- This PR adds support for embedding files that contain a single key
"emb_params". The only example I know of this format is the
"EasyNegative" embedding on HuggingFace, but there are certainly
others.
- This PR also adds support for loading embedding files that have been
saved in safetensors format.
- It also cleans up the code so that the logic of probing for and
selecting the right format parser is clear.
- Commands, invocations and their parameters will now autocomplete
using introspection.
- Two types of parameter *arguments* will also autocomplete:
- --sampler_name will autocomplete the scheduler name
- --model will autocomplete the model name
- There don't seem to be commands for reading/writing image files yet, so
path autocompletion is not implemented
- resolve conflicts with generate.py invocation
- remove unused symbols that pyflakes complains about
- add **untested** code for passing intermediate latent image to the
step callback in the format expected.
This PR fixes#2951 and restores the step_callback argument in the
refactored generate() method. Note that this issue states that
"something is still wrong because steps and step are zero." However,
I think this is confusion over the call signature of the callback, which
since the diffusers merge has been `callback(state:PipelineIntermediateState)`
This is the test script that I used to determine that `step` is being passed
correctly:
```
from pathlib import Path
from invokeai.backend import ModelManager, PipelineIntermediateState
from invokeai.backend.globals import global_config_dir
from invokeai.backend.generator import Txt2Img
def my_callback(state:PipelineIntermediateState, total_steps:int):
print(f'callback(step={state.step}/{total_steps})')
def main():
manager = ModelManager(Path(global_config_dir()) / "models.yaml")
model = manager.get_model('stable-diffusion-1.5')
print ('=== TXT2IMG TEST ===')
steps=30
output = next(Txt2Img(model).generate(prompt='banana sushi',
iterations=None,
steps=steps,
step_callback=lambda x: my_callback(x,steps)
)
)
print(f'image={output.image}, seed={output.seed}, steps={output.params.steps}')
if __name__=='__main__':
main()
```
Currently translated at 100.0% (504 of 504 strings)
translationBot(ui): update translation (Spanish)
Currently translated at 100.0% (501 of 501 strings)
Co-authored-by: gallegonovato <fran-carro@hotmail.es>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/es/
Translation: InvokeAI/Web UI
Currently translated at 100.0% (504 of 504 strings)
translationBot(ui): update translation (Italian)
Currently translated at 100.0% (501 of 501 strings)
translationBot(ui): update translation (Italian)
Currently translated at 100.0% (500 of 500 strings)
Co-authored-by: Riccardo Giovanetti <riccardo.giovanetti@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/it/
Translation: InvokeAI/Web UI
This PR fixes#2951 and restores the step_callback argument in the
refactored generate() method. Note that this issue states that
"something is still wrong because steps and step are zero." However,
I think this is confusion over the call signature of the callback, which
since the diffusers merge has been `callback(state:PipelineIntermediateState)`
This is the test script that I used to determine that `step` is being passed
correctly:
```
from pathlib import Path
from invokeai.backend import ModelManager, PipelineIntermediateState
from invokeai.backend.globals import global_config_dir
from invokeai.backend.generator import Txt2Img
def my_callback(state:PipelineIntermediateState, total_steps:int):
print(f'callback(step={state.step}/{total_steps})')
def main():
manager = ModelManager(Path(global_config_dir()) / "models.yaml")
model = manager.get_model('stable-diffusion-1.5')
print ('=== TXT2IMG TEST ===')
steps=30
output = next(Txt2Img(model).generate(prompt='banana sushi',
iterations=None,
steps=steps,
step_callback=lambda x: my_callback(x,steps)
)
)
print(f'image={output.image}, seed={output.seed}, steps={output.params.steps}')
if __name__=='__main__':
main()
```
- This PR turns on pickle scanning before a legacy checkpoint file
is loaded from disk within the checkpoint_to_diffusers module.
- Also miscellaneous diagnostic message cleanup.
- When a legacy checkpoint model is loaded via --convert_ckpt and its
models.yaml stanza refers to a custom VAE path (using the 'vae:'
key), the custom VAE will be converted and used within the diffusers
model. Otherwise the VAE contained within the legacy model will be
used.
- Note that the heuristic_import() method, which imports arbitrary
legacy files on disk and URLs, will continue to default to the
the standard stabilityai/sd-vae-ft-mse VAE. This can be fixed after
the fact by editing the models.yaml stanza using the Web or CLI
UIs.
- Fixes issue #2917
- The value of png_compression was always 6, despite the value provided to the
--png_compression argument. This fixes the bug.
- It also fixes an inconsistency between the maximum range of png_compression
and the help text.
- Closes#2945
Prior to this commit, all models would be loaded with the extremely unsafe `torch.load` method, except those with the exact extension `.safetensors`. Even a change in casing (eg. `saFetensors`, `Safetensors`, etc) would cause the file to be loaded with torch.load instead of the much safer `safetensors.toch.load_file`.
If a malicious actor renamed an infected `.ckpt` to something like `.SafeTensors` or `.SAFETENSORS` an unsuspecting user would think they are loading a safe .safetensor, but would in fact be parsing an unsafe pickle file, and executing an attacker's payload. This commit fixes this vulnerability by reversing the loading-method decision logic to only use the unsafe `torch.load` when the file extension is exactly `.ckpt`.
fix(ui): remove old scrollbar css
fix(ui): make guidepopover lazy
feat(ui): wip resizable drawer
feat(ui): wip resizable drawer
feat(ui): add scroll-linked shadow
feat(ui): organize files
Align Scrollbar next to content
Move resizable drawer underneath the progress bar
Add InvokeLogo to unpinned & align
Adds Invoke Logo to Unpinned Parameters panel and aligns to make it feel seamless.
Currently translated at 100.0% (500 of 500 strings)
translationBot(ui): update translation (Italian)
Currently translated at 100.0% (500 of 500 strings)
translationBot(ui): update translation (Italian)
Currently translated at 100.0% (482 of 482 strings)
translationBot(ui): update translation (Italian)
Currently translated at 100.0% (480 of 480 strings)
Co-authored-by: Riccardo Giovanetti <riccardo.giovanetti@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/it/
Translation: InvokeAI/Web UI
Currently translated at 100.0% (500 of 500 strings)
translationBot(ui): update translation (Spanish)
Currently translated at 100.0% (482 of 482 strings)
translationBot(ui): update translation (Spanish)
Currently translated at 100.0% (480 of 480 strings)
Co-authored-by: gallegonovato <fran-carro@hotmail.es>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/es/
Translation: InvokeAI/Web UI
Cause of the problem was inadvertent activation of the safety checker.
When conversion occurs on disk, the safety checker is disabled during loading.
However, when converting in RAM, the safety checker was not removed, resulting
in it activating even when user specified --no-nsfw_checker.
This PR fixes the problem by detecting when the caller has requested the InvokeAi
StableDiffusionGeneratorPipeline class to be returned and setting safety checker
to None. Do not do this with diffusers models destined for disk because then they
will be incompatible with the merge script!!
Closes#2836
Some schedulers report not only the noisy latents at the current timestep,
but also their estimate so far of what the de-noised latents will be.
It makes for a more legible preview than the noisy latents do.
* Fix img2img and inpainting code so a strength of 1 behaves the same as txt2img.
* Make generated images identical to their txt2img counterparts when strength is 1.
There are actually two Stable Diffusion v2 legacy checkpoint
configurations:
1) "epsilon" prediction type for Stable Diffusion v2 Base
2) "v-prediction" type for Stable Diffusion v2-768
This commit adds the configuration file needed for epsilon prediction
type models as well as the UI that prompts the user to select the
appropriate configuration file when the code can't do so
automatically.
build(ui): fix husky path
build(ui): fix hmr issue, remove emotion cache
build(ui): clean up package.json
build(ui): update gh action and npm scripts
feat(ui): wip port lightbox to chakra theme
feat(ui): wip use chakra theme tokens
feat(ui): Add status text to main loading spinner
feat(ui): wip chakra theme tweaking
feat(ui): simply iaisimplemenu button
feat(ui): wip chakra theming
feat(ui): Theme Management
feat(ui): Add Ocean Blue Theme
feat(ui): wip lightbox
fix(ui): fix lightbox mouse
feat(ui): set default theme variants
feat(ui): model manager chakra theme
chore(ui): lint
feat(ui): remove last scss
feat(ui): fix switch theme
feat(ui): Theme Cleanup
feat(ui): Stylize Search Models Found List
feat(ui): hide scrollbars
feat(ui): fix floating button position
feat(ui): Scrollbar Styling
fix broken scripts
This PR fixes the following scripts:
1) Scripts that can be executed within the repo's scripts directory.
Note that these are for development testing and are not intended
to be exposed to the user.
configure_invokeai.py - configuration
dream.py - the legacy CLI
images2prompt.py - legacy "dream prompt" retriever
invoke-new.py - new nodes-based CLI
invoke.py - the legacy CLI under another name
make_models_markdown_table.py - a utility used during the release/doc process
pypi_helper.py - another utility used during the release process
sd-metadata.py - retrieve JSON-formatted metadata from a PNG file
2) Scripts that are installed by pip install. They get placed into the venv's
PATH and are intended to be the official entry points:
invokeai-node-cli - new nodes-based CLI
invokeai-node-web - new nodes-based web server
invokeai - legacy CLI
invokeai-configure - install time configuration script
invokeai-merge - model merging script
invokeai-ti - textual inversion script
invokeai-model-install - model installer
invokeai-update - update script
invokeai-metadata" - retrieve JSON-formatted metadata from PNG files
protect invocations against black autoformatting
deps: upgrade to diffusers 0.14, safetensors 0.3, transformers 4.26, accelerate 0.16
This PR fixes the following scripts:
1) Scripts that can be executed within the repo's scripts directory.
Note that these are for development testing and are not intended
to be exposed to the user.
configure_invokeai.py - configuration
dream.py - the legacy CLI
images2prompt.py - legacy "dream prompt" retriever
invoke-new.py - new nodes-based CLI
invoke.py - the legacy CLI under another name
make_models_markdown_table.py - a utility used during the release/doc process
pypi_helper.py - another utility used during the release process
sd-metadata.py - retrieve JSON-formatted metadata from a PNG file
2) Scripts that are installed by pip install. They get placed into the venv's
PATH and are intended to be the official entry points:
invokeai-node-cli - new nodes-based CLI
invokeai-node-web - new nodes-based web server
invokeai - legacy CLI
invokeai-configure - install time configuration script
invokeai-merge - model merging script
invokeai-ti - textual inversion script
invokeai-model-install - model installer
invokeai-update - update script
invokeai-metadata" - retrieve JSON-formatted metadata from PNG files
This is the first phase of a big shifting of files and directories
in the source tree.
You will need to run `pip install -e .` before the code will work again!
Here's what's in the current commit:
1) Remove a lot of dead code that dealt with checkpoint and safetensor loading.
2) Entire ckpt_generator hierarchy is now gone!
3) ldm.invoke.generator.* => invokeai.generator.*
4) ldm.model.* => invokeai.model.*
5) ldm.invoke.model_manager => invokeai.model.model_manager
6) In addition, a number of frequently-accessed classes can be imported
from the invokeai.model and invokeai.generator modules:
from invokeai.generator import ( Generator, PipelineIntermediateState,
StableDiffusionGeneratorPipeline, infill_methods)
from invokeai.models import ( ModelManager, SDLegacyType
InvokeAIDiffuserComponent, AttentionMapSaver,
DDIMSampler, KSampler, PLMSSampler,
PostprocessingSettings )
- Final list can be found in invokeai/configs/INITIAL_MODELS.yaml
- After installing all the models, I discovered a bug in the file
selection form that caused a crash when no remaining uninstalled
models remained. So had to fix this.
Currently translated at 81.4% (382 of 469 strings)
translationBot(ui): update translation (Russian)
Currently translated at 81.6% (382 of 468 strings)
Co-authored-by: Sergey Krashevich <svk@svk.su>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/ru/
Translation: InvokeAI/Web UI
Currently translated at 100.0% (469 of 469 strings)
translationBot(ui): update translation (Italian)
Currently translated at 100.0% (468 of 468 strings)
Co-authored-by: Riccardo Giovanetti <riccardo.giovanetti@gmail.com>
Translate-URL: https://hosted.weblate.org/projects/invokeai/web-ui/it/
Translation: InvokeAI/Web UI
This bug is related to the format in which we stored prompts for some time: an array of weighted subprompts.
This caused some strife when recalling a prompt if the prompt had colons in it, due to our recently introduced handling of negative prompts.
Currently there is no need to store a prompt as anything other than a string, so we revert to doing that.
Compatibility with structured prompts is maintained via helper hook.
Enhancements:
1. Directory-based imports will not attempt to import components of diffusers models.
2. Diffuser directory imports now supported
3. Files that end with .ckpt that are not Stable Diffusion models (such as VAEs) are
skipped during import.
Bugs identified in Psychedelicious's review:
1. The invokeai-configure form now tracks the current contents of `invokeai.init` correctly.
2. The autoencoders are no longer treated like installable models, but instead are
mandatory support models. They will no longer appear in `models.yaml`
Bugs identified in Damian's review:
1. If invokeai-model-install is started before the root directory is initialized, it will
call invokeai-configure to fix the matter.
2. Fix bug that was causing empty `models.yaml` under certain conditions.
3. Made import textbox smaller
4. Hide the "convert to diffusers" options if nothing to import.
After upgrading the deps, the full screen hotkey started to bug out. I believe this was happening because it was triggered in two different components causing it to run twice. Removed it from both floating buttons and moved it to the Invoke tab. Makes sense to keep it there as it is a global hotkey.
After the recent changes the Cancel button wasn't maintaining min height in floating mode. Also the new button group was not scaling in width correctly on the Canvas Beta UI. Fixed both.
- Upgraded all dependencies
- Removed beta TS 5.0 as it conflicted with some packages
- Added types for `Array.prototype.findLast` and `Array.prototype.findLastIndex` (these definitions are provided in TS 5.0
- Fixed fixed type import syntax in a few components
- Re-patched `redux-deep-persist` and tested to ensure the patch still works
