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75 Commits
Author SHA1 Message Date
shadowcz007 05857a92d5 v0.28.0
add rembg api & webapp rembg
2024-05-16 11:49:45 +08:00
shadowcz007 6bdc811286 add rembg api & webapp rembg 2024-05-16 11:49:14 +08:00
shadowcz007 469d50a5b8 Update index.html 2024-05-16 09:02:13 +08:00
shadowcz007 ef86904bfb Update ui_mixlab.js 2024-05-16 09:02:08 +08:00
shadowcz007 d4181ea67c v0.27.1 fixbug 2024-05-16 08:49:30 +08:00
shadowcz007 1c6d17309f Update index.html 2024-05-16 08:49:09 +08:00
shadowcz007 db293ec41d fixbug css 2024-05-16 08:47:17 +08:00
shadowcz007 db8d468f29 0.27.0 增加webapp的mask绘制 2024-05-16 00:11:16 +08:00
shadowcz007 d7d7af7265 add mask edit for webapp 2024-05-16 00:06:42 +08:00
shadowcz007 bd763cadc1 fixbug 2024-05-16 00:05:24 +08:00
shadowcz007 22799fc549 fixbug for mask 2024-05-16 00:05:16 +08:00
shadowcz007 0f231d1271 add minPaint for mask 2024-05-16 00:04:54 +08:00
shadowcz007 8c0c911020 Create LICENSE 2024-05-14 10:02:46 +08:00
shadowcz007 6cb9df700b 增加ComparingTwoFrames、右键image-to-text 2024-05-14 09:59:39 +08:00
shadowcz007 4fdda537b9 Update README.md 2024-05-14 09:57:51 +08:00
shadowcz007 cb6f32465a Update README.md 2024-05-14 09:55:34 +08:00
shadowcz007 c235e36cb4 Merge branch 'main' of https://github.com/shadowcz007/comfyui-mixlab-nodes 2024-05-14 09:54:27 +08:00
shadowcz007 aaca440a94 Update README.md 2024-05-14 09:54:24 +08:00
shadow 1f57950a29 Update README.md 2024-05-14 09:39:57 +08:00
shadow 3d8855ec72 Update README.md 2024-05-14 09:39:45 +08:00
shadowcz007 ac9231d9f3 Update image_mixlab.js 2024-05-13 21:43:20 +08:00
shadowcz007 37c0a56d89 add ComparingTwoFrames 2024-05-13 21:33:44 +08:00
shadowcz007 010915dac4 add help 2024-05-13 11:37:17 +08:00
shadowcz007 83a8b3b970 Update ui_mixlab.js 2024-05-13 10:58:36 +08:00
shadowcz007 f130202aa1 resizeImage 2024-05-12 22:25:08 +08:00
shadowcz007 c8f6800bcd add image-to-text :llava-phi-3-mini-gguf 2024-05-12 17:34:53 +08:00
shadowcz007 078f9f5dd4 Update ui_mixlab.js 2024-05-12 00:03:11 +08:00
shadowcz007 c0de178c7d add re_start 2024-05-11 23:58:05 +08:00
shadowcz007 1c767b538d set n_gpu_layers 2024-05-11 17:53:18 +08:00
shadowcz007 51aab44b5d Update ui_mixlab.js 2024-05-11 14:43:35 +08:00
shadowcz007 b8a0d4a67b Update ui_mixlab.js 2024-05-11 14:17:01 +08:00
shadowcz007 cd0dcfbb8c v0.25.1 2024-05-11 14:12:00 +08:00
shadow fcc9e30eae Update __init__.py 2024-05-11 12:55:14 +08:00
shadowcz007 5f66218a43 修复 sys.stdout.isatty() object has no attribute 'isatty' 2024-05-11 12:28:14 +08:00
shadowcz007 61ef4f9a0f Merge branch 'main' of https://github.com/shadowcz007/comfyui-mixlab-nodes 2024-05-11 12:13:34 +08:00
shadowcz007 f0a8734b42 修复 sys.stdout.isatty() object has no attribute 'isatty' 2024-05-11 12:13:31 +08:00
shadow 4fe95ef4ec Update README.md 2024-05-11 08:53:33 +08:00
shadowcz007 2a5148845b yaml 2024-05-10 14:38:32 +08:00
shadowcz007 8fa562caaf Update install.bat 2024-05-09 09:55:34 +08:00
shadowcz007 cab5620cd5 Update index.html 2024-05-08 23:42:48 +08:00
shadowcz007 be38d36677 Update index.html 2024-05-08 23:32:20 +08:00
shadowcz007 69236fca89 Update __init__.py 2024-05-08 22:55:42 +08:00
shadowcz007 4a4f376bfd Update __init__.py 2024-05-08 22:53:39 +08:00
shadowcz007 fd9718fe24 Update __init__.py 2024-05-08 22:50:30 +08:00
shadowcz007 26a6e11212 llama_cpp 2024-05-08 22:42:34 +08:00
shadowcz007 de1a669f6e Update README.md 2024-05-08 10:11:16 +08:00
shadowcz007 e482c9e5c4 0.25.0 text-to-text for prompt 2024-05-07 21:26:47 +08:00
shadowcz007 4e96a77a41 Update README.md 2024-05-07 21:12:27 +08:00
shadowcz007 3346290e5c Update ImageNode.py 2024-05-07 20:59:22 +08:00
shadowcz007 dcac593efe Update install.bat 2024-05-07 12:49:03 +08:00
shadowcz007 7248d0de02 update 2024-05-07 12:14:42 +08:00
shadowcz007 8ad3ce632c Update index.html 2024-05-07 00:08:35 +08:00
shadowcz007 9398b02562 Update ImageNode.py 2024-05-06 22:13:09 +08:00
shadowcz007 164e4da99d Update ImageNode.py 2024-05-05 18:04:00 +08:00
shadowcz007 0025ea6119 output defaultImage 2024-05-05 13:16:14 +08:00
shadowcz007 eef53a5165 Update ImageNode.py 2024-05-05 12:59:21 +08:00
shadowcz007 9ea066d948 composite_images add position 2024-05-05 12:20:57 +08:00
shadowcz007 4bd900c4a1 Update __init__.py 2024-05-04 09:44:01 +08:00
shadowcz007 736cd2bebd 兼容旧版comfyui 2024-05-04 09:37:25 +08:00
shadowcz007 cd658c2a60 Merge branch 'main' of https://github.com/shadowcz007/comfyui-mixlab-nodes 2024-05-03 22:08:43 +08:00
shadowcz007 9730658f21 Update __init__.py 2024-05-03 22:08:40 +08:00
shadow 3fa107acb1 Update ui_mixlab.js 2024-05-03 18:35:39 +08:00
shadowcz007 7da22179a0 text-to-text 2024-05-03 00:30:16 +08:00
shadowcz007 fc7b71ee78 Update ui_mixlab.js 2024-05-02 19:02:33 +08:00
shadowcz007 b79573bf1f Update __init__.py 2024-05-02 19:02:28 +08:00
shadowcz007 a01db6f7c0 Update README.md 2024-05-02 12:09:47 +08:00
shadowcz007 117d58c58e v0.24.0 2024-05-02 12:06:19 +08:00
shadowcz007 ff6626ed89 add llama.cpp & Local LLM -Phi-3 & llama3
Phi-3
llama3
2024-05-02 12:02:47 +08:00
shadowcz007 10c798a440 Update index.html 2024-05-02 10:54:20 +08:00
shadowcz007 9097d87819 Update index.html 2024-05-02 10:46:09 +08:00
shadowcz007 d901f503d1 fixbug 2024-05-02 10:06:23 +08:00
shadowcz007 65f2b6ce6f update https 2024-05-02 09:07:28 +08:00
shadowcz007 d949fe8bf1 Update __init__.py 2024-05-01 22:26:46 +08:00
shadowcz007 15cfb48550 Update __init__.py 2024-05-01 20:52:50 +08:00
shadowcz007 447dc6d4c3 fixbug 2024-05-01 15:55:43 +08:00
69 changed files with 4926 additions and 384 deletions
+21
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@@ -0,0 +1,21 @@
MIT License
Copyright (c) 2024 shadow
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
+98 -64
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@@ -1,9 +1,26 @@
> 适配了最新版comfyui的py3.11 ,torch 2.1.2+cu121
![](https://img.shields.io/github/release/shadowcz007/comfyui-mixlab-nodes)
> 适配了最新版 comfyui 的 py3.11 ,torch 2.1.2+cu121
> [Mixlab nodes discord](https://discord.gg/cXs9vZSqeK)
####
[comfyui-sd-prompt-mixlab](https://github.com/shadowcz007/comfyui-sd-prompt-mixlab)
##### `最新`:
ChatGPT 节点支持 Local LLM(llama.cpp),Phi3、llama3 都可以直接一个节点运行了。模型下载后,放置到 `models/llamafile/`
- 右键菜单支持 text-to-text,方便对 prompt 词补全
强烈推荐:[Phi-3-mini-4k-instruct-GGUF](https://huggingface.co/lmstudio-community/Phi-3-mini-4k-instruct-GGUF/tree/main),备选:[llama3_if_ai_sdpromptmkr_q2k](https://hf-mirror.com/impactframes/llama3_if_ai_sdpromptmkr_q2k/tree/main)
- 右键菜单支持 image-to-text,使用多模态模型,多模态使用 [llava-phi-3-mini-gguf](https://huggingface.co/xtuner/llava-phi-3-mini-gguf/tree/main),注意需要把llava-phi-3-mini-mmproj-f16.gguf也下载
![](./assets/prompt_ai_setup.png)
![](./assets/prompt-ai.png)
#### `相关插件推荐`
<!-- [comfyui-sd-prompt-mixlab](https://github.com/shadowcz007/comfyui-sd-prompt-mixlab) -->
[comfyui-Image-reward](https://github.com/shadowcz007/comfyui-Image-reward)
@@ -13,12 +30,12 @@
<!-- [comfyui-CLIPSeg](https://github.com/shadowcz007/comfyui-CLIPSeg) -->
## 🚀🚗🚚🏃 Workflow-to-APP
## 🚀🚗🚚🏃 Workflow-to-APP
- 新增AppInfo节点,可以通过简单的配置,把workflow转变为一个Web APP。
- 支持多个web app 切换
- 发布为app的workflow,可以在右键里再次编辑了
- web app可以设置分类,在comfyui右键菜单可以编辑更新web app
- 新增 AppInfo 节点,可以通过简单的配置,把 workflow 转变为一个 Web APP。
- 支持多个 web app 切换
- 发布为 app 的 workflow,可以在右键里再次编辑了
- web app 可以设置分类,在 comfyui 右键菜单可以编辑更新 web app
- 支持动态提示
![](./assets/微信图片_20240421205440.png)
@@ -28,7 +45,6 @@
- The workflow, which is now released as an app, can also be edited again by right-clicking.
- The web app can be configured with categories, and the web app can be edited and updated in the right-click menu of ComfyUI.
![](./assets/0-m-app.png)
![](./assets/appinfo-readme.png)
@@ -36,59 +52,91 @@
![](./assets/appinfo-2.png)
Example:
- workflow
![APP info](./workflow/appinfo-workflow.svg)
[text-to-image](./workflow/Text-to-Image-app.json)
![APP info](./workflow/appinfo-workflow.svg)
[text-to-image](./workflow/Text-to-Image-app.json)
APP-JSON:
- [text-to-image](./example/Text-to-Image_3.json)
- [image-to-image](./example/Image-to-Image_2.json)
- text-to-text
> 暂时支持 9 种节点作为界面上的输入节点:Load Image、VHS_LoadVideo、CLIPTextEncode、PromptSlide、TextInput_、Color、FloatSlider、IntNumber、CheckpointLoaderSimple、LoraLoader
> 暂时支持 9 种节点作为界面上的输入节点:Load Image、VHS*LoadVideo、CLIPTextEncode、PromptSlide、TextInput*、Color、FloatSlider、IntNumber、CheckpointLoaderSimple、LoraLoader
> 输出节点:PreviewImage 、SaveImage、ShowTextForGPT、VHS_VideoCombine、PromptImage
> seed统一输入控件,支持:SamplerCustom、KSampler
> seed 统一输入控件,支持:SamplerCustom、KSampler
> 配套[ps插件](https://github.com/shadowcz007/comfyui-ps-plugin)
> 配套[ps 插件](https://github.com/shadowcz007/comfyui-ps-plugin)
> 如果遇到上传图片不成功,请检查下:局域网或者是云服务,请使用https,端口8189这个服务( 感谢 @Damien 反馈问题)
> 如果遇到上传图片不成功,请检查下:局域网或者是云服务,请使用 https,端口 8189 这个服务( 感谢 @Damien 反馈问题)
> If you encounter difficulties in uploading images, please check the following: for local network or cloud services, please use HTTPS and the service on port 8189. (Thanks to @Damien for reporting the issue.)
## 🏃🚗🚚🚀 Real-time Design
## 🏃🚗🚚🚀 Real-time Design
> ScreenShareNode & FloatingVideoNode. Now comfyui supports capturing screen pixel streams from any software and can be used for LCM-Lora integration. Let's get started with implementation and design! 💻🌐
![screenshare](./assets/screenshare.png)
https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43e-410a-ab3a-1952b7b4e7da
<!-- [ScreenShareNode](./workflow/2-screeshare.json) -->
[ScreenShareNode & FloatingVideoNode](./workflow/3-FloatVideo-workflow.json)
!! Please use the address with HTTPS (https://127.0.0.1).
### SpeechRecognition & SpeechSynthesis
![f](./assets/audio-workflow.svg)
[Voice + Real-time Face Swap Workflow](./workflow/语音+实时换脸workflow.json)
### GPT
> Support for calling multiple GPTs.ChatGPT、ChatGLM3 、ChatGLM4 , 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.Local LLM(llama.cpp)、 ChatGPT、ChatGLM3 、ChatGLM4 , Some code provided by rui. If you are using OpenAI's service, fill in https://api.openai.com/v1 . If you are using a local LLM service, fill in http://127.0.0.1:xxxx/v1 . Azure OpenAI:https://xxxx.openai.azure.com
![gpt-workflow.svg](./assets/gpt-workflow.svg)
[workflow-5](./workflow/5-gpt-workflow.json)
最新:ChatGPT 节点支持 Local LLM(llama.cpp),Phi3、llama3 都可以直接一个节点运行了。
Model download,move to :`models/llamafile/`
强烈推荐:[Phi-3-mini-4k-instruct-GGUF](https://huggingface.co/lmstudio-community/Phi-3-mini-4k-instruct-GGUF/tree/main)
备选:[llama3_if_ai_sdpromptmkr_q2k](https://hf-mirror.com/impactframes/llama3_if_ai_sdpromptmkr_q2k/tree/main)
> 如果碰到安装失败,可以尝试手动安装
```
../../../python_embeded/python.exe -s -m pip install llama-cpp-python --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu121
../../../python_embeded/python.exe -s -m pip install llama-cpp-python[server]
```
> [Mac](https://llama-cpp-python.readthedocs.io/en/latest/install/macos/)
```
pip uninstall llama-cpp-python -y
CMAKE_ARGS="-DLLAMA_METAL=on" pip install -U llama-cpp-python --no-cache-dir
pip install 'llama-cpp-python[server]'
```
```
pip install llama-cpp-python \
--extra-index-url https://abetlen.github.io/llama-cpp-python/whl/metal
```
## Prompt
> PromptSlide
![](./assets/prompt_weight.png)
> ![](./assets/prompt_weight.png)
<!-- ![](./workflow/promptslide-appinfo-workflow.svg) -->
@@ -102,20 +150,20 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
> PromptImage & PromptSimplification,Assist in simplifying prompt words, comparing images and prompt word nodes.
> ChinesePrompt && PromptGenerate,中文prompt节点,直接用中文书写你的prompt
> ChinesePrompt && PromptGenerate,中文 prompt 节点,直接用中文书写你的 prompt
![](./assets/ChinesePrompt_workflow.svg)
### 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.
![layers](./assets/layers-workflow.svg)
![poster](./assets/poster-workflow.svg)
### 3D
![](./assets/3d-workflow.png)
![](./assets/3d_app.png)
[workflow](./assets/Image-to-3D_1.json)
@@ -123,44 +171,44 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
![](./assets/3dimage.png)
[workflow](./workflow/3D-workflow.json)
### Image
#### LoadImagesToBatch
> Upload multiple images for batch input into the IP adapter.
> Upload multiple images for batch input into the IP adapter.
#### LoadImagesFromLocal
> Monitor changes to images in a local folder, and trigger real-time execution of workflows, supporting common image formats, especially PSD format, in conjunction with Photoshop.
> Monitor changes to images in a local folder, and trigger real-time execution of workflows, supporting common image formats, especially PSD format, in conjunction with Photoshop.
![watch](./assets/4-loadfromlocal-watcher-workflow.svg)
[workflow-4](./workflow/4-loadfromlocal-watcher-workflow.json)
#### LoadImagesFromURL
> Conveniently load images from a fixed address on the internet to ensure that default images in the workflow can be executed.
### Style
> Apply VisualStyle Prompting , Modified from [ComfyUI_VisualStylePrompting](https://github.com/ExponentialML/ComfyUI_VisualStylePrompting)
> Apply VisualStyle Prompting , Modified from [ComfyUI_VisualStylePrompting](https://github.com/ExponentialML/ComfyUI_VisualStylePrompting)
![](./assets/VisualStylePrompting.png)
> StyleAligned , Modified from [style_aligned_comfy](https://github.com/brianfitzgerald/style_aligned_comfy)
> StyleAligned , Modified from [style_aligned_comfy](https://github.com/brianfitzgerald/style_aligned_comfy)
### Utils
> The Color node provides a color picker for easy color selection, the Font node offers built-in font selection for use with TextImage to generate text images, and the DynamicDelayByText node allows delayed execution based on the length of the input text.
- [添加了DynamicDelayByText功能,可以根据输入文本的长度进行延迟执行。](./workflow/audio-chatgpt-workflow.json)
- [添加了 DynamicDelayByText 功能,可以根据输入文本的长度进行延迟执行。](./workflow/audio-chatgpt-workflow.json)
- [Added DynamicDelayByText, enabling delayed execution based on input text length.](./workflow/audio-chatgpt-workflow.json)
- [使用CkptNames 对比不同的模型效果](./workflow/ckpts-image-workflow.json)
- [使用 CkptNames 对比不同的模型效果](./workflow/ckpts-image-workflow.json)
- [CkptNames compare the effects of different models.](./workflow/ckpts-image-workflow.json)
### Other Nodes
![main](./assets/all-workflow.svg)
@@ -168,33 +216,27 @@ https://github.com/shadowcz007/comfyui-mixlab-nodes/assets/12645064/e7e77f90-e43
[workflow-1](./workflow/1-workflow.json)
> TransparentImage
![TransparentImage](./assets/TransparentImage.png)
> FeatheredMask、SmoothMask
Add edges to an image.
![FeatheredMask](./assets/FlVou_Y6kaGWYoEj1Tn0aTd4AjMI.jpg)
> LaMaInpainting
from [simple-lama-inpainting](https://github.com/enesmsahin/simple-lama-inpainting)
> rembgNode
"briarmbg","u2net","u2netp","u2net_human_seg","u2net_cloth_seg","silueta","isnet-general-use","isnet-anime"
*** briarmbg *** model was developed by BRlA Al and can be used as an open-source model for non-commercial purposes
**_ briarmbg _** model was developed by BRlA Al and can be used as an open-source model for non-commercial purposes
### Improvement
### Improvement
- Add "help" option to the context menu for each node.
- Add "Nodes Map" option to the global context menu.
@@ -205,23 +247,21 @@ An improvement has been made to directly redirect to GitHub to search for missin
![node-not-found](./assets/node-not-found.png)
### Models
* [Download TripoSR](https://huggingface.co/stabilityai/TripoSR/blob/main/model.ckpt) and place it in ```models/triposr```
- [Download TripoSR](https://huggingface.co/stabilityai/TripoSR/blob/main/model.ckpt) and place it in `models/triposr`
* [Download facebook/dino-vitb16](https://huggingface.co/facebook/dino-vitb16/tree/main) and place it in ```models/triposr/facebook/dino-vitb16```
- [Download facebook/dino-vitb16](https://huggingface.co/facebook/dino-vitb16/tree/main) and place it in `models/triposr/facebook/dino-vitb16`
[Download rembg Models](https://github.com/danielgatis/rembg/tree/main#Models),move to:`models/rembg`
[Download rembg Models](https://github.com/danielgatis/rembg/tree/main#Models),move to:```models/rembg```
[Download lama](https://github.com/enesmsahin/simple-lama-inpainting/releases/download/v0.1.0/big-lama.pt), move to : `models/lama`
[Download lama](https://github.com/enesmsahin/simple-lama-inpainting/releases/download/v0.1.0/big-lama.pt), move to : ```models/lama```
[Download Salesforce/blip-image-captioning-base](https://huggingface.co/Salesforce/blip-image-captioning-base), move to :`models/clip_interrogator/Salesforce/blip-image-captioning-base`
[Download Salesforce/blip-image-captioning-base](https://huggingface.co/Salesforce/blip-image-captioning-base), move to :```models/clip_interrogator/Salesforce/blip-image-captioning-base```
[Download succinctly/text2image-prompt-generator](https://huggingface.co/succinctly/text2image-prompt-generator/tree/main),move to:`models/prompt_generator/text2image-prompt-generator`
[Download succinctly/text2image-prompt-generator](https://huggingface.co/succinctly/text2image-prompt-generator/tree/main),move to:```models/prompt_generator/text2image-prompt-generator```
[Download Helsinki-NLP/opus-mt-zh-en](https://huggingface.co/Helsinki-NLP/opus-mt-zh-en/tree/main),move to:```models/prompt_generator/opus-mt-zh-en```
[Download Helsinki-NLP/opus-mt-zh-en](https://huggingface.co/Helsinki-NLP/opus-mt-zh-en/tree/main),move to:`models/prompt_generator/opus-mt-zh-en`
## Installation
@@ -237,40 +277,35 @@ 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
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
####
####
File / LoadImagesFromPath SaveImageToLocal LoadImagesFromURL
#### discussions:
[discussions](https://github.com/shadowcz007/comfyui-mixlab-nodes/discussions)
[discussions](https://github.com/shadowcz007/comfyui-mixlab-nodes/discussions)
<picture>
<source
@@ -290,4 +325,3 @@ File / LoadImagesFromPath SaveImageToLocal LoadImagesFromURL
src="https://api.star-history.com/svg?repos=shadowcz007/comfyui-mixlab-nodes&type=Date"
/>
</picture>
+298 -44
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@@ -7,9 +7,32 @@ import urllib
import hashlib
import datetime
import folder_paths
import logging
import base64,io,re
from PIL import Image
from comfy.cli_args import args
python = sys.executable
#修复 sys.stdout.isatty() object has no attribute 'isatty'
try:
sys.stdout.isatty()
except:
print('#fix sys.stdout.isatty')
sys.stdout.isatty = lambda: False
llama_port=None
llama_model=""
llama_chat_format=""
try:
from .nodes.ChatGPT import get_llama_models,get_llama_model_path,llama_cpp_client
llama_cpp_client("")
except:
print("##nodes.ChatGPT ImportError")
from .nodes.RembgNode import get_rembg_models,U2NET_HOME,run_briarmbg,run_rembg
from server import PromptServer
@@ -42,7 +65,7 @@ def is_installed(package, package_overwrite=None):
print(f"Couldn't install\nCommand: {command}\nError code: {result.returncode}")
else:
print(package+'## OK')
try:
import OpenSSL
except ImportError:
@@ -79,6 +102,26 @@ install_openai()
current_path = os.path.abspath(os.path.dirname(__file__))
def remove_base64_prefix(base64_str):
"""
去除 base64 字符串中的 data:image/*;base64, 前缀
Args:
base64_str: base64 编码的字符串
Returns:
去除前缀后的 base64 字符串
"""
# 使用正则表达式匹配常见的前缀
pattern = r'^data:image\/(.*);base64,(.+)$'
match = re.match(pattern, base64_str)
if match:
# 如果匹配到常见的前缀,则去除前缀并返回
return match.group(2)
else:
# 如果不匹配到常见的前缀,则直接返回
return base64_str
def calculate_md5(string):
encoded_string = string.encode()
@@ -414,37 +457,86 @@ async def new_start(self, address, port, verbose=True, call_on_start=None):
runner = web.AppRunner(self.app, access_log=None)
await runner.setup()
if not await check_port_available(address, port):
raise RuntimeError(f"Port {port} is already in use.")
# if not await check_port_available(address, port):
# raise RuntimeError(f"Port {port} is already in use.")
http_success = False
http_port=port
for i in range(11): # 尝试最多11次
if await check_port_available(address, port + i):
http_port = port + i
site = web.TCPSite(runner, address, http_port)
await site.start()
http_success = True
break
site = web.TCPSite(runner, address, port)
await site.start()
if not http_success:
raise RuntimeError(f"Ports {port} to {port + 10} are all in use.")
# site = web.TCPSite(runner, address, port)
# await site.start()
ssl_context = None
scheme = "http"
try:
# 跟着本体修改
if args.tls_keyfile and args.tls_certfile:
scheme = "https"
ssl_context = ssl.SSLContext(protocol=ssl.PROTOCOL_TLS_SERVER, verify_mode=ssl.CERT_NONE)
ssl_context.load_cert_chain(certfile=args.tls_certfile,
keyfile=args.tls_keyfile)
else:
# 如果没传,则自动创建
import ssl
crt, key = create_for_https()
ssl_context = ssl.create_default_context(ssl.Purpose.CLIENT_AUTH)
ssl_context.load_cert_chain(crt, key)
except:
import ssl
crt, key = create_for_https()
ssl_context = ssl.create_default_context(ssl.Purpose.CLIENT_AUTH)
ssl_context.load_cert_chain(crt, key)
import ssl
crt, key = create_for_https()
ssl_context = ssl.create_default_context(ssl.Purpose.CLIENT_AUTH)
ssl_context.load_cert_chain(crt, key)
success = False
for i in range(10): # 尝试最多10次
if await check_port_available(address, port + 1 + i):
https_port = port + 1 + i
for i in range(11): # 尝试最多11次
if await check_port_available(address, http_port + 1 + i):
https_port = http_port + 1 + i
site2 = web.TCPSite(runner, address, https_port, ssl_context=ssl_context)
await site2.start()
success = True
break
if not success:
raise RuntimeError(f"Ports {port + 1} to {port + 10} are all in use.")
raise RuntimeError(f"Ports {http_port + 1} to {http_port + 10} are all in use.")
if address == '':
address = '0.0.0.0'
address = '127.0.0.1'
if address=='0.0.0.0':
address = '127.0.0.1'
if verbose:
print("\033[93mStarting server\n")
print("\033[93mTo see the GUI go to: http://{}:{}".format(address, port))
print("\033[93mTo see the GUI go to: https://{}:{}\033[0m".format(address, https_port))
logging.info("\n")
logging.info("\n\nStarting server")
# print("\033[93mStarting server\n")
logging.info("\033[93mTo see the GUI go to: http://{}:{}".format(address, http_port))
logging.info("\033[93mTo see the GUI go to: https://{}:{}\033[0m".format(address, https_port))
# print("\033[93mTo see the GUI go to: http://{}:{}".format(address, http_port))
# print("\033[93mTo see the GUI go to: https://{}:{}\033[0m".format(address, https_port))
if call_on_start is not None:
call_on_start(address, port)
try:
if scheme=='https':
call_on_start(scheme,address, https_port)
else:
call_on_start(scheme,address, http_port)
except:
call_on_start(address,http_port)
except Exception as e:
print(f"Error starting the server: {e}")
@@ -455,7 +547,6 @@ async def new_start(self, address, port, verbose=True, call_on_start=None):
# webbrowser.open(f"https://{address}")
# webbrowser.open(f"http://{address}:{port}")
PromptServer.start=new_start
# 创建路由表
@@ -550,16 +641,65 @@ async def nodes_map_hander(request):
async def get_checkpoints(request):
data = await request.json()
t="checkpoints"
names=[]
try:
t=data['type']
names = folder_paths.get_filename_list(t)
except Exception as e:
print('/mixlab/folder_paths',False,e)
names = folder_paths.get_filename_list(t)
try:
if data['type']=='llamafile':
names=get_llama_models()
except:
print("llamafile none")
try:
if data['type']=='rembg':
names=get_rembg_models(U2NET_HOME)
except:
print("rembg none")
return web.json_response({"names":names,"types":list(folder_paths.folder_names_and_paths.keys())})
@routes.post('/mixlab/rembg')
async def rembg_hander(request):
data = await request.json()
model=data['model']
result={}
data_base64=remove_base64_prefix(data['base64'])
image_data = base64.b64decode(data_base64)
# 创建一个BytesIO对象
image_stream = io.BytesIO(image_data)
# 使用PIL Image模块读取图像
image = Image.open(image_stream)
if model=='briarmbg':
_,rgba_images,_=run_briarmbg([image])
else:
_,rgba_images,_=run_rembg(model,[image])
with io.BytesIO() as buf:
rgba_images[0].save(buf, format='PNG')
img_bytes = buf.getvalue()
img_base64 = base64.b64encode(img_bytes).decode('utf-8')
try:
result={
'data':img_base64,
'model':model,
'status':'success',
}
except Exception as e:
print(e)
return web.json_response(result)
@routes.post("/mixlab/prompt_result")
async def post_prompt_result(request):
data = await request.json()
@@ -577,20 +717,130 @@ async def post_prompt_result(request):
return web.json_response({"result":res})
# 扩展api接口
# from server import PromptServer
# from aiohttp import web
# @routes.post('/ws_image')
# async def my_hander_method(request):
# post = await request.post()
# x = post.get("something")
# return web.json_response({})
async def start_local_llm(data):
global llama_port,llama_model,llama_chat_format
if llama_port and llama_model and llama_chat_format:
return {"port":llama_port,"model":llama_model,"chat_format":llama_chat_format}
import threading
import uvicorn
from llama_cpp.server.app import create_app
from llama_cpp.server.settings import (
Settings,
ServerSettings,
ModelSettings,
ConfigFileSettings,
)
if not "model" in data and "model_path" in data:
data['model']= os.path.basename(data["model_path"])
model=data["model_path"]
elif "model" in data:
model=get_llama_model_path(data['model'])
n_gpu_layers=-1
if "n_gpu_layers" in data:
n_gpu_layers=data['n_gpu_layers']
chat_format="chatml"
model_alias=os.path.basename(model)
# 多模态
clip_model_path=None
prefix = "llava-phi-3-mini"
file_name = prefix+"-mmproj-"
if model_alias.startswith(prefix):
for file in os.listdir(os.path.dirname(model)):
if file.startswith(file_name):
clip_model_path=os.path.join(os.path.dirname(model),file)
chat_format='llava-1-5'
print('#clip_model_path',chat_format,clip_model_path)
address="127.0.0.1"
port=9090
success = False
for i in range(11): # 尝试最多11次
if await check_port_available(address, port + i):
port = port + i
success = True
break
if success == False:
return {"port":None,"model":""}
server_settings=ServerSettings(host=address,port=port)
app = create_app(
server_settings=server_settings,
model_settings=[
ModelSettings(
model=model,
model_alias=os.path.basename(model),
n_gpu_layers=n_gpu_layers,
n_ctx=4098,
chat_format=chat_format,
embedding=False,
clip_model_path=clip_model_path
)])
def run_uvicorn():
uvicorn.run(
app,
host=os.getenv("HOST", server_settings.host),
port=int(os.getenv("PORT", server_settings.port)),
ssl_keyfile=server_settings.ssl_keyfile,
ssl_certfile=server_settings.ssl_certfile,
)
# 创建一个子线程
thread = threading.Thread(target=run_uvicorn)
# 启动子线程
thread.start()
llama_port=port
llama_model=data['model']
llama_chat_format=chat_format
return {"port":llama_port,"model":llama_model,"chat_format":llama_chat_format}
# llam服务的开启
@routes.post('/mixlab/start_llama')
async def my_hander_method(request):
data =await request.json()
# print(data)
try:
result=await start_local_llm(data)
except:
result={
{"port":None,"model":"","llama_cpp_error":True}
}
print('start_local_llm error')
return web.json_response(result)
# 重启服务
@routes.post('/mixlab/re_start')
def re_start(request):
try:
sys.stdout.close_log()
except Exception as e:
pass
return os.execv(sys.executable, [sys.executable] + sys.argv)
# 导入节点
from .nodes.PromptNode import GLIGENTextBoxApply_Advanced,EmbeddingPrompt,RandomPrompt,PromptSlide,PromptSimplification,PromptImage,JoinWithDelimiter
from .nodes.ImageNode import LoadImages_,CompositeImages,GridDisplayAndSave,GridInput,ImagesPrompt,SaveImageAndMetadata,SaveImageToLocal,SplitImage,GridOutput,GetImageSize_,MirroredImage,ImageColorTransfer,NoiseImage,TransparentImage,GradientImage,LoadImagesFromPath,LoadImagesFromURL,ResizeImage,TextImage,SvgImage,Image3D,ShowLayer,NewLayer,MergeLayers,CenterImage,AreaToMask,SmoothMask,SplitLongMask,ImageCropByAlpha,EnhanceImage,FaceToMask
from .nodes.ImageNode import ComparingTwoFrames,LoadImages_,CompositeImages,GridDisplayAndSave,GridInput,ImagesPrompt,SaveImageAndMetadata,SaveImageToLocal,SplitImage,GridOutput,GetImageSize_,MirroredImage,ImageColorTransfer,NoiseImage,TransparentImage,GradientImage,LoadImagesFromPath,LoadImagesFromURL,ResizeImage,TextImage,SvgImage,Image3D,ShowLayer,NewLayer,MergeLayers,CenterImage,AreaToMask,SmoothMask,SplitLongMask,ImageCropByAlpha,EnhanceImage,FaceToMask
# from .nodes.Vae import VAELoader,VAEDecode
from .nodes.ScreenShareNode import ScreenShareNode,FloatingVideo
@@ -651,6 +901,7 @@ NODE_CLASS_MAPPINGS = {
# "VAELoaderConsistencyDecoder":VAELoader,
"SaveImageToLocal":SaveImageToLocal,
"SaveImageAndMetadata_":SaveImageAndMetadata,
"ComparingTwoFrames_":ComparingTwoFrames,
# "VAEDecodeConsistencyDecoder":VAEDecode,
"ScreenShare":ScreenShareNode,
"FloatingVideo":FloatingVideo,
@@ -705,6 +956,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"IntNumber":"Int Input ♾️MixlabApp",
"ImagesPrompt_":"Images Input ♾️MixlabApp",
"SaveImageAndMetadata_":"Save Image Output ♾️MixlabApp",
"ComparingTwoFrames_":"Comparing Two Frames ♾️MixlabApp",
"ResizeImageMixlab":"Resize Image ♾️Mixlab",
"RandomPrompt": "Random Prompt ♾️Mixlab",
"PromptImage":"Output Prompt and Image ♾️Mixlab",
@@ -713,7 +965,7 @@ NODE_DISPLAY_NAME_MAPPINGS = {
"VAEDecodeConsistencyDecoder":"Consistency Decoder Decode",
"ScreenShare":"Screen Share ♾️Mixlab",
"FloatingVideo":"FloatingVideo ♾️Mixlab",
"ChatGPTOpenAI":"ChatGPT ♾️Mixlab",
"ChatGPTOpenAI":"ChatGPT & Local LLM ♾️Mixlab",
"ShowTextForGPT":"Show Text ♾️MixlabApp",
"MergeLayers":"Merge Layers ♾️Mixlab",
"SpeechSynthesis":"SpeechSynthesis ♾️Mixlab",
@@ -756,42 +1008,44 @@ NODE_DISPLAY_NAME_MAPPINGS = {
# web ui的节点功能
WEB_DIRECTORY = "./web"
print('--------------')
print('\033[91m ### Mixlab Nodes: \033[93mLoaded')
logging.info('--------------')
logging.info('\033[91m ### Mixlab Nodes: \033[93mLoaded')
# print('\033[91m ### Mixlab Nodes: \033[93mLoaded')
try:
from .nodes.Lama import LaMaInpainting
print('LaMaInpainting.available',LaMaInpainting.available)
logging.info('LaMaInpainting.available {}'.format(LaMaInpainting.available))
if LaMaInpainting.available:
NODE_CLASS_MAPPINGS['LaMaInpainting']=LaMaInpainting
except Exception as e:
print('LaMaInpainting.available',False,e)
logging.info('LaMaInpainting.available False')
try:
from .nodes.ClipInterrogator import ClipInterrogator
print('ClipInterrogator.available',ClipInterrogator.available)
logging.info('ClipInterrogator.available {}'.format(ClipInterrogator.available))
if ClipInterrogator.available:
NODE_CLASS_MAPPINGS['ClipInterrogator']=ClipInterrogator
except Exception as e:
print('ClipInterrogator.available',False,e)
logging.info('ClipInterrogator.available False')
try:
from .nodes.TextGenerateNode import PromptGenerate,ChinesePrompt
print('PromptGenerate.available',PromptGenerate.available)
logging.info('PromptGenerate.available {}'.format(PromptGenerate.available))
if PromptGenerate.available:
NODE_CLASS_MAPPINGS['PromptGenerate_Mix']=PromptGenerate
print('ChinesePrompt.available',ChinesePrompt.available)
logging.info('ChinesePrompt.available {}'.format(ChinesePrompt.available))
if ChinesePrompt.available:
NODE_CLASS_MAPPINGS['ChinesePrompt_Mix']=ChinesePrompt
except Exception as e:
print('TextGenerateNode.available',False,e)
logging.info('TextGenerateNode.available False')
try:
from .nodes.RembgNode import RembgNode_
print('RembgNode_.available',RembgNode_.available)
logging.info('RembgNode_.available {}'.format(RembgNode_.available))
if RembgNode_.available:
NODE_CLASS_MAPPINGS['RembgNode_Mix']=RembgNode_
except Exception as e:
print('RembgNode_.available',False,e)
logging.info('RembgNode_.available False' )
print('\033[93m -------------- \033[0m')
logging.info('\033[93m -------------- \033[0m')
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@@ -10,6 +10,12 @@ if exist "%python_exec%" (
for /f "delims=" %%i in (%requirements_txt%) do (
%python_exec% -s -m pip install "%%i" -i https://pypi.tuna.tsinghua.edu.cn/simple
)
%python_exec% -s -m pip install --upgrade --force llama-cpp-python --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cu121
%python_exec% -s -m pip install --upgrade --force llama-cpp-python[server]
) else (
echo Installing with system Python
for /f "delims=" %%i in (%requirements_txt%) do (
+109 -17
View File
@@ -87,16 +87,102 @@ def ZhipuAI_client(key):
return client
# 优先使用phi
def phi_sort(lst):
return sorted(lst, key=lambda x: x.lower().count('phi'), reverse=True)
def get_llama_path():
try:
return folder_paths.get_folder_paths('llamafile')[0]
except:
return os.path.join(folder_paths.models_dir, "llamafile")
def get_llama_models():
res=[]
model_path=get_llama_path()
if os.path.exists(model_path):
files = os.listdir(model_path)
for file in files:
if os.path.isfile(os.path.join(model_path, file)):
res.append(file)
res=phi_sort(res)
return res
llama_modes_list=get_llama_models()
def get_llama_model_path(file_name):
model_path=get_llama_path()
mp=os.path.join(model_path,file_name)
return mp
def llama_cpp_client(file_name):
try:
if is_installed('llama_cpp')==False:
import subprocess
# 安装
print('#pip install llama-cpp-python')
result = subprocess.run([sys.executable, '-s', '-m', 'pip',
'install',
'llama-cpp-python',
'--extra-index-url',
'https://abetlen.github.io/llama-cpp-python/whl/cu121'
], capture_output=True, text=True)
#检查命令执行结果
if result.returncode == 0:
print("#install success")
from llama_cpp import Llama
subprocess.run([sys.executable, '-s', '-m', 'pip',
'install',
'llama-cpp-python[server]'
], capture_output=True, text=True)
else:
print("#install error")
else:
from llama_cpp import Llama
except:
print("#install llama-cpp-python error")
if file_name:
mp=get_llama_model_path(file_name)
# file_name=get_llama_models()[0]
# model_path=os.path.join(folder_paths.models_dir, "llamafile")
# mp=os.path.join(model_path,file_name)
llm = Llama(model_path=mp, chat_format="chatml",n_gpu_layers=-1,n_ctx=512)
return llm
def chat(client, model_name,messages ):
try_count = 0
while True:
try_count += 1
try:
response = client.chat.completions.create(
model=model_name,
messages=messages
)
if hasattr(client, "chat"):
response = client.chat.completions.create(
model=model_name,
messages=messages
)
else:
# 是llama的
response = client.create_chat_completion_openai_v1(
messages=messages,
# response_format={
# "type": "json_object",
# },
# temperature=0.7,
)
break
except openai.AuthenticationError as ex:
raise ex
@@ -105,7 +191,8 @@ def chat(client, model_name,messages ):
raise ex
time.sleep(3)
continue
# print(response.keys())
finish_reason = response.choices[0].finish_reason
if finish_reason != "stop":
raise RuntimeError("API finished with unexpected reason: " + finish_reason)
@@ -128,6 +215,16 @@ class ChatGPTNode:
@classmethod
def INPUT_TYPES(cls):
model_list=llama_modes_list+[
"gpt-3.5-turbo",
"gpt-3.5-turbo-0125",
"gpt-35-turbo",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-4-0613",
"gpt-4-1106-preview",
"glm-4"
]
return {
"required": {
"api_key":("KEY", {"default": "", "multiline": True,"dynamicPrompts": False}),
@@ -138,16 +235,8 @@ class ChatGPTNode:
"default": "You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.",
"multiline": True,"dynamicPrompts": False
}),
"model": ([
"gpt-3.5-turbo",
"gpt-3.5-turbo-0125",
"gpt-35-turbo",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-16k-0613",
"gpt-4-0613",
"gpt-4-1106-preview",
"glm-4"],
{"default": "gpt-3.5-turbo"}),
"model": ( model_list,
{"default": model_list[0]}),
"seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "step": 1}),
"context_size":("INT", {"default": 1, "min": 0, "max":30, "step": 1}),
},
@@ -170,8 +259,8 @@ class ChatGPTNode:
api_url,
prompt,
system_content,
model,
seed,context_size,unique_id = None, extra_pnginfo=None):
model,
seed,context_size,unique_id = None, extra_pnginfo=None):
# print(api_key!='',api_url,prompt,system_content,model,seed)
# 可以选择保留会话历史以维持上下文记忆
# 或者在此处清除会话历史 self.session_history.clear()
@@ -193,6 +282,9 @@ class ChatGPTNode:
if model == "glm-4" :
client = ZhipuAI_client(api_key) # 使用 Zhipuai 的接口
print('using Zhipuai interface')
elif model in llama_modes_list:
#
client=llama_cpp_client(model)
else :
client = openai_client(api_key,api_url) # 使用 ChatGPT 的接口
print('using ChatGPT interface')
+9 -3
View File
@@ -70,14 +70,20 @@ def load_caption_model(model_path,config,t='blip-base'):
return (caption_model,caption_processor)
def get_clip_interrogator_path():
try:
return folder_paths.get_folder_paths('clip_interrogator')[0]
except:
return os.path.join(folder_paths.models_dir, "clip_interrogator")
caption_model_path=os.path.join(folder_paths.models_dir, "clip_interrogator/Salesforce/blip-image-captioning-base")
cache_path=get_clip_interrogator_path()
caption_model_path=os.path.join(cache_path, "Salesforce/blip-image-captioning-base")
if not os.path.exists(caption_model_path):
print(f"## clip_interrogator_model not found: {caption_model_path}, pls download from https://huggingface.co/Salesforce/blip-image-captioning-base")
caption_model_path='Salesforce/blip-image-captioning-base'
cache_path=os.path.join(folder_paths.models_dir, "clip_interrogator")
# Tensor to PIL
def tensor2pil(image):
View File
+248 -37
View File
@@ -29,23 +29,122 @@ def opencv_to_pil(image):
return pil_image
def composite_images(foreground, background, mask):
def composite_images(foreground, background, mask,is_multiply_blend=False,position="overall"):
width,height=foreground.size
bg_image=background
bwidth,bheight=bg_image.size
# 按z-index排序
layer = {
"x":0,
"y":0,
"width":width,
"height":height,
"z_index":88,
"scale_option":'overall',
"image":foreground,
"mask":mask
}
if position=="overall":
layer = {
"x":0,
"y":0,
"width":bwidth,
"height":bheight,
"z_index":88,
"scale_option":'overall',
"image":foreground,
"mask":mask
}
elif position=='center_bottom':
scale = int(bwidth*0.25) / width
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)
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
}
elif position=='center_top':
scale = int(bwidth*0.25) / width
new_height = int(height * scale)
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
}
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
# width, height = bg_image.size
layer_image=layer['image']
layer_mask=layer['mask']
@@ -53,12 +152,12 @@ def composite_images(foreground, background, mask):
bg_image=merge_images(bg_image,
layer_image,
layer_mask,
layer['x'],
layer['y'],
layer['width'],
layer['height'],
layer['scale_option']
)
layer['x'],
layer['y'],
layer['width'],
layer['height'],
layer['scale_option'],
is_multiply_blend )
bg_image=bg_image.convert('RGB')
@@ -704,7 +803,6 @@ def multiply_blend(image1, image2):
# cv2.imwrite('result.jpg', result)
def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option,is_multiply_blend=False):
# 打开底图
bg_image = bg_image.convert("RGBA")
@@ -730,21 +828,42 @@ def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option,
# 整体缩放
layer_image = layer_image.resize((width, height))
elif scale_option == "longest":
original_width, original_height = layer_image.size
if original_width > original_height:
new_width=width
scale = width / original_width
new_height = int(original_height * scale)
x=0
y=int((height-new_height)*0.5)
else:
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:
#
# 调整mask的大小
nw, nh = layer_image.size
mask = mask.resize((nw, nh))
# 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)
# # 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)
# new_rgb_image.paste(layer_image, (x, y), mask=mask)
# mask=new_rgb_image.convert('L')
# mask = ImageOps.invert(mask)
if is_multiply_blend:
bg_image_white=Image.new("RGB", bg_image.size,(255, 255, 255))
@@ -753,8 +872,11 @@ def merge_images(bg_image, layer_image, mask, x, y, width, height, scale_option,
bg_image=multiply_blend(bg_image_white,bg_image)
bg_image=bg_image.convert("RGBA")
else:
# 在底图上粘贴图层
bg_image.paste(layer_image, (x, y), mask=mask)
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)
# 输出合成后的图片
return bg_image
@@ -802,6 +924,31 @@ def resize_image(layer_image, scale_option, width, height,color="white"):
resized_image = resized_image.convert("RGB")
resized_image=resize_2(resized_image)
return resized_image
elif scale_option == "longest":
#暂时不用,
if original_width > original_height:
new_width=width
scale = width / original_width
new_height = int(original_height * scale)
x=0
y=int((new_height-height)*0.5)
resized_image = Image.new("RGB", (new_width, new_height), color=color)
resized_image.paste(layer_image.resize((new_width, new_height)), (x,y))
resized_image = resized_image.convert("RGB")
resized_image=resize_2(resized_image)
return resized_image
else:
new_height=height
scale = height / original_height
new_width = int(original_height * scale)
x=int((new_width-width)*0.5)
y=0
resized_image = Image.new("RGB", (new_width, new_height), color=color)
resized_image.paste(layer_image.resize((new_width, new_height)), (x,y))
resized_image = resized_image.convert("RGB")
resized_image=resize_2(resized_image)
return resized_image
layer_image=resize_2(layer_image)
return layer_image
@@ -1703,10 +1850,15 @@ class CompositeImages:
def INPUT_TYPES(s):
return {
"required": {
"foreground": ("IMAGE",),
"mask":("MASK",),
"background": ("IMAGE",),
},
"foreground": (any_type,),
"mask":("MASK",),
"background": ("IMAGE",),
},
"optional":{
"is_multiply_blend": ("BOOLEAN", {"default": False}),
"position": (['overall',"center_bottom","center_top","right_bottom","left_bottom","right_top","left_top"],),
}
}
RETURN_TYPES = ("IMAGE",)
@@ -1718,11 +1870,11 @@ class CompositeImages:
# OUTPUT_IS_LIST = (True,)
def run(self, foreground,mask,background):
def run(self, foreground,mask,background,is_multiply_blend,position):
foreground= tensor2pil(foreground)
mask= tensor2pil(mask)
background= tensor2pil(background)
res=composite_images(foreground,background,mask)
res=composite_images(foreground,background,mask,is_multiply_blend,position)
return (pil2tensor(res),)
@@ -2831,6 +2983,65 @@ class SaveImageAndMetadata:
return { "ui": { "images": results } }
class ComparingTwoFrames:
def __init__(self):
self.output_dir = folder_paths.get_output_directory()
self.type = "output"
self.prefix_append = "ComparingTwoFrames"
self.compress_level = 4
@classmethod
def INPUT_TYPES(s):
return {"required":
{"before_image": ("IMAGE", ),
"after_image": ("IMAGE", )
},
}
RETURN_TYPES = ()
FUNCTION = "comparingImages"
OUTPUT_NODE = True
CATEGORY = "♾️Mixlab/Output"
def comparingImages(self, before_image,after_image):
filename_prefix = self.prefix_append
full_output_folder, filename, counter, subfolder, filename_prefix = folder_paths.get_save_image_path(
filename_prefix, self.output_dir, after_image[0].shape[1], after_image[0].shape[0])
bresults = list()
for bimage in before_image:
i = 255. * bimage.cpu().numpy()
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
file = f"{filename}_{counter:05}_.png"
img.save(os.path.join(full_output_folder, file), pnginfo=None, compress_level=self.compress_level)
bresults.append({
"filename": file,
"subfolder": subfolder,
"type": self.type
})
counter += 1
results = list()
for aimage in after_image:
i = 255. * aimage.cpu().numpy()
img = Image.fromarray(np.clip(i, 0, 255).astype(np.uint8))
file = f"{filename}_{counter:05}_.png"
img.save(os.path.join(full_output_folder, file), pnginfo=None, compress_level=self.compress_level)
results.append({
"filename": file,
"subfolder": subfolder,
"type": self.type
})
counter += 1
return { "ui": { "after_images": results,"before_images":bresults } }
class ImageColorTransfer:
@classmethod
def INPUT_TYPES(s):
+7 -2
View File
@@ -42,8 +42,13 @@ else:
_available=True
llma_model_path=os.path.join(folder_paths.models_dir, "lama/big-lama.pt")
def get_lama_path():
try:
return folder_paths.get_folder_paths('lama')[0]
except:
return os.path.join(folder_paths.models_dir, "lama")
llma_model_path=os.path.join(get_lama_path(), "big-lama.pt")
if not os.path.exists(llma_model_path):
os.environ['LAMA_MODEL']=''
print(f"## lama torchscript model not found: {llma_model_path},pls download from https://github.com/enesmsahin/simple-lama-inpainting/releases/download/v0.1.0/big-lama.pt")
+23 -15
View File
@@ -476,6 +476,24 @@ os.environ["U2NET_HOME"] = U2NET_HOME
global _available
_available=False
def get_rembg_models(path):
"""从目录中获取文件并提取文件名
Args:
path: 目录路径
Returns:
文件名列表
"""
filenames = []
for root, _, files in os.walk(path):
for filename in files:
# 过滤隐藏文件
if not filename.startswith('.'):
name, ext = os.path.splitext(os.path.basename(filename))
filenames.append(name)
return filenames
def is_installed(package):
try:
spec = importlib.util.find_spec(package)
@@ -509,7 +527,7 @@ except:
_available=False
def briarmbg_run(images=[]):
def run_briarmbg(images=[]):
mroot=os.path.join(folder_paths.models_dir, "rembg")
m=os.path.join(mroot,'briarmbg.pth')
if os.path.exists(m)==False:
@@ -573,7 +591,7 @@ def briarmbg_run(images=[]):
return (masks,rgba_images,rgb_images)
def run_bg(model_name= "unet",images=[]):
def run_rembg(model_name= "unet",images=[]):
# model_name = "unet" # "isnet-general-use"
rembg_session = new_session(model_name)
masks=[]
@@ -643,17 +661,7 @@ class RembgNode_:
def INPUT_TYPES(s):
return {"required": {
"image": ("IMAGE",),
"model_name": ([
"briarmbg",
"u2net",
"u2netp",
"u2net_human_seg",
"u2net_cloth_seg",
"silueta",
"isnet-general-use",
"isnet-anime",
],),
"model_name": (get_rembg_models(U2NET_HOME),),
},
}
@@ -681,9 +689,9 @@ class RembgNode_:
images.append(im)
if model_name=='briarmbg':
masks,rgba_images,rgb_images=briarmbg_run(images)
masks,rgba_images,rgb_images=run_briarmbg(images)
else:
masks,rgba_images,rgb_images=run_bg(model_name,images)
masks,rgba_images,rgb_images=run_rembg(model_name,images)
masks=[pil2tensor(m) for m in masks]
+9 -3
View File
@@ -18,19 +18,25 @@ from lark import Lark, Transformer, v_args
global _available
_available=True
def get_text_generator_path():
try:
return folder_paths.get_folder_paths('prompt_generator')[0]
except:
return os.path.join(folder_paths.models_dir, "prompt_generator")
text_generator_model_path=os.path.join(folder_paths.models_dir, "prompt_generator/text2image-prompt-generator")
prompt_generator=get_text_generator_path()
text_generator_model_path=os.path.join(prompt_generator, "text2image-prompt-generator")
if not os.path.exists(text_generator_model_path):
print(f"## text_generator_model not found: {text_generator_model_path}, pls download from https://huggingface.co/succinctly/text2image-prompt-generator/tree/main")
text_generator_model_path='succinctly/text2image-prompt-generator'
zh_en_model_path=os.path.join(folder_paths.models_dir, "prompt_generator/opus-mt-zh-en")
zh_en_model_path=os.path.join(prompt_generator, "opus-mt-zh-en")
if not os.path.exists(zh_en_model_path):
print(f"## zh_en_model not found: {zh_en_model_path}, pls download from https://huggingface.co/Helsinki-NLP/opus-mt-zh-en/tree/main")
zh_en_model_path='Helsinki-NLP/opus-mt-zh-en'
def is_installed(package):
try:
spec = importlib.util.find_spec(package)
+362 -121
View File
@@ -247,10 +247,10 @@
.card textarea {
width: 100%;
/* height: 200px; */
height: 'fit-content';
/* min-width: 300px; */
margin-top: 12px;
resize: vertical;
resize: none;
overflow: hidden;
}
@@ -404,9 +404,9 @@
display: none;
}
/* 定义滚动条轨道的背景颜色 */
/* 定义滚动条轨道的背景颜色 */
::-webkit-scrollbar-track {
::-webkit-scrollbar-track {
background-color: #f1f1f1;
/* 轨道背景颜色 */
}
@@ -434,28 +434,35 @@
/* 角落颜色 */
}
/*
.dynamic_prompt::after {
content: attr(title);
position: absolute;
position: absolute;
color: black;
padding: 4px;
padding-left: 25px;
border-radius: 4px;
} */
summary {
user-select: none;
}
</style>
<!-- <script src="../../../scripts/api.js" type="module"></script> -->
<link href="/extensions/comfyui-mixlab-nodes/lib/photoswipe.min.css" rel="stylesheet">
<link href="/extensions/comfyui-mixlab-nodes/lib/classic.min.css" rel="stylesheet">
<script src="/extensions/comfyui-mixlab-nodes/lib/pickr.min.js"></script>
<script src="/extensions/comfyui-mixlab-nodes/lib/filerobot-image-editor.min.js"></script>
<!-- <script src="/extensions/comfyui-mixlab-nodes/lib/filerobot-image-editor.min.js"></script> -->
<script type="module" src="/extensions/comfyui-mixlab-nodes/lib/model-viewer.min.js"></script>
<link rel="stylesheet" href="/extensions/comfyui-mixlab-nodes/lib/login.css">
</head>
<body>
<div id="editor_container"></div>
<div id="editor_container">
<iframe style="width:100%; height:100vh;" id="miniPaint"
src="/extensions/comfyui-mixlab-nodes/lib/miniPaint-4.14.2/index.html" allow="camera"></iframe>
</div>
<div class="header">
<div id="logo" style="margin: 0 24px;
margin-bottom: 24px;
@@ -467,15 +474,15 @@
<a class="link" href="https://www.mixcomfy.com" target="_blank">ComfyUI中文爱好者社区推荐</a>
</div>
<a target="_blank" id="login_btn" href="https://www.mixcomfy.com/blog/" style="text-decoration: none;
<a id="login_btn" target="_blank" href="https://discord.gg/xbP2GZF6gn"
style="text-decoration: none;
color: black;font-size:12px">
<svg height="32" aria-hidden="true" viewBox="0 0 16 16" version="1.1" width="32" data-view-component="true"
class="octicon octicon-mark-github v-align-middle color-fg-default">
<path
d="M8 0c4.42 0 8 3.58 8 8a8.013 8.013 0 0 1-5.45 7.59c-.4.08-.55-.17-.55-.38 0-.27.01-1.13.01-2.2 0-.75-.25-1.23-.54-1.48 1.78-.2 3.65-.88 3.65-3.95 0-.88-.31-1.59-.82-2.15.08-.2.36-1.02-.08-2.12 0 0-.67-.22-2.2.82-.64-.18-1.32-.27-2-.27-.68 0-1.36.09-2 .27-1.53-1.03-2.2-.82-2.2-.82-.44 1.1-.16 1.92-.08 2.12-.51.56-.82 1.28-.82 2.15 0 3.06 1.86 3.75 3.64 3.95-.23.2-.44.55-.51 1.07-.46.21-1.61.55-2.33-.66-.15-.24-.6-.83-1.23-.82-.67.01-.27.38.01.53.34.19.73.9.82 1.13.16.45.68 1.31 2.69.94 0 .67.01 1.3.01 1.49 0 .21-.15.45-.55.38A7.995 7.995 0 0 1 0 8c0-4.42 3.58-8 8-8Z">
</path>
</svg> Community</a>
</svg> HELP/帮助</a>
</div>
<a id="author"></a>
@@ -553,6 +560,42 @@
};
async function uploadMask(arrayBuffer, imgurl) {
const body = new FormData()
const filename = 'clipspace-mask-' + performance.now() + '.png'
let original_url = new URL(imgurl)
const original_ref = { filename: original_url.searchParams.get('filename') }
let original_subfolder = original_url.searchParams.get('subfolder')
if (original_subfolder) original_ref.subfolder = original_subfolder
let original_type = original_url.searchParams.get('type')
if (original_type) original_ref.type = original_type
body.append('image', arrayBuffer, filename)
body.append('original_ref', JSON.stringify(original_ref))
body.append('type', 'input')
body.append('subfolder', 'clipspace')
const url = get_url()
const resp = await fetch(`${url}/upload/mask`, {
method: 'POST',
body
})
// console.log(resp)
let data = await resp.json()
let { name, subfolder, type } = data
let src = `${url}/view?filename=${encodeURIComponent(
name
)}&type=${type}&subfolder=${subfolder}&rand=${Math.random()}`
return { url: src, name: 'clipspace/' + name }
}
const parseImageToBase64 = url => {
return new Promise((res, rej) => {
@@ -637,125 +680,316 @@
}
function editImage(img, data) {
// 获取 rembg 模型
async function get_rembg_models() {
try {
const response = await fetch(`${get_url()}/mixlab/folder_paths`, {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify({
type: 'rembg'
})
})
const data = await response.json()
// console.log(data)
return data.names
} catch (error) {
console.error(error)
}
}
const update = async () => {
const { imageData } = filerobotImageEditor.getCurrentImgData()
let base64 = imageData.imageBase64;
//自动抠图
async function run_rembg(model, base64) {
try {
const response = await fetch(`${get_url()}/mixlab/rembg`, {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify({
model,
base64
})
})
let fileBlob = base64ToBlob(base64)
// // 获取读取的文件内容,即 Blob 对象
let hashId = await calculateImageHash(fileBlob)
const data = await response.json()
// console.log(data)
return data.data
} catch (error) {
console.error(error)
}
}
if (hashId == window._appData.data[data.id].hashId) return
function convertImageToBlackBasedOnAlpha(image) {
const canvas = document.createElement('canvas');
const ctx = canvas.getContext('2d');
let { url, name } = await uploadImage(fileBlob);
// 在这里可以对 Blob 对象进行进一步处理
// imageElement.src = url;
window._appData.data[data.id].inputs.image = name;
window._appData.data[data.id].hashId = hashId;
// Draw the image onto the canvas
canvas.width = image.width;
canvas.height = image.height;
ctx.drawImage(image, 0, 0);
console.log("上传的文件:", url, data.id, name);
// Get the image data from the canvas
const imageData = ctx.getImageData(0, 0, canvas.width, canvas.height);
const pixels = imageData.data;
img.src = base64;
// Modify the RGB values based on the alpha channel
for (let i = 0; i < pixels.length; i += 4) {
const alpha = pixels[i + 3];
if (alpha !== 0) {
// Set non-transparent pixels to black
pixels[i] = 0; // Red
pixels[i + 1] = 0; // Green
pixels[i + 2] = 0; // Blue
}
}
const { TABS, TOOLS } = FilerobotImageEditor;
const config = {
source: img.src,
// loadableDesignState:{ //默认值
// annotations:{
// watermark:{
// image:'https://127.0.0.1:8189/view?filename=1703554480406.png&type=input&subfolder=&rand=0.044164708320141965',
// width:100,
// height:200,
// x:10,
// y:50,
// name: "Image",
// id:'watermark'
// }
// }
// },
// annotationsCommon: {
// fill: '#ff0000',
// },
// Text: { text: 'Filerobot...' },
Rotate: { angle: 90, componentType: 'slider' },
// Put the modified image data back onto the canvas
ctx.putImageData(imageData, 0, 0);
Crop: {
presetsItems: [
{
titleKey: 'classicTv',
descriptionKey: '4:3',
ratio: 4 / 3,
// icon: CropClassicTv,
},
{
titleKey: 'cinemascope',
descriptionKey: '21:9',
ratio: 21 / 9,
// icon: CropCinemaScope,
},
],
presetsFolders: [
{
titleKey: 'socialMedia', // will be translated into Social Media as backend contains this translation key
// icon: Social, // optional,
groups: [
{
titleKey: 'facebook',
items: [
{
titleKey: 'profile',
width: 180,
height: 180,
descriptionKey: 'fbProfileSize',
},
{
titleKey: 'coverPhoto',
width: 820,
height: 312,
descriptionKey: 'fbCoverPhotoSize',
},
],
},
],
},
],
},
tabsIds: [...Object.values(TABS)], // or ['Adjust', 'Annotate', 'Watermark']
defaultTabId: TABS.WATERMARK, // or 'Annotate'
defaultToolId: TOOLS.WATERMARK, // or 'Text'
closeAfterSave: true
};
// Convert the modified canvas to base64 data URL
const base64ImageData = canvas.toDataURL('image/png'); // Replace 'png' with your desired image format
return base64ImageData;
}
// 图像编辑
async function editImage(image, data) {
//判断mask是否有输出
let isMask = data.options.hasMask;
console.log(data)
//app
document.body.querySelector('.app').style.display = 'none'
document.body.querySelector('#author').style.display = 'none'
let editor = document.querySelector('#editor_container')
// Assuming we have a div with id="editor_container"
editor.style.display = 'block';
// console.log(img,editor,data)
document.body.style.overflow = 'hidden'
const iframe = editor.querySelector('iframe');
const filerobotImageEditor = new FilerobotImageEditor(
editor,
config,
);
// 复原
const resetLayer = () => {
let Layers = iframe.contentWindow.Layers;
for (const layer of Layers.get_layers()) {
layer.visible = true;
}
Layers.refresh_gui()
}
//取image
const getImageBase64FromLayer = () => {
let Layers = iframe.contentWindow.Layers;
let tempCanvas = document.createElement("canvas");
let tempCtx = tempCanvas.getContext("2d");
let dim = Layers.get_dimensions();
tempCanvas.width = dim.width;
tempCanvas.height = dim.height;
for (const layer of Layers.get_layers()) {
if (layer.name === 'Image_' + data.id) {
layer.visible = true;
} else {
layer.visible = false;
}
}
Layers.refresh_gui()
filerobotImageEditor.render({
onSave: (editedImageObject, designState) => {
console.log('saved', designState)
//adjustments
update()
},
onClose: (closingReason) => {
console.log('Closing reason', closingReason);
Layers.convert_layers_to_canvas(tempCtx);
return tempCanvas.toDataURL()
}
filerobotImageEditor.terminate();
editor.style.display = 'none'
document.body.style.overflow = 'auto'
//add mask
const addMask = (id, name, image) => {
let Layers = iframe.contentWindow.Layers;
var new_mask_layer = {
id,
name,
type: 'brush',
data: [],
render_function: ['brush', 'render'],
width: image.naturalWidth || image.width,
height: image.naturalHeight || image.height,
},
});
};
Layers.insert(new_mask_layer);
}
//add image
const addImage = (id, name, image) => {
let Layers = iframe.contentWindow.Layers;
var new_mask_layer = {
id,
name,
type: 'image',
data: image,
width: image.naturalWidth || image.width,
height: image.naturalHeight || image.height,
width_original: image.naturalWidth || image.width,
height_original: image.naturalHeight || image.height,
};
Layers.insert(new_mask_layer);
}
//默认的画笔size设置大
// let inputSize = (iframe.contentDocument.getElementById('size')).querySelector('input');
// inputSize.value=50;
// (iframe.contentDocument.getElementById('size')).querySelector('.increase_number').click()
//自动抠图
let autoMaskSelect = iframe.contentDocument.getElementById('automask_image_mixlab');
const select = iframe.contentDocument.getElementById('automask_models_mixlab');
let rembgModels = await get_rembg_models()
// 遍历模型列表并创建选项
for (const model of rembgModels) {
const option = document.createElement('option');
option.value = model;
option.textContent = model;
select.appendChild(option);
}
let autoMaskBtn = iframe.contentDocument.getElementById('automask_image_mixlab');
autoMaskBtn.addEventListener('click', async e => {
//api请求
let base64 = getImageBase64FromLayer()
resetLayer()
let res = await run_rembg(select.value, base64)
const match = res.match(/^data:image\/(\w+);base64,/);
if (!match) {
res = 'data:image/png;base64,' + res
}
let image = await createImage(res)
let mb = convertImageToBlackBasedOnAlpha(image)
let mask = await createImage(mb)
addImage((Layers.get_layers()).length, 'Mask_' + data.id, mask)
})
let cancelImageBtn = iframe.contentDocument.getElementById('cancel_image_mixlab');
cancelImageBtn.addEventListener('click', e => {
editor.style.display = 'none';
document.body.querySelector('.app').style.display = 'flex'
document.body.querySelector('#author').style.display = 'block'
})
// 获取 id 为 "mix" 的 button 元素
let saveImageBtn = iframe.contentDocument.getElementById('save_image_mixlab');
saveImageBtn.style = `width: 98px;
height: 36px;
margin: 0 12px;
background-color: var(--background-color-active);
color: var(--text-color-active);`
saveImageBtn.addEventListener('click', async e => {
//保存,并更新图片
e.preventDefault();
//image的合成,排除mask和brush
if (isMask) {
let Layers = iframe.contentWindow.Layers;
let tempCanvas = document.createElement("canvas");
let tempCtx = tempCanvas.getContext("2d");
let dim = Layers.get_dimensions();
tempCanvas.width = dim.width;
tempCanvas.height = dim.height;
for (const layer of Layers.get_layers()) {
if (layer.name !== 'Image_' + data.id) {
layer.visible = true;
} else {
layer.visible = false;
}
}
Layers.refresh_gui()
Layers.convert_layers_to_canvas(tempCtx);
// 复原
resetLayer()
// 获取图像数据
const imageData = tempCtx.getImageData(0, 0, dim.width, dim.height);
const imageDataData = imageData.data;
// 反相图像数据
for (let i = 0; i < imageDataData.length; i += 4) {
// imageDataData[i] = 255 - imageDataData[i];
// imageDataData[i + 1] = 255 - imageDataData[i + 1];
// imageDataData[i + 2] = 255 - imageDataData[i + 2];
imageDataData[i + 3] = 255 - imageDataData[i + 3]; // 反相透明度
}
// 更新画布
tempCtx.putImageData(imageData, 0, 0);
let base64 = tempCanvas.toDataURL();
// console.log(base64);
editor.style.display = 'none';
let fileBlob = base64ToBlob(base64)
// // 获取读取的文件内容,即 Blob 对象
let hashId = await calculateImageHash(fileBlob)
if (hashId == window._appData.data[data.id].hashId) return;
const { url: imgurl } = await uploadImage(base64ToBlob(data.options.defaultImage))
let { url, name } = await uploadMask(fileBlob, imgurl);
// 在这里可以对 Blob 对象进行进一步处理
// imageElement.src = url;
window._appData.data[data.id].inputs.image = name;
window._appData.data[data.id].hashId = hashId;
// console.log("上传的文件:", url, data.id, name);
//更新图片
const canvas = document.createElement("canvas");
canvas.width = dim.width;
canvas.height = dim.height;
const ctx = canvas.getContext('2d');
const defaultImage = await createImage(data.options.defaultImage)
ctx.drawImage(defaultImage, 0, 0, dim.width, dim.height);
// 绘制base64图片
// const base64Image = base64
const base64ImageObj = await createImage(base64)
ctx.globalCompositeOperation = 'destination-in';
ctx.drawImage(base64ImageObj, 0, 0, dim.width, dim.height);
image.src = canvas.toDataURL();
}
document.body.querySelector('.app').style.display = 'flex'
document.body.querySelector('#author').style.display = 'block'
})
var Layers = iframe.contentWindow.Layers;
// console.log(Layers)
//判断是否已经存在
let layers1 = Layers.get_layers()
if (!layers1.filter(l => l.name == 'Image_' + data.id)[0]) {
addImage((Layers.get_layers()).length, 'Image_' + data.id, image)
}
if (isMask) {
if (!layers1.filter(l => l.name == 'Mask_' + data.id)[0]) {
addMask((Layers.get_layers()).length, 'Mask_' + data.id, image)
}
}
}
@@ -948,6 +1182,10 @@
function createOutputs(outputData, link) {
const url = new URL(window.location.href);
const params = new URLSearchParams(url.search);
const innerApp = params.get("innerApp");
const container = document.createElement('div');
container.className = "output";
@@ -956,11 +1194,11 @@
const copyHTML = document.createElement('button');
copyHTML.innerText = 'copy as html'
action.appendChild(copyHTML)
if (!innerApp) action.appendChild(copyHTML)
const copyImage = document.createElement('button');
copyImage.innerText = 'copy image'
action.appendChild(copyImage)
if (!innerApp) action.appendChild(copyImage)
copyImage.style.marginLeft = '18px';
let isURL = false;
@@ -1062,18 +1300,19 @@
"Image Save",
"SaveImageAndMetadata_",
"TransparentImage"].includes(node.class_type)) {
console.log('output#image', node)
const url = node.options?.defaultImage || window._appData?.icon || base64Df;
let a = document.createElement('a');
a.id = `output_${node.id}`
a.setAttribute('data-pswp-width', "200");
a.setAttribute('data-pswp-height', "200");
a.setAttribute('target', "_blank");
a.setAttribute('href', base64Df);
a.setAttribute('href', url);
a.setAttribute('title', node.title);
let img = new Image();
// img;
img.src = window._appData?.icon || base64Df;
img.src = url;
a.appendChild(img)
output_card.appendChild(a);
isShowImageFn = true;
@@ -1477,7 +1716,8 @@
if (!isVideoUpload) btnFromClipboard.addEventListener('click', (event) => handleClipboardImage(imageElement, data));
if (!isVideoUpload && !isBase64Upload) btnForImageEdit.addEventListener('click', e => editImage(imageElement, data))
// 只有mask有输出,才有编辑功能
if (!isVideoUpload && !isBase64Upload && data.options.hasMask) btnForImageEdit.addEventListener('click', e => editImage(imageElement, data))
uploadImageInput.addEventListener('click', (event) => {
@@ -2267,7 +2507,8 @@
// leftDiv.appendChild(des);
leftDiv.appendChild(statusDiv);
leftDiv.appendChild(input1);
mainDiv.appendChild(submitButton);
if (typeof (data.data) == 'object') mainDiv.appendChild(submitButton);
rightDiv.appendChild(output);
@@ -2624,7 +2865,7 @@
ui.title.update(appData.name || 'Mixlab APP');
// 更新应用图标
ui.icon.update(appData.icon || base64Df);
ui.icon.update(appData.icon || appData.output[0]?.options?.defaultImage || base64Df);
ui.des.update(appData.description || '-');
+22 -3
View File
@@ -70,7 +70,8 @@ function get_position_style (ctx, widget_width, y, node_height) {
display: 'flex',
flexDirection: 'column',
// alignItems: 'center',
justifyContent: 'flex-start'
justifyContent: 'flex-start',
zIndex: 9999999
}
}
@@ -192,7 +193,7 @@ async function extractInputAndOutputData (
options.hasMask = true
}
// loadImage的默认图,转为base64
let imgurl = app.graph.getNodeById(id).imgs[0].src
let imgurl = app.graph.getNodeById(id).imgs[0].src + '&channel=rgb'
options.defaultImage = await drawImageToCanvas(imgurl, 512)
console.log('#loadImage的默认图', options)
@@ -207,9 +208,27 @@ async function extractInputAndOutputData (
// input.push()
}
if (outputIds.includes(id)) {
let options = {}
//输出的默认图
if (
node.type === 'SaveImageAndMetadata_' &&
app.graph.getNodeById(id).imgs
) {
// SaveImageAndMetadata_的默认图,转为base64
let imgurl = app.graph.getNodeById(id).imgs[0].src
options.defaultImage = await drawImageToCanvas(imgurl, 512)
console.log('#SaveImageAndMetadata_的默认图', options)
}
// let node = app.graph.getNodeById(id)
// output.push()
output[outputIds.indexOf(id)] = { ...data[id], title: node.title, id }
output[outputIds.indexOf(id)] = {
...data[id],
title: node.title,
id,
options
}
}
if (
+106
View File
@@ -0,0 +1,106 @@
async function* completion (url, messages, controller) {
let data = {
model: 'gpt-3.5-turbo-16k',
messages,
temperature: 0.6,
stream: true
}
// if (imageNode) {
// data = { ...data, image_data: [imageNode] }
// }
// let controller = new AbortController()
let response = await fetch(url, {
method: 'POST',
body: JSON.stringify(data),
headers: {
Connection: 'keep-alive',
'Content-Type': 'application/json',
Accept: 'text/event-stream'
},
signal: controller.signal
})
const reader = response.body.getReader()
const decoder = new TextDecoder()
let content = ''
let leftover = '' // Buffer for partially read lines
try {
let cont = true
while (cont) {
let result = await reader.read()
if (result.done) {
break
}
// Add any leftover data to the current chunk of data
const text = leftover + decoder.decode(result.value)
// Check if the last character is a line break
const endsWithLineBreak = text.endsWith('\n')
// Split the text into lines
let lines = text.split('\n')
// If the text doesn't end with a line break, then the last line is incomplete
// Store it in leftover to be added to the next chunk of data
if (!endsWithLineBreak) {
leftover = lines.pop()
} else {
leftover = '' // Reset leftover if we have a line break at the end
}
// Parse all sse events and add them to result
const regex = /^(\S+):\s(.*)$/gm
for (const line of lines) {
const match = regex.exec(line)
if (match) {
result[match[1]] = match[2]
// since we know this is llama.cpp, let's just decode the json in data
if (result.data) {
result.data = JSON.parse(result.data)
// console.log('#result.data',result.data)
content += result.data.choices[0].delta?.content || ''
// yield
yield result
// if we got a stop token from server, we will break here
if (result.data.choices[0].finish_reason == 'stop') {
if (result.data.generation_settings) {
// generation_settings = result.data.generation_settings;
}
cont = false
break
}
}
}
}
}
} catch (e) {
console.error('llama error: ', e)
throw e
} finally {
controller.abort()
}
return content
// return (await response.json()).content
}
export async function completion_ (url, messages, controller, callback) {
let request = await completion(url, messages, controller)
for await (const chunk of request) {
let content = chunk.data.choices[0].delta.content || ''
if (chunk.data.choices[0].role == 'assistant') {
//开始
content = ''
}
if (callback) callback(content)
}
}
+1 -1
View File
@@ -3,7 +3,7 @@ import { app } from '../../../scripts/app.js'
const repoOwner = 'shadowcz007' // 替换为仓库的所有者
const repoName = 'comfyui-mixlab-nodes' // 替换为仓库的名称
const version = 'v0.23.0'
const version = 'v0.28.0'
fetch(`https://api.github.com/repos/${repoOwner}/${repoName}/releases/latest`)
.then(response => response.json())
+149
View File
@@ -705,7 +705,9 @@ app.registerExtension({
async beforeRegisterNodeDef (nodeType, nodeData, app) {
if (nodeType.comfyClass == 'LoadImagesToBatch') {
const orig_nodeCreated = nodeType.prototype.onNodeCreated
nodeType.prototype.onNodeCreated = function () {
orig_nodeCreated?.apply(this, arguments)
@@ -841,3 +843,150 @@ app.registerExtension({
}
}
})
// 如何引入css
app.registerExtension({
name: 'Mixlab.output.ComparingTwoFrames_',
init () {
$el('link', {
rel: 'stylesheet',
href: '/extensions/comfyui-mixlab-nodes/lib/juxtapose.css',
parent: document.head
})
$el('style', {
textContent: `
.juxtapose-name{
display: none!important;
}
`,
parent: document.body
})
},
async beforeRegisterNodeDef (nodeType, nodeData, app) {
if (nodeType.comfyClass == 'ComparingTwoFrames_') {
const onNodeCreated = nodeType.prototype.onNodeCreated
nodeType.prototype.onNodeCreated = function () {
const r = onNodeCreated
? onNodeCreated.apply(this, arguments)
: undefined
this.size = [400, this.size[1]]
console.log('##onNodeCreated', this)
const widget = {
type: 'div',
name: 'preview',
draw (ctx, node, widget_width, y, widget_height) {
Object.assign(
this.div.style,
get_position_style(ctx, 400, 44, node.size[1])
)
},
serialize: false
}
widget.div = $el('div', {})
document.body.appendChild(widget.div)
this.addCustomWidget(widget)
this.serialize_widgets = true //需要保存参数
const onRemoved = this.onRemoved
this.onRemoved = () => {
widget.div.remove()
return onRemoved?.()
}
return r
}
const onExecuted = nodeType.prototype.onExecuted
nodeType.prototype.onExecuted = function (message) {
onExecuted?.apply(this, arguments)
console.log('##onExecuted', this, message)
this.widgets[0].div.id = 'mix_comparingtowframes_' + this.id
let after_image = message.after_images[0]
let before_image = message.before_images[0]
after_image = `${window.location.protocol}//${
window.location.hostname
}:${window.location.port}/view?filename=${encodeURIComponent(
after_image.filename
)}&type=${after_image.type}&subfolder=${encodeURIComponent(
after_image.subfolder
)}&t=${+new Date()}`
before_image = `${window.location.protocol}//${
window.location.hostname
}:${window.location.port}/view?filename=${encodeURIComponent(
before_image.filename
)}&type=${before_image.type}&subfolder=${encodeURIComponent(
before_image.subfolder
)}&t=${+new Date()}`
this.widgets[0].div.innerHTML = ''
let slider = new juxtapose.JXSlider(
'#mix_comparingtowframes_' + this.id,
[
{
src: before_image,
label: 'Before'
},
{
src: after_image,
label: 'After'
}
],
{
animate: true,
showLabels: true,
showCredits: false,
startingPosition: '50%',
makeResponsive: false
}
)
this.widgets_values = [
{
src: before_image,
label: 'Before'
},
{
src: after_image,
label: 'After'
}
]
this.size=[this.size[0],300]
}
}
},
async loadedGraphNode (node, app) {
// console.log('##loadedGraphNode', node)
if (node.type === 'ComparingTwoFrames_') {
// node.widgets[0].div.id = 'mix_comparingtowframes_' + node.id
// if (node.widgets_values && node.widgets_values[0]) {
// node.widgets[0].div.innerHTML = ''
// let slider = new juxtapose.JXSlider(
// '#mix_comparingtowframes_' + node.id,
// node.widgets_values,
// {
// animate: true,
// showLabels: true,
// showCredits: false,
// startingPosition: '50%',
// makeResponsive: false
// }
// )
// }
}
}
})
+684 -74
View File
@@ -9,6 +9,148 @@ import {
import { smart_init, addSmartMenu } from './smart_connect.js'
import { completion_ } from './chat.js'
function showTextByLanguage (key, json) {
// 获取浏览器语言
var language = navigator.language
// 判断是否为中文
if (
language.indexOf('zh') !== -1 ||
(language.indexOf('cn') !== -1 && json[key])
) {
return json[key]
} else {
return key
}
}
//系统prompt
const systemPrompt = `You are a prompt creator, your task is to create prompts for the user input request, the prompts are image descriptions that include keywords for (an adjective, type of image, framing/composition, subject, subject appearance/action, environment, lighting situation, details of the shoot/illustration, visuals aesthetics and artists), brake keywords by comas, provide high quality, non-verboose, coherent, brief, concise, and not superfluous prompts, the subject from the input request must be included verbatim on the prompt,the prompt is english`
if (!localStorage.getItem('_mixlab_system_prompt')) {
localStorage.setItem('_mixlab_system_prompt', systemPrompt)
}
// 获取llama 模型
async function get_llamafile_models () {
try {
const response = await fetch('/mixlab/folder_paths', {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify({
type: 'llamafile'
})
})
const data = await response.json()
// console.log(data)
return data.names
} catch (error) {
console.error(error)
}
}
// 运行llama
async function start_llama (model = 'Phi-3-mini-4k-instruct-Q5_K_S.gguf') {
let n_gpu_layers = -1
try {
n_gpu_layers = parseInt(localStorage.getItem('_mixlab_llama_n_gpu'))
} catch (error) {}
try {
const response = await fetch('/mixlab/start_llama', {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify({
model,
n_gpu_layers
})
})
const data = await response.json()
if (data.llama_cpp_error) {
return
}
return {
url: `http://${window.location.hostname}:${data.port}`,
model: data.model,
chat_format: data.chat_format
}
} catch (error) {
console.error(error)
}
}
function resizeImage (base64Image) {
var img = new Image()
var canvas = document.createElement('canvas')
var ctx = canvas.getContext('2d')
return new Promise((res, rej) => {
img.onload = function () {
// 等比例缩放图片
var width = img.width
var height = img.height
var max_width = 768
if (width > max_width) {
height *= max_width / width
width = max_width
}
// 设置canvas尺寸
canvas.width = width
canvas.height = height
// 在canvas上绘制图片
ctx.drawImage(img, 0, 0, width, height)
// 将canvas转换为base64图片数据
var canvasData = canvas.toDataURL()
res(canvasData) // canvas转换后的base64图片数据
}
img.src = base64Image
})
}
// 菜单入口
async function createMenu () {
const menu = document.querySelector('.comfy-menu')
const separator = document.createElement('div')
separator.style = `margin: 20px 0px;
width: 100%;
height: 1px;
background: var(--border-color);
`
menu.append(separator)
if (!menu.querySelector('#mixlab_chatbot_by_llamacpp')) {
const appsButton = document.createElement('button')
appsButton.id = 'mixlab_chatbot_by_llamacpp'
appsButton.textContent = '♾️Mixlab'
// appsButton.onclick = () =>
appsButton.onclick = async () => {
if (window._mixlab_llamacpp) {
//显示运行的模型
createModelsModal([
window._mixlab_llamacpp.url,
window._mixlab_llamacpp.model
])
} else {
let ms = await get_llamafile_models()
ms = ms.filter(m => !m.match('-mmproj-'))
if (ms.length > 0) createModelsModal(ms)
}
}
menu.append(appsButton)
}
}
let isScriptLoaded = {}
function loadExternalScript (url) {
@@ -299,8 +441,9 @@ async function get_my_app (filename = null, category = '') {
data = []
for (const res of result.data) {
let { app, workflow } = res.data;
if (app?.filename) data.push({
let { app, workflow } = res.data
if (app?.filename)
data.push({
...app,
data: workflow,
date: res.date
@@ -344,6 +487,33 @@ injectCSS(`::-webkit-scrollbar {
width: 2px;
}
#mixlab_chatbot_by_llamacpp{
font-size:14px
}
#mixlab_chatbot_by_llamacpp::before {
content: attr(title);
position: absolute;
margin-top: 24px;
font-size: 10px;
}
.mix_tag{
padding:8px;cursor: pointer;font-size: 14px;
color: var(--input-text);
background-color: var(--comfy-input-bg);
border-radius: 8px;
border-color: var(--border-color);
border-style: solid;
margin-top: 2px;
margin-bottom: 14px;
}
.mix_tag:hover{
background-color: #101c19;
color: aquamarine;
}
@keyframes loading_mixlab {
0% {
background-color: green;
@@ -369,7 +539,6 @@ injectCSS(`::-webkit-scrollbar {
border-left: 2px solid var(--input-text);
}
`)
async function getCustomnodeMappings (mode = 'url') {
@@ -494,13 +663,28 @@ app.showMissingNodesError = async function (
// 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,
nodesMap
).join('')}</ul>${
hasAddedNodes
? 'Nodes that have failed to load will show as red on the graph.'
: ''
`<a style="color: white;
font-size: 18px;
font-weight: 800;
letter-spacing: 2px;
font-family: sans-serif;
}"
href="https://discord.gg/cXs9vZSqeK" target="_blank">${showTextByLanguage(
'Welcome to Mixlab nodes discord, seeking help.',
{
'Welcome to Mixlab nodes discord, seeking help.':
'寻求帮助,加入Mixlab nodes交流频道'
}
)}</a><br><br>${showTextByLanguage(
'When loading the graph, the following node types were not found:',
{
'When loading the graph, the following node types were not found:':
'缺少以下节点:'
}
)}
<ul>${missingNodeGithub(missingNodeTypes, nodesMap).join('')}</ul>${
hasAddedNodes ? '' : ''
}`
)
this.logging.addEntry('Comfy.App', 'warn', {
@@ -586,13 +770,245 @@ async function fetchReadmeContent (url) {
}
}
function createModelsModal (models) {
var div =
document.querySelector('#model-modal') || document.createElement('div')
div.id = 'model-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;
background: #000000a8;
`
var modal = document.createElement('div')
div.addEventListener('click', e => {
e.stopPropagation()
div.remove()
})
div.appendChild(modal)
modal.classList.add('modal-body')
// Set modal styles
modal.style.cssText = `
color: var(--descrip-text);
background-color: var(--comfy-menu-bg);
position: fixed;
overflow:hidden;
top: 50%;
left: 50%;
transform: translate(-50%, -50%);
z-index: 9999;
border-radius: 4px;
box-shadow: 4px 4px 14px rgba(255,255,255,0.2);
`
// 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;
justify-content: space-between;
padding: 20px;
cursor: pointer;
user-select: none;
`
// headTitleElement.href = 'https://github.com/shadowcz007/comfyui-mixlab-nodes'
// headTitleElement.target = '_blank'
const linkIcon = document.createElement('small')
linkIcon.textContent = showTextByLanguage('Auto Open', {
'Auto Open': '自动开启'
})
linkIcon.style.padding = '4px'
const n_gpu = document.createElement('input')
n_gpu.type = 'number'
n_gpu.setAttribute('min', -1)
n_gpu.setAttribute('max', 9999)
n_gpu.style = `color: var(--input-text);
background-color: var(--comfy-input-bg);
border-radius: 8px;
border-color: var(--border-color);
height: 26px;
padding: 4px 10px;
width: 48px;
margin-left: 12px;`
if (localStorage.getItem('_mixlab_llama_n_gpu')) {
n_gpu.value = parseInt(localStorage.getItem('_mixlab_llama_n_gpu'))
} else {
n_gpu.value = -1
localStorage.setItem('_mixlab_llama_n_gpu', -1)
}
const n_gpu_p = document.createElement('p')
n_gpu_p.innerText = 'n_gpu_layers'
const n_gpu_div = document.createElement('div')
n_gpu_div.style = `display: flex;
justify-content: center;
align-items: center;
font-size: 12px;`
n_gpu_div.appendChild(n_gpu_p)
n_gpu_div.appendChild(n_gpu)
const title = document.createElement('p')
title.innerText = 'Models'
title.style = `font-size: 18px;
margin-right: 8px;`
const left_d = document.createElement('div')
left_d.style = `display: flex;
justify-content: center;
align-items: center;
font-size: 12px;`
left_d.appendChild(title)
left_d.appendChild(linkIcon)
headTitleElement.appendChild(left_d)
headTitleElement.appendChild(n_gpu_div)
//重启
const reStart = document.createElement('small')
reStart.textContent = showTextByLanguage('restart', {
restart: '重启'
})
reStart.style.padding = '4px'
headTitleElement.appendChild(reStart)
if (localStorage.getItem('_mixlab_auto_llama_open')) {
linkIcon.style.backgroundColor = '#66ff6c'
linkIcon.style.color = 'black'
}
linkIcon.addEventListener('click', e => {
e.stopPropagation()
if (localStorage.getItem('_mixlab_auto_llama_open')) {
localStorage.setItem('_mixlab_auto_llama_open', '')
linkIcon.style.backgroundColor = ''
linkIcon.style.color = 'var(--descrip-text)'
} else {
localStorage.setItem('_mixlab_auto_llama_open', 'true')
linkIcon.style.backgroundColor = '#66ff6c'
linkIcon.style.color = 'black'
}
})
reStart.addEventListener('click', e => {
e.stopPropagation()
div.remove()
fetch('mixlab/re_start', {
method: 'POST'
})
})
n_gpu.addEventListener('click', e => {
e.stopPropagation()
localStorage.setItem('_mixlab_llama_n_gpu', n_gpu.value)
})
modal.appendChild(headTitleElement)
// Create modal content area
var modalContent = document.createElement('div')
modalContent.classList.add('modal-content')
var input = document.createElement('textarea')
input.className = 'comfy-multiline-input'
input.style = ` height: 260px;
width: 480px;
font-size: 16px;
padding: 18px;`
input.value = localStorage.getItem('_mixlab_system_prompt')
input.addEventListener('change', e => {
e.stopPropagation()
localStorage.setItem('_mixlab_system_prompt', input.value)
})
input.addEventListener('click', e => {
e.stopPropagation()
})
modalContent.appendChild(input)
for (const m of models) {
let d = document.createElement('div')
d.innerText = m
d.className = `mix_tag`
if (!window._mixlab_llamacpp) {
d.addEventListener('click', async e => {
e.stopPropagation()
div.remove()
let res = await start_llama(m)
window._mixlab_llamacpp = res
localStorage.setItem('_mixlab_llama_select', res.model)
if (document.body.querySelector('#mixlab_chatbot_by_llamacpp')) {
document.body
.querySelector('#mixlab_chatbot_by_llamacpp')
.setAttribute('title', window._mixlab_llamacpp.url)
}
})
}
modalContent.appendChild(d)
}
modal.appendChild(modalContent)
const helpInfo = document.createElement('a')
helpInfo.textContent = showTextByLanguage('Help', {
Help: '寻求帮助'
})
helpInfo.style = `text-align: center;
display: block;
padding: 8px;
cursor: pointer;
font-size: 12px;
color: white;`
helpInfo.href="https://discord.gg/cXs9vZSqeK"
helpInfo.target="_blank"
modal.appendChild(helpInfo)
document.body.appendChild(div)
}
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%;
div.style.cssText = `
width: 100%;
z-index: 9990;
height: 100vh;
display: flex;
@@ -895,9 +1311,46 @@ function drawBadge (node, orig, restArgs) {
return r
}
function convertImageUrlToBase64 (imageUrl) {
return fetch(imageUrl)
.then(response => response.blob())
.then(blob => {
return new Promise((resolve, reject) => {
const reader = new FileReader()
reader.onloadend = () => resolve(reader.result)
reader.onerror = reject
reader.readAsDataURL(blob)
})
})
}
async function getSelectImageNode () {
var nodes = app.canvas.selected_nodes
let imageNode = null
if (Object.keys(app.canvas.selected_nodes).length == 0) return
for (var id in nodes) {
if (nodes[id].imgs) {
let base64 = await convertImageUrlToBase64(nodes[id].imgs[0].currentSrc)
imageNode = await resizeImage(base64)
}
}
return imageNode
}
app.registerExtension({
name: 'Comfy.Mixlab.ui',
init () {
//是否要自动加载模型
if (localStorage.getItem('_mixlab_auto_llama_open')) {
let model = localStorage.getItem('_mixlab_llama_select')
start_llama(model).then(res => {
window._mixlab_llamacpp = res
document.body
.querySelector('#mixlab_chatbot_by_llamacpp')
.setAttribute('title', res.url)
})
}
LGraphCanvas.prototype.helpAboutNode = async function (node) {
nodesMap =
nodesMap && Object.keys(nodesMap).length > 0
@@ -922,75 +1375,169 @@ app.registerExtension({
smart_init()
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)
console.log('getNodeMenuOptions', node.type == 'CLIPTextEncode')
LGraphCanvas.prototype.text2text = async function (node) {
// console.log(node)
let widget = node.widgets.filter(
w => w.name === 'text' && typeof w.value == 'string'
)[0]
if (widget) {
app.canvas.centerOnNode(node)
let opts = [
{
content: 'Help ♾️Mixlab', // with a name
callback: () => {
LGraphCanvas.prototype.helpAboutNode(node)
} // and the callback
},
{
content: 'Fix node v2', // with a name
callback: () => {
LGraphCanvas.prototype.fixTheNode(node)
let controller = new AbortController()
let ends = [] //TODO 判断终止 <|im_start|>
let userInput = widget.value
widget.value = widget.value.trim()
widget.value += '\n'
try {
await completion_(
window._mixlab_llamacpp.url + '/v1/chat/completions',
[
{
role: 'system',
content: localStorage.getItem('_mixlab_system_prompt')
},
{ role: 'user', content: userInput }
],
controller,
t => {
// console.log(t)
widget.value += t
}
)
} catch (error) {
//是否要自动加载模型
if (localStorage.getItem('_mixlab_auto_llama_open')) {
let model = localStorage.getItem('_mixlab_llama_select')
start_llama(model).then(async res => {
window._mixlab_llamacpp = res
document.body
.querySelector('#mixlab_chatbot_by_llamacpp')
.setAttribute('title', res.url)
await completion_(
window._mixlab_llamacpp.url + '/v1/chat/completions',
[
{
role: 'system',
content: localStorage.getItem('_mixlab_system_prompt')
},
{ role: 'user', content: userInput }
],
controller,
t => {
// console.log(t)
widget.value += t
}
)
})
}
}
]
if (node.widgets) {
// let text_widget = node.widgets.filter(
// w => w.name === 'text' && typeof w.value == 'string'
// )
// if (text_widget && text_widget.length == 1) {
// opts.push({
// content: 'Text-to-Text ♾️Mixlab', // with a name
// callback: () => {
// LGraphCanvas.prototype.text2text(node)
// } // and the callback
// })
// }
widget.value = widget.value.trim()
}
}
opts = addSmartMenu(opts, node)
LGraphCanvas.prototype.image2text = async function (node) {
let imageBase64 = await getSelectImageNode()
// if (node.type == 'CLIPTextEncode') {
// // 则出现 randomPrompt
// // CLIPTextEncode 的widget ,name== 'text'
// let node_widget_name = 'text'
// const widget = node.widgets.filter(w => w.name === node_widget_name)[0]
if (imageBase64) {
// console.log('image2text')
// 添加note 节点
const NoteNode = LiteGraph.createNode('Note')
NoteNode.title = `Image-to-Text ${node.id}`
NoteNode.size = [NoteNode.size[0] + 100, NoteNode.size[1]]
let widget = NoteNode.widgets[0]
widget.value = ''
// let mixlab_nodes_smart_connect= [{node_type:'CLIPTextEncode',
// node_widget_name:'text',
// inputNodeName:'RandomPrompt',
// inputNode_output_type:'STRING'}]
NoteNode.pos = [node.pos[0] + node.size[0] + 24, node.pos[1] - 48]
// if (widget) {
// opts = [
// {
// content: 'RandomPrompt',
// callback: () => {
// LGraphCanvas.prototype._createNodeForInput(
// node, //当前node
// widget,//当前node里需要自动连线的widget
// 'RandomPrompt',//作为input的node type
// 'STRING'// 作为input的node的outputs的type. the input slot type of the target node
// )
// }
// },
// null,
// ...opts
// ]
// }
// }
app.canvas.graph.add(NoteNode, false)
app.canvas.centerOnNode(NoteNode)
return [...opts, null, ...options] // and return the options
let controller = new AbortController()
let ends = []
let userInput = widget.value
widget.value = widget.value.trim()
widget.value += '\n'
try {
await completion_(
window._mixlab_llamacpp.url + '/v1/chat/completions',
[
{
role: 'system',
content: localStorage.getItem('_mixlab_system_prompt')
},
// { role: 'user', content: userInput }
{
role: 'user',
content: [
{
type: 'image_url',
image_url: {
url: imageBase64
}
},
{ type: 'text', text: 'What’s in this image?' }
]
}
],
controller,
t => {
// console.log(t)
widget.value += t
NoteNode.size[1] = widget.element.scrollHeight + 20
widget.computedHeight = NoteNode.size[1]
app.canvas.centerOnNode(NoteNode)
}
)
} catch (error) {
//是否要自动加载模型
if (localStorage.getItem('_mixlab_auto_llama_open')) {
let model = localStorage.getItem('_mixlab_llama_select')
start_llama(model).then(async res => {
window._mixlab_llamacpp = res
document.body
.querySelector('#mixlab_chatbot_by_llamacpp')
.setAttribute('title', res.url)
await completion_(
window._mixlab_llamacpp.url + '/v1/chat/completions',
[
{
role: 'system',
content: localStorage.getItem('_mixlab_system_prompt')
},
{
role: 'user',
content: [
{
type: 'image_url',
image_url: {
url: imageBase64
}
},
{ type: 'text', text: 'What’s in this image?' }
]
}
],
controller,
t => {
// console.log(t)
widget.value += t
NoteNode.size[1] = widget.element.scrollHeight + 20
widget.computedHeight = NoteNode.size[1]
app.canvas.centerOnNode(NoteNode)
}
)
})
}
}
widget.value = widget.value.trim()
}
}
const getGroupMenuOptions = LGraphCanvas.prototype.getGroupMenuOptions // store the existing method
@@ -1139,6 +1686,70 @@ app.registerExtension({
this.setDirty(true, true)
}
const getNodeMenuOptions = LGraphCanvas.prototype.getNodeMenuOptions
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)
let opts = [
{
content: 'Help ♾️Mixlab', // with a name
callback: () => {
LGraphCanvas.prototype.helpAboutNode(node)
} // and the callback
},
{
content: 'Fix node v2', // with a name
callback: () => {
LGraphCanvas.prototype.fixTheNode(node)
}
}
]
if (node.widgets) {
let text_widget = node.widgets.filter(
w => w.name === 'text' && typeof w.value == 'string'
)
let text_input = node.inputs?.filter(
inp => inp.name == 'text' && inp.type == 'STRING'
)
if (
text_input &&
text_input.length == 0 &&
text_widget &&
text_widget.length == 1 &&
window._mixlab_llamacpp &&
node.type != 'ShowTextForGPT'
) {
opts.push({
content: 'Text-to-Text ♾️Mixlab', // with a name
callback: () => {
LGraphCanvas.prototype.text2text(node)
} // and the callback
})
}
if (
node.imgs &&
node.imgs.length > 0 &&
window._mixlab_llamacpp &&
window._mixlab_llamacpp.chat_format === 'llava-1-5'
) {
opts.push({
content: 'Image-to-Text ♾️Mixlab', // with a name
callback: () => {
LGraphCanvas.prototype.image2text(node)
} // and the callback
})
}
}
return [...opts, null, ...options] // and return the options
}
// 支持app模式的json
const loadAppJson = async data => {
let workflow
@@ -1173,8 +1784,6 @@ app.registerExtension({
event.preventDefault()
event.stopPropagation()
// Dragging from Chrome->Firefox there is a file but its a bmp, so ignore that
if (
event.dataTransfer.files.length &&
@@ -1182,13 +1791,14 @@ app.registerExtension({
) {
const reader = new FileReader()
reader.onload = async () => {
loadAppJson(reader.result)
}
reader.readAsText(event.dataTransfer.files[0])
}
})
}
createMenu()
},
setup () {
setTimeout(async () => {
@@ -1198,7 +1808,7 @@ app.registerExtension({
const apps = await get_my_app()
if (!apps) return
console.log('apps',apps)
console.log('apps', apps)
let apps_map = { 0: [] }
+347
View File
@@ -0,0 +1,347 @@
/* juxtapose - v1.2.2 - 2020-09-03
* Copyright (c) 2020 Alex Duner and Northwestern University Knight Lab
*/
div.juxtapose {
width: 100%;
font-family: Helvetica, Arial, sans-serif;
}
div.jx-slider {
width: 100%;
height: 100%;
position: relative;
overflow: hidden;
cursor: pointer;
color: #f3f3f3;
}
div.jx-handle {
position: absolute;
height: 100%;
width: 40px;
cursor: col-resize;
z-index: 15;
margin-left: -20px;
}
.vertical div.jx-handle {
height: 40px;
width: 100%;
cursor: row-resize;
margin-top: -20px;
margin-left: 0;
}
div.jx-control {
height: 100%;
margin-right: auto;
margin-left: auto;
width: 3px;
background-color: currentColor;
}
.vertical div.jx-control {
height: 3px;
width: 100%;
background-color: currentColor;
position: relative;
top: 50%;
transform: translateY(-50%);
}
div.jx-controller {
position: absolute;
margin: auto;
top: 0;
bottom: 0;
height: 60px;
width: 9px;
margin-left: -3px;
background-color: currentColor;
}
.vertical div.jx-controller {
height: 9px;
width: 100px;
margin-left: auto;
margin-right: auto;
top: -3px;
position: relative;
}
div.jx-arrow {
position: absolute;
margin: auto;
top: 0;
bottom: 0;
width: 0;
height: 0;
transition: all .2s ease;
}
.vertical div.jx-arrow {
position: absolute;
margin: 0 auto;
left: 0;
right: 0;
width: 0;
height: 0;
transition: all .2s ease;
}
div.jx-arrow.jx-left {
left: 2px;
border-style: solid;
border-width: 8px 8px 8px 0;
border-color: transparent currentColor transparent transparent;
}
div.jx-arrow.jx-right {
right: 2px;
border-style: solid;
border-width: 8px 0 8px 8px;
border-color: transparent transparent transparent currentColor;
}
.vertical div.jx-arrow.jx-left {
left: 0px;
top: 2px;
border-style: solid;
border-width: 0px 8px 8px 8px;
border-color: transparent transparent currentColor transparent;
}
.vertical div.jx-arrow.jx-right {
right: 0px;
top: auto;
bottom: 2px;
border-style: solid;
border-width: 8px 8px 0 8px;
border-color: currentColor transparent transparent transparent;
}
div.jx-handle:hover div.jx-arrow.jx-left,
div.jx-handle:active div.jx-arrow.jx-left {
left: -1px;
}
div.jx-handle:hover div.jx-arrow.jx-right,
div.jx-handle:active div.jx-arrow.jx-right {
right: -1px;
}
.vertical div.jx-handle:hover div.jx-arrow.jx-left,
.vertical div.jx-handle:active div.jx-arrow.jx-left {
left: 0px;
top: 0px;
}
.vertical div.jx-handle:hover div.jx-arrow.jx-right,
.vertical div.jx-handle:active div.jx-arrow.jx-right {
right: 0px;
bottom: 0px;
}
div.jx-image {
position: absolute;
height: 100%;
display: inline-block;
top: 0;
overflow: hidden;
-webkit-backface-visibility: hidden;
}
.vertical div.jx-image {
width: 100%;
left: 0;
top: auto;
}
div.jx-image img {
height: 100%;
width: auto;
z-index: 5;
position: absolute;
margin-bottom: 0;
max-height: none;
max-width: none;
max-height: initial;
max-width: initial;
}
.vertical div.jx-image img {
height: auto;
width: 100%;
}
div.jx-image.jx-left {
left: 0;
background-position: left;
}
div.jx-image.jx-left img {
left: 0;
}
div.jx-image.jx-right {
right: 0;
background-position: right;
}
div.jx-image.jx-right img {
right: 0;
bottom: 0;
}
.veritcal div.jx-image.jx-left {
top: 0;
background-position: top;
}
.veritcal div.jx-image.jx-left img {
top: 0;
}
.vertical div.jx-image.jx-right {
bottom: 0;
background-position: bottom;
}
.veritcal div.jx-image.jx-right img {
bottom: 0;
}
div.jx-image div.jx-label {
font-size: 1em;
padding: .25em .75em;
position: relative;
display: inline-block;
top: 0;
background-color: #000; /* IE 8 */
background-color: rgba(0,0,0,.7);
color: white;
z-index: 10;
white-space: nowrap;
line-height: 18px;
vertical-align: middle;
}
div.jx-image.jx-left div.jx-label {
float: left;
left: 0;
}
div.jx-image.jx-right div.jx-label {
float: right;
right: 0;
}
.vertical div.jx-image div.jx-label {
display: table;
position: absolute;
}
.vertical div.jx-image.jx-right div.jx-label {
left: 0;
bottom: 0;
top: auto;
}
div.jx-credit {
line-height: 1.1;
font-size: 0.75em;
}
div.jx-credit em {
font-weight: bold;
font-style: normal;
}
/* Animation */
div.jx-image.transition {
transition: width .5s ease;
}
div.jx-handle.transition {
transition: left .5s ease;
}
.vertical div.jx-image.transition {
transition: height .5s ease;
}
.vertical div.jx-handle.transition {
transition: top .5s ease;
}
/* Knight Lab Credit */
a.jx-knightlab {
background-color: #000; /* IE 8 */
background-color: rgba(0,0,0,.25);
bottom: 0;
display: table;
height: 14px;
line-height: 14px;
padding: 1px 4px 1px 5px;
position: absolute;
right: 0;
text-decoration: none;
z-index: 10;
}
a.jx-knightlab div.knightlab-logo {
display: inline-block;
vertical-align: middle;
height: 8px;
width: 8px;
background-color: #c34528;
transform: rotate(45deg);
-ms-transform: rotate(45deg);
-webkit-transform: rotate(45deg);
top: -1.25px;
position: relative;
cursor: pointer;
}
a.jx-knightlab:hover {
background-color: #000; /* IE 8 */
background-color: rgba(0,0,0,.35);
}
a.jx-knightlab:hover div.knightlab-logo {
background-color: #ce4d28;
}
a.jx-knightlab span.juxtapose-name {
display: table-cell;
margin: 0;
padding: 0;
font-family: Helvetica, Arial, sans-serif;
font-weight: 300;
color: white;
font-size: 10px;
padding-left: 0.375em;
vertical-align: middle;
line-height: normal;
text-shadow: none;
}
/* keyboard accessibility */
div.jx-controller:focus,
div.jx-image.jx-left div.jx-label:focus,
div.jx-image.jx-right div.jx-label:focus,
a.jx-knightlab:focus {
background: #eae34a;
color: #000;
}
a.jx-knightlab:focus span.juxtapose-name{
color: #000;
border: none;
}
+8
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File diff suppressed because one or more lines are too long
+47
View File
@@ -0,0 +1,47 @@
/*
object-assign
(c) Sindre Sorhus
@license MIT
*/
/*!
pica
https://github.com/nodeca/pica
*/
/*!
* Block below copied from Protovis: http://mbostock.github.com/protovis/
* Copyright 2010 Stanford Visualization Group
* Licensed under the BSD License: http://www.opensource.org/licenses/bsd-license.php
* @license
*/
/*!
* jQuery JavaScript Library v3.7.1
* https://jquery.com/
*
* Copyright OpenJS Foundation and other contributors
* Released under the MIT license
* https://jquery.org/license
*
* Date: 2023-08-28T13:37Z
*/
/*!
* quantize.js Copyright 2008 Nick Rabinowitz.
* Licensed under the MIT license: http://www.opensource.org/licenses/mit-license.php
* @license
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<title>miniPaint - image editor</title>
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<meta name="keywords"
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<meta itemprop="description"
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<meta name="twitter:title" content="miniPaint" />
<meta name="twitter:description"
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<meta name="twitter:image:alt"
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<meta property="og:type" content="article" />
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<div class="hidden" id="tmp"></div>
<div id="popups"></div>
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