InvokeAI/scripts/preload_models.py

#!/usr/bin/env python
# Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)
# Before running stable-diffusion on an internet-isolated machine,
# run this script from one with internet connectivity. The
# two machines must share a common .cache directory.

import warnings
import load_models

if __name__ == '__main__':
    load_models.main()
This commit separates the InvokeAI source code from end-user files - preload_models.py has been renamed load_models.py. I've left a shell legacy version with the previous name to avoid breaking any code. - The load_models.py script now takes an optional --root argument, which points to an install directory for the models, scripts, config files, and the default outputs directory. In the future, the embeddings manager directory will also be stored here. - If no --root is provided, and no init file or environment variable is present, load_models.py will install to '.' by default, which is the current behavior. (This has not been tested thoroughly.) - The location of the root directory is stored in the file .invokeai in the user's home directory ($HOME on Linux/Mac, or HOMEPATH on windows). The load_models.py script creates this file if it does not already exist. - invoke.py and load_models.py use the following search path to find the install directory: 1. Contents of the environment variable INVOKEAI_ROOT 2. The --root=XXXXX option in ~/.invokeai 3. The --root option passed on the script command line. 4. As a last gasp, the currently working directory (".") Running `python scripts/load_models.py --root ~/invokeai` will create a directory structured like this (shortened for clarity): ~/invokeai ├── configs │ ├── models.yaml │ └── stable-diffusion │ ├── v1-finetune.yaml │ ├── v1-finetune_style.yaml │ ├── v1-inference.yaml │ ├── v1-inpainting-inference.yaml │ └── v1-m1-finetune.yaml ├── models │ ├── CompVis │ ├── bert-base-uncased │ ├── clipseg │ ├── codeformer │ ├── gfpgan │ ├── ldm │ │ └── stable-diffusion-v1 │ │ ├── sd-v1-5-inpainting.ckpt │ │ └── vae-ft-mse-840000-ema-pruned.ckpt │ └── openai ├── outputs └── scripts ├── dream.py ├── images2prompt.py ├── invoke.py ├── legacy_api.py ├── load_models.py ├── merge_embeddings.py ├── orig_scripts │ ├── download_first_stages.sh │ ├── train_searcher.py │ └── txt2img.py ├── preload_models.py └── sd-metadata.py 1. You can now run invoke.py anywhere! Just copy it to one of your bin directories, or put the ~/invokeai/scripts onto your PATH. 2. git pulls will no longer fight with you over models.yaml 3. It keeps end users out of the source code repo and will create a path for us to do installs from invokeai.tar.gz. 2022-11-15 17:59:00 +00:00			`#!/usr/bin/env python`
added assertion checks for out-of-bound arguments; added various copyright and license agreement files 2022-08-24 13:22:04 +00:00			`# Copyright (c) 2022 Lincoln D. Stein (https://github.com/lstein)`
simplified instructions to preload Bert and kornia prerequisites; fixed --grid and --batch handling; added timing information after image generation 2022-08-17 16:00:00 +00:00			`# Before running stable-diffusion on an internet-isolated machine,`
			`# run this script from one with internet connectivity. The`
			`# two machines must share a common .cache directory.`
adjusted instructions for the released stable-diffusion-v1 weights 2022-08-22 19:33:27 +00:00
attempt to make batch install more reliable 1. added nvidia channel to environment.yml 2. updated pytorch-cuda requirement 3. let conda figure out what version of pytorch to install 4. add conda install status checking to .bat and .sh install files 5. in preload_models.py catch and handle download/access token errors 2022-11-01 16:02:22 +00:00			`import warnings`
This commit separates the InvokeAI source code from end-user files - preload_models.py has been renamed load_models.py. I've left a shell legacy version with the previous name to avoid breaking any code. - The load_models.py script now takes an optional --root argument, which points to an install directory for the models, scripts, config files, and the default outputs directory. In the future, the embeddings manager directory will also be stored here. - If no --root is provided, and no init file or environment variable is present, load_models.py will install to '.' by default, which is the current behavior. (This has not been tested thoroughly.) - The location of the root directory is stored in the file .invokeai in the user's home directory ($HOME on Linux/Mac, or HOMEPATH on windows). The load_models.py script creates this file if it does not already exist. - invoke.py and load_models.py use the following search path to find the install directory: 1. Contents of the environment variable INVOKEAI_ROOT 2. The --root=XXXXX option in ~/.invokeai 3. The --root option passed on the script command line. 4. As a last gasp, the currently working directory (".") Running `python scripts/load_models.py --root ~/invokeai` will create a directory structured like this (shortened for clarity): ~/invokeai ├── configs │ ├── models.yaml │ └── stable-diffusion │ ├── v1-finetune.yaml │ ├── v1-finetune_style.yaml │ ├── v1-inference.yaml │ ├── v1-inpainting-inference.yaml │ └── v1-m1-finetune.yaml ├── models │ ├── CompVis │ ├── bert-base-uncased │ ├── clipseg │ ├── codeformer │ ├── gfpgan │ ├── ldm │ │ └── stable-diffusion-v1 │ │ ├── sd-v1-5-inpainting.ckpt │ │ └── vae-ft-mse-840000-ema-pruned.ckpt │ └── openai ├── outputs └── scripts ├── dream.py ├── images2prompt.py ├── invoke.py ├── legacy_api.py ├── load_models.py ├── merge_embeddings.py ├── orig_scripts │ ├── download_first_stages.sh │ ├── train_searcher.py │ └── txt2img.py ├── preload_models.py └── sd-metadata.py 1. You can now run invoke.py anywhere! Just copy it to one of your bin directories, or put the ~/invokeai/scripts onto your PATH. 2. git pulls will no longer fight with you over models.yaml 3. It keeps end users out of the source code repo and will create a path for us to do installs from invokeai.tar.gz. 2022-11-15 17:59:00 +00:00			`import load_models`
add more step-by-step documentation and links 2022-10-29 13:18:48 +00:00
add support for safety checker (NSFW filter) Now you can activate the Hugging Face `diffusers` library safety check for NSFW and other potentially disturbing imagery. To turn on the safety check, pass --safety_checker at the command line. For developers, the flag is `safety_checker=True` passed to ldm.generate.Generate(). Once the safety checker is turned on, it cannot be turned off unless you reinitialize a new Generate object. When the safety checker is active, suspect images will be blurred and a warning icon is added. There is also a warning message printed in the CLI, but it can be a little hard to see because of its positioning in the output stream. There is a slight but noticeable delay when the safety checker runs. Note that invisible watermarking is not currently implemented. The watermark code distributed by the CompViz distribution uses a library that does not seem to be able to retrieve the watermarks it creates, and it does not appear that Hugging Face `diffusers` or other SD distributions are doing any watermarking. 2022-10-24 02:26:18 +00:00			`if __name__ == '__main__':`
This commit separates the InvokeAI source code from end-user files - preload_models.py has been renamed load_models.py. I've left a shell legacy version with the previous name to avoid breaking any code. - The load_models.py script now takes an optional --root argument, which points to an install directory for the models, scripts, config files, and the default outputs directory. In the future, the embeddings manager directory will also be stored here. - If no --root is provided, and no init file or environment variable is present, load_models.py will install to '.' by default, which is the current behavior. (This has not been tested thoroughly.) - The location of the root directory is stored in the file .invokeai in the user's home directory ($HOME on Linux/Mac, or HOMEPATH on windows). The load_models.py script creates this file if it does not already exist. - invoke.py and load_models.py use the following search path to find the install directory: 1. Contents of the environment variable INVOKEAI_ROOT 2. The --root=XXXXX option in ~/.invokeai 3. The --root option passed on the script command line. 4. As a last gasp, the currently working directory (".") Running `python scripts/load_models.py --root ~/invokeai` will create a directory structured like this (shortened for clarity): ~/invokeai ├── configs │ ├── models.yaml │ └── stable-diffusion │ ├── v1-finetune.yaml │ ├── v1-finetune_style.yaml │ ├── v1-inference.yaml │ ├── v1-inpainting-inference.yaml │ └── v1-m1-finetune.yaml ├── models │ ├── CompVis │ ├── bert-base-uncased │ ├── clipseg │ ├── codeformer │ ├── gfpgan │ ├── ldm │ │ └── stable-diffusion-v1 │ │ ├── sd-v1-5-inpainting.ckpt │ │ └── vae-ft-mse-840000-ema-pruned.ckpt │ └── openai ├── outputs └── scripts ├── dream.py ├── images2prompt.py ├── invoke.py ├── legacy_api.py ├── load_models.py ├── merge_embeddings.py ├── orig_scripts │ ├── download_first_stages.sh │ ├── train_searcher.py │ └── txt2img.py ├── preload_models.py └── sd-metadata.py 1. You can now run invoke.py anywhere! Just copy it to one of your bin directories, or put the ~/invokeai/scripts onto your PATH. 2. git pulls will no longer fight with you over models.yaml 3. It keeps end users out of the source code repo and will create a path for us to do installs from invokeai.tar.gz. 2022-11-15 17:59:00 +00:00			`load_models.main()`
clipseg library and environment in place 2022-10-16 20:45:07 +00:00