There are some bugs with it that I cannot figure out related to `floating-ui` and `downshift`'s handling of refs.
Will need to revisit this component in the future.
* Testing change to LatentsToText to allow setting different cfg_scale values per diffusion step.
* Adding first attempt at float param easing node, using Penner easing functions.
* Core implementation of ControlNet and MultiControlNet.
* Added support for ControlNet and MultiControlNet to legacy non-nodal Txt2Img in backend/generator. Although backend/generator will likely disappear by v3.x, right now they are very useful for testing core ControlNet and MultiControlNet functionality while node codebase is rapidly evolving.
* Added example of using ControlNet with legacy Txt2Img generator
* Resolving rebase conflict
* Added first controlnet preprocessor node for canny edge detection.
* Initial port of controlnet node support from generator-based TextToImageInvocation node to latent-based TextToLatentsInvocation node
* Switching to ControlField for output from controlnet nodes.
* Resolving conflicts in rebase to origin/main
* Refactored ControlNet nodes so they subclass from PreprocessedControlInvocation, and only need to override run_processor(image) (instead of reimplementing invoke())
* changes to base class for controlnet nodes
* Added HED, LineArt, and OpenPose ControlNet nodes
* Added an additional "raw_processed_image" output port to controlnets, mainly so could route ImageField to a ShowImage node
* Added more preprocessor nodes for:
MidasDepth
ZoeDepth
MLSD
NormalBae
Pidi
LineartAnime
ContentShuffle
Removed pil_output options, ControlNet preprocessors should always output as PIL. Removed diagnostics and other general cleanup.
* Prep for splitting pre-processor and controlnet nodes
* Refactored controlnet nodes: split out controlnet stuff into separate node, stripped controlnet stuff form image processing/analysis nodes.
* Added resizing of controlnet image based on noise latent. Fixes a tensor mismatch issue.
* More rebase repair.
* Added support for using multiple control nets. Unfortunately this breaks direct usage of Control node output port ==> TextToLatent control input port -- passing through a Collect node is now required. Working on fixing this...
* Fixed use of ControlNet control_weight parameter
* Fixed lint-ish formatting error
* Core implementation of ControlNet and MultiControlNet.
* Added first controlnet preprocessor node for canny edge detection.
* Initial port of controlnet node support from generator-based TextToImageInvocation node to latent-based TextToLatentsInvocation node
* Switching to ControlField for output from controlnet nodes.
* Refactored controlnet node to output ControlField that bundles control info.
* changes to base class for controlnet nodes
* Added more preprocessor nodes for:
MidasDepth
ZoeDepth
MLSD
NormalBae
Pidi
LineartAnime
ContentShuffle
Removed pil_output options, ControlNet preprocessors should always output as PIL. Removed diagnostics and other general cleanup.
* Prep for splitting pre-processor and controlnet nodes
* Refactored controlnet nodes: split out controlnet stuff into separate node, stripped controlnet stuff form image processing/analysis nodes.
* Added resizing of controlnet image based on noise latent. Fixes a tensor mismatch issue.
* Cleaning up TextToLatent arg testing
* Cleaning up mistakes after rebase.
* Removed last bits of dtype and and device hardwiring from controlnet section
* Refactored ControNet support to consolidate multiple parameters into data struct. Also redid how multiple controlnets are handled.
* Added support for specifying which step iteration to start using
each ControlNet, and which step to end using each controlnet (specified as fraction of total steps)
* Cleaning up prior to submitting ControlNet PR. Mostly turning off diagnostic printing. Also fixed error when there is no controlnet input.
* Added dependency on controlnet-aux v0.0.3
* Commented out ZoeDetector. Will re-instate once there's a controlnet-aux release that supports it.
* Switched CotrolNet node modelname input from free text to default list of popular ControlNet model names.
* Fix to work with current stable release of controlnet_aux (v0.0.3). Turned of pre-processor params that were added post v0.0.3. Also change defaults for shuffle.
* Refactored most of controlnet code into its own method to declutter TextToLatents.invoke(), and make upcoming integration with LatentsToLatents easier.
* Cleaning up after ControlNet refactor in TextToLatentsInvocation
* Extended node-based ControlNet support to LatentsToLatentsInvocation.
* chore(ui): regen api client
* fix(ui): add value to conditioning field
* fix(ui): add control field type
* fix(ui): fix node ui type hints
* fix(nodes): controlnet input accepts list or single controlnet
* Moved to controlnet_aux v0.0.4, reinstated Zoe controlnet preprocessor. Also in pyproject.toml had to specify downgrade of timm to 0.6.13 _after_ controlnet-aux installs timm >= 0.9.2, because timm >0.6.13 breaks Zoe preprocessor.
* Core implementation of ControlNet and MultiControlNet.
* Added first controlnet preprocessor node for canny edge detection.
* Switching to ControlField for output from controlnet nodes.
* Resolving conflicts in rebase to origin/main
* Refactored ControlNet nodes so they subclass from PreprocessedControlInvocation, and only need to override run_processor(image) (instead of reimplementing invoke())
* changes to base class for controlnet nodes
* Added HED, LineArt, and OpenPose ControlNet nodes
* Added more preprocessor nodes for:
MidasDepth
ZoeDepth
MLSD
NormalBae
Pidi
LineartAnime
ContentShuffle
Removed pil_output options, ControlNet preprocessors should always output as PIL. Removed diagnostics and other general cleanup.
* Prep for splitting pre-processor and controlnet nodes
* Refactored controlnet nodes: split out controlnet stuff into separate node, stripped controlnet stuff form image processing/analysis nodes.
* Added resizing of controlnet image based on noise latent. Fixes a tensor mismatch issue.
* Added support for using multiple control nets. Unfortunately this breaks direct usage of Control node output port ==> TextToLatent control input port -- passing through a Collect node is now required. Working on fixing this...
* Fixed use of ControlNet control_weight parameter
* Core implementation of ControlNet and MultiControlNet.
* Added first controlnet preprocessor node for canny edge detection.
* Initial port of controlnet node support from generator-based TextToImageInvocation node to latent-based TextToLatentsInvocation node
* Switching to ControlField for output from controlnet nodes.
* Refactored controlnet node to output ControlField that bundles control info.
* changes to base class for controlnet nodes
* Added more preprocessor nodes for:
MidasDepth
ZoeDepth
MLSD
NormalBae
Pidi
LineartAnime
ContentShuffle
Removed pil_output options, ControlNet preprocessors should always output as PIL. Removed diagnostics and other general cleanup.
* Prep for splitting pre-processor and controlnet nodes
* Refactored controlnet nodes: split out controlnet stuff into separate node, stripped controlnet stuff form image processing/analysis nodes.
* Added resizing of controlnet image based on noise latent. Fixes a tensor mismatch issue.
* Cleaning up TextToLatent arg testing
* Cleaning up mistakes after rebase.
* Removed last bits of dtype and and device hardwiring from controlnet section
* Refactored ControNet support to consolidate multiple parameters into data struct. Also redid how multiple controlnets are handled.
* Added support for specifying which step iteration to start using
each ControlNet, and which step to end using each controlnet (specified as fraction of total steps)
* Cleaning up prior to submitting ControlNet PR. Mostly turning off diagnostic printing. Also fixed error when there is no controlnet input.
* Commented out ZoeDetector. Will re-instate once there's a controlnet-aux release that supports it.
* Switched CotrolNet node modelname input from free text to default list of popular ControlNet model names.
* Fix to work with current stable release of controlnet_aux (v0.0.3). Turned of pre-processor params that were added post v0.0.3. Also change defaults for shuffle.
* Refactored most of controlnet code into its own method to declutter TextToLatents.invoke(), and make upcoming integration with LatentsToLatents easier.
* Cleaning up after ControlNet refactor in TextToLatentsInvocation
* Extended node-based ControlNet support to LatentsToLatentsInvocation.
* chore(ui): regen api client
* fix(ui): fix node ui type hints
* fix(nodes): controlnet input accepts list or single controlnet
* Added Mediapipe image processor for use as ControlNet preprocessor.
Also hacked in ability to specify HF subfolder when loading ControlNet models from string.
* Fixed bug where MediapipFaceProcessorInvocation was ignoring max_faces and min_confidence params.
* Added nodes for float params: ParamFloatInvocation and FloatCollectionOutput. Also added FloatOutput.
* Added mediapipe install requirement. Should be able to remove once controlnet_aux package adds mediapipe to its requirements.
* Added float to FIELD_TYPE_MAP ins constants.ts
* Progress toward improvement in fieldTemplateBuilder.ts getFieldType()
* Fixed controlnet preprocessors and controlnet handling in TextToLatents to work with revised Image services.
* Cleaning up from merge, re-adding cfg_scale to FIELD_TYPE_MAP
* Making sure cfg_scale of type list[float] can be used in image metadata, to support param easing for cfg_scale
* Fixed math for per-step param easing.
* Added option to show plot of param value at each step
* Just cleaning up after adding param easing plot option, removing vestigial code.
* Modified control_weight ControlNet param to be polistmorphic --
can now be either a single float weight applied for all steps, or a list of floats of size total_steps, that specifies weight for each step.
* Added more informative error message when _validat_edge() throws an error.
* Just improving parm easing bar chart title to include easing type.
* Added requirement for easing-functions package
* Taking out some diagnostic prints.
* Added option to use both easing function and mirror of easing function together.
* Fixed recently introduced problem (when pulled in main), triggered by num_steps in StepParamEasingInvocation not having a default value -- just added default.
---------
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
There was an issue where for graphs w/ iterations, your images were output all at once, at the very end of processing. So if you canceled halfway through an execution of 10 nodes, you wouldn't get any images - even though you'd completed 5 images' worth of inference.
## Cause
Because graphs executed breadth-first (i.e. depth-by-depth), leaf nodes were necessarily processed last. For image generation graphs, your `LatentsToImage` will be leaf nodes, and be the last depth to be executed.
For example, a `TextToLatents` graph w/ 3 iterations would execute all 3 `TextToLatents` nodes fully before moving to the next depth, where the `LatentsToImage` nodes produce output images, resulting in a node execution order like this:
1. TextToLatents
2. TextToLatents
3. TextToLatents
4. LatentsToImage
5. LatentsToImage
6. LatentsToImage
## Solution
This PR makes a two changes to graph execution to execute as deeply as it can along each branch of the graph.
### Eager node preparation
We now prepare as many nodes as possible, instead of just a single node at a time.
We also need to change the conditions in which nodes are prepared. Previously, nodes were prepared only when all of their direct ancestors were executed.
The updated logic prepares nodes that:
- are *not* `Iterate` nodes whose inputs have *not* been executed
- do *not* have any unexecuted `Iterate` ancestor nodes
This results in graphs always being maximally prepared.
### Always execute the deepest prepared node
We now choose the next node to execute by traversing from the bottom of the graph instead of the top, choosing the first node whose inputs are all executed.
This means we always execute the deepest node possible.
## Result
Graphs now execute depth-first, so instead of an execution order like this:
1. TextToLatents
2. TextToLatents
3. TextToLatents
4. LatentsToImage
5. LatentsToImage
6. LatentsToImage
... we get an execution order like this:
1. TextToLatents
2. LatentsToImage
3. TextToLatents
4. LatentsToImage
5. TextToLatents
6. LatentsToImage
Immediately after inference, the image is decoded and sent to the gallery.
fixes#3400
1. Contents of autoscan directory field are restored after doing an installation.
2. Activate dialogue to choose V2 parameterization when importing from a directory.
3. Remove autoscan directory from init file when its checkbox is unselected.
4. Add widget cycling behavior to install models form.
The processor is automatically selected when model is changed.
But if the user manually changes the processor, processor settings, or disables the new `Auto configure processor` switch, auto processing is disabled.
The user can enable auto configure by turning the switch back on.
When auto configure is enabled, a small dot is overlaid on the expand button to remind the user that the system is not auto configuring the processor for them.
If auto configure is enabled, the processor settings are reset to the default for the selected model.
Add uploading to IAIDndImage
- add `postUploadAction` arg to `imageUploaded` thunk, with several current valid options (set control image, set init, set nodes image, set canvas, or toast)
- updated IAIDndImage to optionally allow click to upload
- when the controlnet model is changed, if there is a default processor for the model set, the processor is changed.
- once a control image is selected (and processed), changing the model does not change the processor - must be manually changed
- Also fixed up order in which logger is created in invokeai-web
so that handlers are installed after command-line options are
parsed (and not before!)
This handles the case when an image is deleted but is still in use in as eg an init image on canvas, or a control image. If we just delete the image, canvas/controlnet/etc may break (the image would just fail to load).
When an image is deleted, the app checks to see if it is in use in:
- Image to Image
- ControlNet
- Unified Canvas
- Node Editor
The delete dialog will always open if the image is in use anywhere, and the user is advised that deleting the image will reset the feature(s).
Even if the user has ticked the box to not confirm on delete, the dialog will still show if the image is in use somewhere.
- fix "bounding box region only" not being respected when saving
- add toasts for each action
- improve workflow `take()` predicates to use the requestId
- responsive changes were causing a lot of weird layout issues, had to remove the rest of them
- canvas (non-beta) toolbar now wraps
- reduces minH for prompt boxes a bit
1. Model installer works correctly under Windows 11 Terminal
2. Fixed crash when configure script hands control off to installer
3. Kill install subprocess on keyboard interrupt
4. Command-line functionality for --yes configuration and model installation
restored.
5. New command-line features:
- install/delete lists of diffusers, LoRAS, controlnets and textual inversions
using repo ids, paths or URLs.
Help:
```
usage: invokeai-model-install [-h] [--diffusers [DIFFUSERS ...]] [--loras [LORAS ...]] [--controlnets [CONTROLNETS ...]] [--textual-inversions [TEXTUAL_INVERSIONS ...]] [--delete] [--full-precision | --no-full-precision]
[--yes] [--default_only] [--list-models {diffusers,loras,controlnets,tis}] [--config_file CONFIG_FILE] [--root_dir ROOT]
InvokeAI model downloader
options:
-h, --help show this help message and exit
--diffusers [DIFFUSERS ...]
List of URLs or repo_ids of diffusers to install/delete
--loras [LORAS ...] List of URLs or repo_ids of LoRA/LyCORIS models to install/delete
--controlnets [CONTROLNETS ...]
List of URLs or repo_ids of controlnet models to install/delete
--textual-inversions [TEXTUAL_INVERSIONS ...]
List of URLs or repo_ids of textual inversion embeddings to install/delete
--delete Delete models listed on command line rather than installing them
--full-precision, --no-full-precision
use 32-bit weights instead of faster 16-bit weights (default: False)
--yes, -y answer "yes" to all prompts
--default_only only install the default model
--list-models {diffusers,loras,controlnets,tis}
list installed models
--config_file CONFIG_FILE, -c CONFIG_FILE
path to configuration file to create
--root_dir ROOT path to root of install directory
```
Implement `dnd-kit` for image drag and drop
- vastly simplifies logic bc we can drag and drop non-serializable data (like an `ImageDTO`)
- also much prettier
- also will fix conflicts with file upload via OS drag and drop, bc `dnd-kit` does not use native HTML drag and drop API
- Implemented for Init image, controlnet, and node editor so far
More progress on the ControlNet UI
- The invokeai.db database file has now been moved into
`INVOKEAIROOT/databases`. Using plural here for possible
future with more than one database file.
- Removed a few dangling debug messages that appeared during
testing.
- Rebuilt frontend to test web.
1. Separated the "starter models" and "more models" sections. This
gives us room to list all installed diffuserse models, not just
those that are on the starter list.
2. Support mouse-based paste into the textboxes with either middle
or right mouse buttons.
3. Support terminal-style cursor movement:
^A to move to beginning of line
^E to move to end of line
^K kill text to right and put in killring
^Y yank text back
4. Internal code cleanup.
The gallery could get in a state where it thought it had just reached the end of the list and endlessly fetches more images, if there are no more images to fetch (weird I know).
Add some logic to remove the `end reached` handler when there are no more images to load.
it doesn't work for the img2img pipelines, but the implemented conditional display could break the scheduler selection dropdown.
simple fix until diffusers merges the fix - never use this scheduler.
Inputs with explicit values are validated by pydantic even if they also
have a connection (which is the actual value that is used).
Fix this by omitting explicit values for inputs that have a connection.
Problem was that controlnet support involved adding **kwargs to method calls down in denoising loop, and AddsMaskLatents didn't accept **kwarg arg. So just changed to accept and pass on **kwargs.
This may cause minor gallery jumpiness at the very end of processing, but is necessary to prevent the progress image from sticking around if the last node in a session did not have an image output.
Some socket events should not be handled by the slice reducers. For example generation progress should not be handled for a canceled session.
Added another layer of socket actions.
Example:
- `socketGeneratorProgress` is dispatched when the actual socket event is received
- Listener middleware exclusively handles this event and determines if the application should also handle it
- If so, it dispatches `appSocketGeneratorProgress`, which the slices can handle
Needed to fix issues related to canceling invocations.
Now that images are in a database and we can make filtered queries, we can do away with the cumbersome `resultsSlice` and `uploadsSlice`.
- Remove `resultsSlice` and `uploadsSlice` entirely
- Add `imagesSlice` fills the same role
- Convert the application to use `imagesSlice`, reducing a lot of messy logic where we had to check which category was selected
- Add a simple filter popover to the gallery, which lets you select any number of image categories
Because we dynamically insert images into the DB and UI's images state, `page`/`per_page` pagination makes loading the images awkward.
Using `offset`/`limit` pagination lets us query for images with an offset equal to the number of images already loaded (which match the query parameters).
The result is that we always get the correct next page of images when loading more.
