| # Kohya's GUI | |
| This repository provides a Windows-focused Gradio GUI for [Kohya's Stable Diffusion trainers](https://github.com/kohya-ss/sd-scripts). The GUI allows you to set the training parameters and generate and run the required CLI commands to train the model. | |
| If you run on Linux and would like to use the GUI, there is now a port of it as a docker container. You can find the project [here](https://github.com/P2Enjoy/kohya_ss-docker). | |
| ### Table of Contents | |
| - [Tutorials](#tutorials) | |
| - [Required Dependencies](#required-dependencies) | |
| - [Linux/macOS](#linux-and-macos-dependencies) | |
| - [Installation](#installation) | |
| - [Linux/macOS](#linux-and-macos) | |
| - [Default Install Locations](#install-location) | |
| - [Windows](#windows) | |
| - [CUDNN 8.6](#optional--cudnn-86) | |
| - [Upgrading](#upgrading) | |
| - [Windows](#windows-upgrade) | |
| - [Linux/macOS](#linux-and-macos-upgrade) | |
| - [Launching the GUI](#starting-gui-service) | |
| - [Windows](#launching-the-gui-on-windows) | |
| - [Linux/macOS](#launching-the-gui-on-linux-and-macos) | |
| - [Direct Launch via Python Script](#launching-the-gui-directly-using-kohyaguipy) | |
| - [Dreambooth](#dreambooth) | |
| - [Finetune](#finetune) | |
| - [Train Network](#train-network) | |
| - [LoRA](#lora) | |
| - [Troubleshooting](#troubleshooting) | |
| - [Page File Limit](#page-file-limit) | |
| - [No module called tkinter](#no-module-called-tkinter) | |
| - [FileNotFoundError](#filenotfounderror) | |
| - [Change History](#change-history) | |
| ## Tutorials | |
| [How to Create a LoRA Part 1: Dataset Preparation](https://www.youtube.com/watch?v=N4_-fB62Hwk): | |
| [](https://www.youtube.com/watch?v=N4_-fB62Hwk) | |
| [How to Create a LoRA Part 2: Training the Model](https://www.youtube.com/watch?v=k5imq01uvUY): | |
| [](https://www.youtube.com/watch?v=k5imq01uvUY) | |
| ## Required Dependencies | |
| - Install [Python 3.10](https://www.python.org/ftp/python/3.10.9/python-3.10.9-amd64.exe) | |
| - make sure to tick the box to add Python to the 'PATH' environment variable | |
| - Install [Git](https://git-scm.com/download/win) | |
| - Install [Visual Studio 2015, 2017, 2019, and 2022 redistributable](https://aka.ms/vs/17/release/vc_redist.x64.exe) | |
| ### Linux and macOS dependencies | |
| These dependencies are taken care of via `setup.sh` in the installation section. No additional steps should be needed unless the scripts inform you otherwise. | |
| ## Installation | |
| ### Runpod | |
| Follow the instructions found in this discussion: https://github.com/bmaltais/kohya_ss/discussions/379 | |
| ### Linux and macOS | |
| In the terminal, run | |
| ``` | |
| git clone https://github.com/bmaltais/kohya_ss.git | |
| cd kohya_ss | |
| # May need to chmod +x ./setup.sh if you're on a machine with stricter security. | |
| # There are additional options if needed for a runpod environment. | |
| # Call 'setup.sh -h' or 'setup.sh --help' for more information. | |
| ./setup.sh | |
| ``` | |
| Setup.sh help included here: | |
| ```bash | |
| Kohya_SS Installation Script for POSIX operating systems. | |
| The following options are useful in a runpod environment, | |
| but will not affect a local machine install. | |
| Usage: | |
| setup.sh -b dev -d /workspace/kohya_ss -g https://mycustom.repo.tld/custom_fork.git | |
| setup.sh --branch=dev --dir=/workspace/kohya_ss --git-repo=https://mycustom.repo.tld/custom_fork.git | |
| Options: | |
| -b BRANCH, --branch=BRANCH Select which branch of kohya to check out on new installs. | |
| -d DIR, --dir=DIR The full path you want kohya_ss installed to. | |
| -g REPO, --git_repo=REPO You can optionally provide a git repo to check out for runpod installation. Useful for custom forks. | |
| -h, --help Show this screen. | |
| -i, --interactive Interactively configure accelerate instead of using default config file. | |
| -n, --no-update Do not update kohya_ss repo. No git pull or clone operations. | |
| -p, --public Expose public URL in runpod mode. Won't have an effect in other modes. | |
| -r, --runpod Forces a runpod installation. Useful if detection fails for any reason. | |
| -s, --skip-space-check Skip the 10Gb minimum storage space check. | |
| -u, --no-gui Skips launching the GUI. | |
| -v, --verbose Increase verbosity levels up to 3. | |
| ``` | |
| #### Install location | |
| The default install location for Linux is where the script is located if a previous installation is detected that location. | |
| Otherwise, it will fall to `/opt/kohya_ss`. If /opt is not writeable, the fallback is `$HOME/kohya_ss`. Lastly, if all else fails it will simply install to the current folder you are in (PWD). | |
| On macOS and other non-Linux machines, it will first try to detect an install where the script is run from and then run setup there if that's detected. | |
| If a previous install isn't found at that location, then it will default install to `$HOME/kohya_ss` followed by where you're currently at if there's no access to $HOME. | |
| You can override this behavior by specifying an install directory with the -d option. | |
| If you are using the interactive mode, our default values for the accelerate config screen after running the script answer "This machine", "None", "No" for the remaining questions. | |
| These are the same answers as the Windows install. | |
| ### Windows | |
| - Install [Python 3.10](https://www.python.org/ftp/python/3.10.9/python-3.10.9-amd64.exe) | |
| - make sure to tick the box to add Python to the 'PATH' environment variable | |
| - Install [Git](https://git-scm.com/download/win) | |
| - Install [Visual Studio 2015, 2017, 2019, and 2022 redistributable](https://aka.ms/vs/17/release/vc_redist.x64.exe) | |
| In the terminal, run: | |
| ``` | |
| git clone https://github.com/bmaltais/kohya_ss.git | |
| cd kohya_ss | |
| .\setup.bat | |
| ``` | |
| If this is a 1st install answer No when asked `Do you want to uninstall previous versions of torch and associated files before installing`. | |
| Then configure accelerate with the same answers as in the MacOS instructions when prompted. | |
| ### Optional: CUDNN 8.6 | |
| This step is optional but can improve the learning speed for NVIDIA 30X0/40X0 owners. It allows for larger training batch size and faster training speed. | |
| Due to the file size, I can't host the DLLs needed for CUDNN 8.6 on Github. I strongly advise you download them for a speed boost in sample generation (almost 50% on 4090 GPU) you can download them [here](https://b1.thefileditch.ch/mwxKTEtelILoIbMbruuM.zip). | |
| To install, simply unzip the directory and place the `cudnn_windows` folder in the root of the this repo. | |
| Run the following commands to install: | |
| ``` | |
| .\venv\Scripts\activate | |
| python .\tools\cudann_1.8_install.py | |
| ``` | |
| Once the commands have completed successfully you should be ready to use the new version. MacOS support is not tested and has been mostly taken from https://gist.github.com/jstayco/9f5733f05b9dc29de95c4056a023d645 | |
| ## Upgrading | |
| The following commands will work from the root directory of the project if you'd prefer to not run scripts. | |
| These commands will work on any OS. | |
| ```bash | |
| git pull | |
| .\venv\Scripts\activate | |
| pip install --use-pep517 --upgrade -r requirements.txt | |
| ``` | |
| ### Windows Upgrade | |
| When a new release comes out, you can upgrade your repo with the following commands in the root directory: | |
| ```powershell | |
| upgrade.bat | |
| ``` | |
| ### Linux and macOS Upgrade | |
| You can cd into the root directory and simply run | |
| ```bash | |
| # Refresh and update everything | |
| ./setup.sh | |
| # This will refresh everything, but NOT clone or pull the git repo. | |
| ./setup.sh --no-git-update | |
| ``` | |
| Once the commands have completed successfully you should be ready to use the new version. | |
| # Starting GUI Service | |
| The following command line arguments can be passed to the scripts on any OS to configure the underlying service. | |
| ``` | |
| --listen: the IP address to listen on for connections to Gradio. | |
| --username: a username for authentication. | |
| --password: a password for authentication. | |
| --server_port: the port to run the server listener on. | |
| --inbrowser: opens the Gradio UI in a web browser. | |
| --share: shares the Gradio UI. | |
| ``` | |
| ### Launching the GUI on Windows | |
| The two scripts to launch the GUI on Windows are gui.ps1 and gui.bat in the root directory. | |
| You can use whichever script you prefer. | |
| To launch the Gradio UI, run the script in a terminal with the desired command line arguments, for example: | |
| `gui.ps1 --listen 127.0.0.1 --server_port 7860 --inbrowser --share` | |
| or | |
| `gui.bat --listen 127.0.0.1 --server_port 7860 --inbrowser --share` | |
| ## Launching the GUI on Linux and macOS | |
| Run the launcher script with the desired command line arguments similar to Windows. | |
| `gui.sh --listen 127.0.0.1 --server_port 7860 --inbrowser --share` | |
| ## Launching the GUI directly using kohya_gui.py | |
| To run the GUI directly bypassing the wrapper scripts, simply use this command from the root project directory: | |
| ``` | |
| .\venv\Scripts\activate | |
| python .\kohya_gui.py | |
| ``` | |
| ## Dreambooth | |
| You can find the dreambooth solution specific here: [Dreambooth README](train_db_README.md) | |
| ## Finetune | |
| You can find the finetune solution specific here: [Finetune README](fine_tune_README.md) | |
| ## Train Network | |
| You can find the train network solution specific here: [Train network README](train_network_README.md) | |
| ## LoRA | |
| Training a LoRA currently uses the `train_network.py` code. You can create a LoRA network by using the all-in-one `gui.cmd` or by running the dedicated LoRA training GUI with: | |
| ``` | |
| .\venv\Scripts\activate | |
| python lora_gui.py | |
| ``` | |
| Once you have created the LoRA network, you can generate images via auto1111 by installing [this extension](https://github.com/kohya-ss/sd-webui-additional-networks). | |
| ### Naming of LoRA | |
| The LoRA supported by `train_network.py` has been named to avoid confusion. The documentation has been updated. The following are the names of LoRA types in this repository. | |
| 1. __LoRA-LierLa__ : (LoRA for __Li__ n __e__ a __r__ __La__ yers) | |
| LoRA for Linear layers and Conv2d layers with 1x1 kernel | |
| 2. __LoRA-C3Lier__ : (LoRA for __C__ olutional layers with __3__ x3 Kernel and __Li__ n __e__ a __r__ layers) | |
| In addition to 1., LoRA for Conv2d layers with 3x3 kernel | |
| LoRA-LierLa is the default LoRA type for `train_network.py` (without `conv_dim` network arg). LoRA-LierLa can be used with [our extension](https://github.com/kohya-ss/sd-webui-additional-networks) for AUTOMATIC1111's Web UI, or with the built-in LoRA feature of the Web UI. | |
| To use LoRA-C3Liar with Web UI, please use our extension. | |
| ## Sample image generation during training | |
| A prompt file might look like this, for example | |
| ``` | |
| # prompt 1 | |
| masterpiece, best quality, (1girl), in white shirts, upper body, looking at viewer, simple background --n low quality, worst quality, bad anatomy,bad composition, poor, low effort --w 768 --h 768 --d 1 --l 7.5 --s 28 | |
| # prompt 2 | |
| masterpiece, best quality, 1boy, in business suit, standing at street, looking back --n (low quality, worst quality), bad anatomy,bad composition, poor, low effort --w 576 --h 832 --d 2 --l 5.5 --s 40 | |
| ``` | |
| Lines beginning with `#` are comments. You can specify options for the generated image with options like `--n` after the prompt. The following can be used. | |
| * `--n` Negative prompt up to the next option. | |
| * `--w` Specifies the width of the generated image. | |
| * `--h` Specifies the height of the generated image. | |
| * `--d` Specifies the seed of the generated image. | |
| * `--l` Specifies the CFG scale of the generated image. | |
| * `--s` Specifies the number of steps in the generation. | |
| The prompt weighting such as `( )` and `[ ]` are working. | |
| ## Troubleshooting | |
| ### Page File Limit | |
| - X error relating to `page file`: Increase the page file size limit in Windows. | |
| ### No module called tkinter | |
| - Re-install [Python 3.10](https://www.python.org/ftp/python/3.10.9/python-3.10.9-amd64.exe) on your system. | |
| ### FileNotFoundError | |
| This is usually related to an installation issue. Make sure you do not have any python modules installed locally that could conflict with the ones installed in the venv: | |
| 1. Open a new powershell terminal and make sure no venv is active. | |
| 2. Run the following commands: | |
| ``` | |
| pip freeze > uninstall.txt | |
| pip uninstall -r uninstall.txt | |
| ``` | |
| This will store a backup file with your current locally installed pip packages and then uninstall them. Then, redo the installation instructions within the kohya_ss venv. | |
| ## Change History | |
| * 2023/04/22 (v21.5.5) | |
| - Update LoRA merge GUI to support SD checkpoint merge and up to 4 LoRA merging | |
| - Fixed `lora_interrogator.py` not working. Please refer to [PR #392](https://github.com/kohya-ss/sd-scripts/pull/392) for details. Thank you A2va and heyalexchoi! | |
| - Fixed the handling of tags containing `_` in `tag_images_by_wd14_tagger.py`. | |
| - Add new Extract DyLoRA gui to the Utilities tab. | |
| - Add new Merge LyCORIS models into checkpoint gui to the Utilities tab. | |
| - Add new info on startup to help debug things | |
| * 2023/04/17 (v21.5.4) | |
| - Fixed a bug that caused an error when loading DyLoRA with the `--network_weight` option in `train_network.py`. | |
| - Added the `--recursive` option to each script in the `finetune` folder to process folders recursively. Please refer to [PR #400](https://github.com/kohya-ss/sd-scripts/pull/400/) for details. Thanks to Linaqruf! | |
| - Upgrade Gradio to latest release | |
| - Fix issue when Adafactor is used as optimizer and LR Warmup is not 0: https://github.com/bmaltais/kohya_ss/issues/617 | |
| - Added support for DyLoRA in `train_network.py`. Please refer to [here](./train_network_README-ja.md#dylora) for details (currently only in Japanese). | |
| - Added support for caching latents to disk in each training script. Please specify __both__ `--cache_latents` and `--cache_latents_to_disk` options. | |
| - The files are saved in the same folder as the images with the extension `.npz`. If you specify the `--flip_aug` option, the files with `_flip.npz` will also be saved. | |
| - Multi-GPU training has not been tested. | |
| - This feature is not tested with all combinations of datasets and training scripts, so there may be bugs. | |
| - Added workaround for an error that occurs when training with `fp16` or `bf16` in `fine_tune.py`. | |
| - Implemented DyLoRA GUI support. There will now be a new 'DyLoRA Unit` slider when the LoRA type is selected as `kohya DyLoRA` to specify the desired Unit value for DyLoRA training. | |
| - Update gui.bat and gui.ps1 based on: https://github.com/bmaltais/kohya_ss/issues/188 | |
| - Update `setup.bat` to install torch 2.0.0 instead of 1.2.1. If you want to upgrade from 1.2.1 to 2.0.0 run setup.bat again, select 1 to uninstall the previous torch modules, then select 2 for torch 2.0.0 | |
| * 2023/04/09 (v21.5.2) | |
| - Added support for training with weighted captions. Thanks to AI-Casanova for the great contribution! | |
| - Please refer to the PR for details: [PR #336](https://github.com/kohya-ss/sd-scripts/pull/336) | |
| - Specify the `--weighted_captions` option. It is available for all training scripts except Textual Inversion and XTI. | |
| - This option is also applicable to token strings of the DreamBooth method. | |
| - The syntax for weighted captions is almost the same as the Web UI, and you can use things like `(abc)`, `[abc]`, and `(abc:1.23)`. Nesting is also possible. | |
| - If you include a comma in the parentheses, the parentheses will not be properly matched in the prompt shuffle/dropout, so do not include a comma in the parentheses. | |
| - Run gui.sh from any place | |