("IMAGE","PROMPT","FLOAT","INT")
RETURN_NAMES = ("current frame (image)","prompt","denoise (float)","seed (int)")
FUNCTION = "run"
CATEGORY = "♾️Mixlab/Screen"
@@ -109,7 +109,7 @@ class FloatingVideo:
@classmethod
def INPUT_TYPES(s):
return { "required":{
"images": ("IMAGE",)
"image": ("IMAGE",)
}, }
# RETURN_TYPES = ('IMAGE','MASK')
@@ -124,16 +124,16 @@ class FloatingVideo:
# OUTPUT_IS_LIST = (False,False,)
# 运行的函数
def run(self,images):
def run(self,image):
results = list()
for image in images:
image=tensor2pil(image)
for im in image:
im=tensor2pil(im)
# image_base64 = base64.b64encode(image.tobytes())
buffered = BytesIO()
image.save(buffered, format="JPEG")
im.save(buffered, format="JPEG")
image_base64 = base64.b64encode(buffered.getvalue()).decode("utf-8")
results.append(image_base64)
+4 -4
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@@ -566,7 +566,7 @@ class AppInfo:
},
"optional":{
"IMAGE": ("IMAGE",),
"image": ("IMAGE",),
"description":("STRING",{"multiline": True,"default": "","dynamicPrompts": False}),
"version":("INT", {
"default": 1,
@@ -594,12 +594,12 @@ class AppInfo:
INPUT_IS_LIST = True
# OUTPUT_IS_LIST = (True,)
def run(self,name,input_ids,output_ids,IMAGE,description,version,share_prefix,link,category,auto_save):
def run(self,name,input_ids,output_ids,image,description,version,share_prefix,link,category,auto_save):
name=name[0]
im=None
if IMAGE:
im=IMAGE[0][0]
if image:
im=image[0][0]
#TODO batch 的方式需要处理
im=create_temp_file(im)
# image [img,] img[batch,w,h,a] 列表里面是batch,
+2 -2
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@@ -1,9 +1,9 @@
[project]
name = "comfyui-mixlab-nodes"
description = "3D, ScreenShareNode & FloatingVideoNode, SpeechRecognition & SpeechSynthesis, GPT, LoadImagesFromLocal, Layers, Other Nodes, ..."
version = "0.28.3"
version = "0.30.1"
license = "MIT"
dependencies = ["numpy", "pyOpenSSL", "watchdog", "opencv-python-headless", "matplotlib", "openai", "simple-lama-inpainting", "clip-interrogator==0.6.0", "transformers>=4.36.0", "lark-parser", "imageio-ffmpeg", "rembg[gpu]", "omegaconf==2.3.0", "Pillow>=9.5.0", "einops==0.7.0", "trimesh>=4.0.5", "huggingface-hub", "scikit-image"]
dependencies = ["scikit-image","soundfile","numpy", "pyOpenSSL", "watchdog", "opencv-python-headless", "matplotlib", "openai", "simple-lama-inpainting", "clip-interrogator==0.6.0", "transformers>=4.36.0", "lark-parser", "imageio-ffmpeg", "rembg[gpu]", "omegaconf==2.3.0", "Pillow>=9.5.0", "einops==0.7.0", "trimesh>=4.0.5", "huggingface-hub", "scikit-image"]
[project.urls]
Repository = "https://github.com/shadowcz007/comfyui-mixlab-nodes"
+3 -2
View File
@@ -526,7 +526,7 @@ app.registerExtension({
//td bg
const tdBG = document.createElement('button')
tdBG.innerText = 'TDBG'
tdBG.innerText = 'Canvas Mode'
tdBG.style = style
tdBG.style.marginLeft = '12px'
@@ -709,6 +709,7 @@ app.registerExtension({
this.serialize_widgets = true //需要保存参数
window._mixlab_app_json = null
}
const onExecuted = nodeType.prototype.onExecuted
@@ -725,7 +726,7 @@ app.registerExtension({
const div = this.widgets.filter(w => w.div)[0].div
Array.from(div.querySelectorAll('button'), b =>
b.innerText != 'TDBG' ? (b.style.background = 'yellow') : ''
b.innerText != 'Canvas Mode' ? (b.style.background = 'yellow') : ''
)
} catch (error) {}
}
+1 -1
View File
@@ -3,7 +3,7 @@ import { app } from '../../../scripts/app.js'
const repoOwner = 'shadowcz007' // 替换为仓库的所有者
const repoName = 'comfyui-mixlab-nodes' // 替换为仓库的名称
const version = 'v0.30.0'
const version = 'v0.30.1'
fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
.then(response => response.json())
+27 -3
View File
@@ -209,13 +209,16 @@ app.registerExtension({
text = text.filter(t => t && t?.trim())
if (this.widgets) {
// console.log('#ShowTextForGPT',this.widgets)
// const pos = this.widgets.findIndex(w => w.name === 'text')
for (let i = 0; i < this.widgets.length; i++) {
if (this.widgets[i].name == 'show_text') this.widgets[i].onRemove?.()
if (this.widgets[i].name == 'show_text')
this.widgets[i].onRemove?.()
console.log('#ShowTextForGPT', this.widgets[i])
}
this.widgets.length = 1
this.widgets.length = 2
}
// console.log('ShowTextForGPT',text)
for (let list of text) {
if (list) {
// console.log('#####', list)
@@ -228,6 +231,8 @@ app.registerExtension({
w.inputEl.readOnly = true
w.inputEl.style.opacity = 0.6
// w.inputEl.style.display='none'
try {
if (typeof list != 'string') {
let data = JSON.parse(list)
@@ -280,5 +285,24 @@ app.registerExtension({
this.serialize_widgets = true //需要保存参数
}
},
async loadedGraphNode (node, app) {
if (node.type === 'ShowTextForGPT') {
let widget = node.widgets.filter(w => w.name == 'show_text')[0]
// if (widget.value) {
// let [url, prompt] = widget.value
// this[`wavesurfer_${node.id}`] = updateWaveWidgetValue(
// node.widgets,
// node.id,
// url,
// prompt,
// this[`wavesurfer_${node.id}`]
// )
// }
console.log('#loadedGraphNode', node)
}
}
})
+1 -1
View File
@@ -1267,7 +1267,7 @@ app.registerExtension({
})
widget.PictureInPicture = $el('button', {
innerText: 'PictureInPicture',
innerText: 'Picture In Picture',
style: {
display: 'pictureInPictureEnabled' in document ? 'block' : 'none',
cursor: 'pointer',