MiaoshouAI Assistant for [Automatic1111 WebUI]
喵手助理 [Automatic1111 WebUI]
Download Civitai models from your webui, miaoshou assistant will automaticly set the model cover and put the models in the right folder for you.
喵手助理非常簡單的搜索並下載Civitai或者煉丹閣上面的模型,同時會自動保存模型的封面和將模型自動下載到對應的文件夾中。
Manage your existing model, get your trigger word and model sample image tags easily. Send them to your prompt to start edit your own.
喵手助理可以管理你的模型,讓你查看模型的觸發詞,並且一鍵將模型的tag信息發送至txt2img, img2img, inpainting, extra 的提示詞。
Download different Stable Diffusion Official 1.5, 2.1 Models, Controlnet Models and VAE models from one place.
你也可以在模型源中,選擇下載不同的官方模型的1.5 2.1模型文件,Contrlnet以及VAE的各類模型。
Manage your boot setups including CPU settings, theme settings, API and port setting, etc with simple clicks.
啟動助手可以幫助你輕鬆一鍵設置並保存CPU,主題,API和端口等的啟動設置。
Install from Automatic1111 WebUI | 在Automatic1111 WebUI 下安裝
In Automatic1111 WebUI, go to Extensions Tab
->Install from URL
, copy the following address in "**URL for extension's git repository**".
在 Automatic1111 WebUI 中,前往 扩展插件
-> 从URL安装
,在`扩展插件的git仓库网址`中复制以下地址。
https://github.com/miaoshouai/miaoshouai-assistant.git
Click Install
, wait until it's done. Go to Settings
-> Reload UI
点击安裝
,等待安装完成。然后前往設置
-> 重新加载界面
OR you can just click on download from this page and unzip your file in your extensions folder under webui folder, then restart your Webui.
或者你可以直接點擊下載本頁面上的zip文件並解壓至你Webui目錄下的extensions文件夾
Top 200 Model Hashes used on Civitai from about 450,000 Civitai images as of 4/30/2023
First i recommend reading the Part 1 and after that part 2. Part one explains the settings.
I have planned to expand more on multidiffusion tutorials:
Workflow on region prompt control
Maybe inpaint workflow tutorial
If you have something you would like to see tutorial on let me know in the discussion.
Please leave feedback and images you manage to create with the tutorial :)
Updates:
05/01
V1.0 of Multidiffusion IMG2IMG Workflow
Tutorial more focused on scaling in IMG2IMG
04/29
V1.2 of Multidiffusion upscaler how to use + workflow
Clarified few things in the tutorial
04/25
V1.1 of Multidiffusion upscaler how to use + workflow
Fixed some typos, uncompressed images, wording
04/24
V1.0 of Multidiffusion upscaler how to use + workflow
This is information i have gathered experimenting with the extension. I might get something wrong and if you spot something wrong with guide, please leave comment. Any feedback is welcome.
I am not native English speaker and write such text. I can't do anything about that. :)
I am not the creator of this extension and i am not in any way related to them. They can be found from Gitgub . Please show some love for them if you have time :).
The name of the model info file that records information about the model has been changed.
As a result, even models with a normal model info file may be moved to a new folder when scanning models for Civitai.
To prevent this, uncheck the "Create a model folder corresponding to the model type" option.
Stable Diffusion Webui Extension for Civitai, to download civitai shortcut and models.
Stable Diffusion Webui's Extension tab, go to Install from url sub-tab. Copy this project's url into it, click install.
git clone https://github.com/sunnyark/civitai-shortcut
Install url : https://github.com/sunnyark/civitai-shortcut
The information in the Civitai model information tab is obtained in real-time from the Civitai website.
Download : downloads the model for the selected version. You can choose to create specific folders for each version. The downloaded model will be automatically saved in the appropriate location, and a preview image and info will be generated together with it.
The information in the Saved model information tab are composed of the information saved on the Civitai website when creating the shortcut.
Update Model Information : updates the information of an individual shortcut to the latest information. This function only works when the site is functioning normally.
Delete Shortcut : deletes the information of a registered shortcut.
Civitai User Gallery : The Civitai User Gallery allows users to view uploaded images.
Upload : This function creates a shortcut that can be used by the extension when you enter the Civitai site's model URL. It only works when the site is functioning properly. You can either click and drag the URL from the address bar or drag and drop saved internet shortcuts. You can also select multiple internet shortcuts and drop them at once.
Browsing : This function displays the registered shortcuts in thumbnail format, and when selected, displays their details on the right-hand side of the window. This function works independently of the Civitai site.
Scan New Version : This is a function that searches for the latest version of downloaded models on the Civitai site. It retrieves information from the site and only functions properly when the site is operational.
Classification : Function for managing shortcuts by classification.
Scan and Update Models
Scan Models for Civitai - Scan and register shortcut for models without model information that are currently held.
Update Shortcut - Move the shortcut update function from the Upload tab.
Update the model information for the shortcut - Update the information of registered shortcuts with the latest information.
Scan downloaded models for shortcut registration - Register new shortcuts for downloaded models that have been deleted or have missing model information.
Setting tab - Set the number of columns in the image gallery.
You can save the model URL of the Civitai site for future reference and storage.
This allows you to download the model when needed and check if the model has been updated to the latest version.
The downloaded models are saved to the designated storage location.
When using Civitai Shortcut, five items will be created:
sc_saves: a folder where registered model URLs are backed up and stored.
sc_thumb_images: a folder where thumbnails of registered URLs are stored.
sc_infos: a folder where model info and images are saved when registering a shortcut.
CivitaiShortCut.json: a JSON file that records and manages registered model URLs.
CivitaiShortCutClassification.json: a JSON file that records and manages registered classification.
CivitaiShortCutSetting.json: a JSON file that records setting.
v 1.3c
* Add "Scan and Update Models" and "Settings" tabs to the Manage tab.
* Scan and Update Models tab
Scan Models for Civitai - Scan and register shortcut for models without model information that are currently held.
Update Shortcut - Move the shortcut update function from the Upload tab.
Update the model information for the shortcut - Update the information of registered shortcuts with the latest information.
Scan downloaded models for shortcut registration - Register new shortcuts for downloaded models that have been deleted or have missing model information.
* Setting tab - Set the number of columns in the image gallery.
* The name of the model info file that records information about the model has been changed.
As a result, even models with a normal model info file may be moved to a new folder when scanning models for Civitai.
To prevent this, uncheck the "Create a model folder corresponding to the model type" option.
v 1.3a
* A new feature has been added that allows you to manage and classify items.
You can add, delete, and update classification items in the "manage" -> "classification" tab.
To add a shortcut, select the desired classification item in the center top and click on the list on the left to register the desired shortcut. When you click, the registered shortcut appears in the center of the screen, and you can remove it by clicking on the registered shortcut.
Click the "update" button to complete the registration.
In the "civitai shortcut" -> "information" tab, a "model classification" item has been added on the right side, and you can perform registration and deletion of shortcuts for the model corresponding to the desired classification item.
After modification, click the "update" button to complete the task.
* In the browsing "search" feature, you can check the items registered in the classification.
When you select a classification item from the dropdown list, the selected item appears in the list and works in conjunction with the "filter model type" and "search" features.
The "search" feature works by entering items such as tags, classification, and search keywords.
The tags, classification, and search keywords are applied with "and" operation, and each item is applied with "or" operation. Each item is separated by ",".
Although only one item can be selected from the classification dropdown list, you can enter multiple items by using the "@" prefix.
v 1.2a
* The Downloaded Model tab, which duplicated the functionality of the Saved Model Information tab, has been removed
* The application method for generating image information has been internally modified to include information from Civitai's 'information' field in addition to the image. As a result, there have been changes to the naming convention for saved images. Please update the images using 'Update Shortcut's Model Information' accordingly.
v 1.2
* A Civitai User Gallery tab has been added where users can view the information and images of the models in the gallery. If there are no images available for a particular model, the tab may appear empty. There may also be a delay in the data provided by the API.
* An "Update Downloaded Model Information" button has been added below the "Upload" button on the left-hand side. This button updates the internal information when users rename folders during Stable Diffusion operation.
* The option to download additional networks by selecting them from a list has been removed. This feature was deemed unnecessary as users can simply specify the desired folder in Settings -> Additional Networks. Personally, I use the "models/Lora" folder for this purpose.
* Users can now specify the folder name when downloading a model to an individual folder. The default format is "model name-version name", but users can input their preferred value. If a folder with the same version of the model already exists within the model's folder, that folder name will be displayed.
* Minor design changes have been made.
* Bug: There are several bugs, but when viewing the gallery images at full size, the image control and browsing controls overlap.
v 1.1c
* Measures have been taken to alleviate bottleneck issues during information loading.
* The search function now includes a #tag search feature.
Search terms are separated by commas (,) and are connected with an "or" operation within the search terms and within the tags. There is an "and" operation between the search terms and tags.
* The shortcut storage table has been changed to add the #tag search function.
Existing shortcuts require an "update shortcut model information" for tag searches.
v 1.1
* When registering a shortcut, model information and images are saved in a separate folder.
* This allows users to access model information from "Saved Model Information" Tab even if there is no connection to the Civitai site.
* "Thumbnail Update" button is removed and replaced with an "Update Shortcut's Model Information" button to keep the model information and images up to date.
* "Download images Only" button is removed from "Civitai Model Information" Tab that can be accessed live, and "Delete shortcut" button is moved to "Saved Model Information" Tab.
* "Delete shortcut" button removes the model information and images stored in sc_infos in one go.
* "Update Model Information" button is added to "Saved Model Information" Tab for individual updating of model information, in addition to "Update Shortcut's Model Information" that updates all model information.
This is copy of a pretrained_model for Google´s F.I.L.M interpolation algorithm.
It is taken from google drive for easier and automated download, the original is here:
pretrained_models – Google Drive
As the whole project on github is under Apache License, I assume this pretrained model underlies same license, since it is referenced by that project (https://github.com/google-research/frame-interpolation#see-windows_installation-for-windows-support)
This is a node setup workflow to compare different textual inversion embeddings in comfyUI.
Use Cases can be comparing of Character likeness embeddings or testing of different strengths of the same embedding.
For testing I am using Emma Watson, Selena Gomez and Wednesday Addams textual inversions, but any other can be put in their place.
After some trial and error, I discovered an efficient method for creating LoRAs that can apply styles or features to various items. My LoRAs have been well-received here, on civitai.com, and it's surprising how easy and fast the process is. It almost feels like cheating. I've enjoyed the recognition, but I believe it's time to humbly share my approach with everyone at no cost.
This tutorial showcases the typical process I follow for creating most of my LoRAs.
TLDR version: I utilize generated images; I incorporate simplistic illustrations into the training data; I employ basic captioning: [triggerword] [concept], and I use a simple Python script to create the caption files.
STEP 1: Find an idea (style / feature) and check that SD with your favorite checkpoint can't do it. Let's say, the boho-style.
Dear revAnimated, please generate a "boho tank" for me:
OK, the boho-style seems a good idea to try,
STEP 2: Check other image generators.
Dear Bing, please generate a "boho tank" for me:
prompt: illustration of battle tank in boho-style
Dear DALEE-2, please generate a "boho tank" for me:
prompt: battle tank in boho style, illustration
OK, we can see that these pictures somewhat capture the boho-style. Therefore ....
STEP 3: Generate the training set using an image generator which can understand the boho-style.
Some of my LoRAs use no generated images in the training set, while others incorporate a portion of generated images. Notably, my most recent LoRAs rely exclusively on generated pictures.
For example, generate "boho tank," "boho computer," "boho village," "boho dirigible," "boho submarine," etc. Aim for 1-6 images per concept, totaling 50-100 images.
When you generate such uncommon things, like "boho tank" you might come across images such the ones shown in STEP 2. Don't worry about including these images in the training data; they're often better than (semi-)realistic pictures. For instance, my training data for BohoAI only contains the following examples of dirigibles:
Yet, the final model produces this:
Include also some (semi-)realistic pictures. They should not be problem to generate for some concepts, like "boho living room".
STEP 4: Clean up the images by removing logos, generated author signatures, and other similar elements. Also remove unwanted artefacts, like the extra cannon on the tank tower.
The removal can be quite crude: just place other part of the picture over the unwanted part.
Do not resize the picture.
STEP 5: Captioning.
Use very basic captions, like "BohoAI dirigible."
To expedite the process, try this trick: save the images in a folder named after the concept. So, all dirigible pictures will be in a folder named "dirigible."
Once you have all images organized in their respective folders, execute the Python procedure I provide in attached files. It recursively travels through folders, and for each .jpg file creates .txt containing a given triggerword and the folder name.
STEP 6: We are good to go. Train the LoRA.
I think that you cannot go wrong with your usual setting.
After some experimenting, it seems that rank 128 and alpha 128 are needed to get the desired result. I'm going to make a deeper study later.
I'm sharing the config for kohya ss, but please take it with a grain of salt. I often change it and experiment blindly. BohoAI was trained with this config using 10 repetitions.
The LoRA encapsulates boho-style, adeptly applying it to untrained concepts.
Check dajusha's review picture (there are no pictures of any animals in my dataset.): https://civitai.com/images/616301?period=Week&periodMode=published&sort=Most+Reactions&view=categories&modelVersionId=56427&modelId=51966&postId=172873
I've shared my secret and kindly request one favor: if you publish your LoRA trained using this method, please credit this tutorial.
Numerous creators can adopt and enhance this idea, ultimately elevating the quality of civitai.com content. By sharing my golden goose, I kindly ask you to consider supporting me with a coffee through these links:
One SEAIT to Install Them, One Click to Launch Them, One Space-Saving Models Folder to Bind Them All.
"Super Easy AI Installer Tool" (SEAIT) is a user-friendly project that simplifies the installation process of AI-related projects for users. The tool is designed to provide an easy-to-use solution for accessing and installing AI projects with minimal technical hassle to none.
Tested on Windows 10+ and Nvidia GPU-based cards
Don't forget to leave a like or a star.
https://github.com/diStyApps/seait
Please note that Virustotal and other antivirus programs may give a false positive when running this app. This is due the use Pyinstaller to convert the python file EXE, which can sometimes trigger false positives even for the simpler scripts which is a known issue
Unfortunately, I don't have the time to handle these false positives. However, please rest assured that the code is transparent on https://github.com/diStyApps/seait
I would rather add features and more AI tools at this stage of development.
Source: https://github.com/pyinstaller/pyinstaller/issues/6754
Download the "Super Easy AI Installer Tool" at your own discretion.
Support for multiple languages [x]
Adding more projects [x]
Customizable project directory [x]
User-defined arguments [x]
Saving argument configurations [x]
In-app update feature [ ]
Potential argument profile management [ ]
Better event handling [ ]
Pre-installed auto1111 version [ ]
Fully independent version without Python or Git dependencies [ ]
See the [Project/Feature Requests](https://github.com/diStyApps/seait/discussions/11) for a full list of proposed features (and known issues).
Support
https://www.patreon.com/distyx
https://coindrop.to/disty
V2 新增10个 Add 10
分享一些自用的手部深度图,使用方法:拖到“深度图编辑器depth lib”这个插件里就行了。
插件url安装地址:
https://github.com/jexom/sd-webui-depth-lib.git
Share some self-use hand depth images, how to use them: just drag them into the "depth lib" plugin.
Plugin url installation address:
Trained on a large image scrape of various breastfeeding pictures, mainly drawings.
breastfeeding