* close modal when user clicks cancel
* close modal when delete image context cleared
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Co-authored-by: Mary Hipp <maryhipp@Marys-MacBook-Air.local>
- Accordions now may be opened or closed regardless of whether or not their contents are enabled or active
- Accordions have a short text indicator alerting the user if their contents are enabled, either a simple `Enabled` or, for accordions like LoRA or ControlNet, `X Active` if any are active
This caused a lot of re-rendering whenever the selection changed, which caused a huge performance hit. It also made changing the current image lag a bit.
Instead of providing an array of image names as a multi-select dnd payload, there is now no multi-select dnd payload at all - instead, the payload types are used by the `imageDropped` listener to pull the selection out of redux.
Now, the only big re-renders are when the selectionCount changes. In the future I'll figure out a good way to do image names as payload without incurring re-renders.
Every `GalleryImage` was rerendering any time the app rerendered bc the selector function itself was not memoized. This resulted in the memoization cache inside the selector constantly being reset.
Same for `BatchImage`.
Also updated memoization for a few other selectors.
Eg `useGetMainModelsQuery()`, `useGetLoRAModelsQuery()` instead of `useListModelsQuery({base_type})`.
Add specific adapters for each model type. Just more organised and easier to consume models now.
Also updated LoRA UI to use the model name.
This introduces the core functionality for batch operations on images and multiple selection in the gallery/batch manager.
A number of other substantial changes are included:
- `imagesSlice` is consolidated into `gallerySlice`, allowing for simpler selection of filtered images
- `batchSlice` is added to manage the batch
- The wonky context pattern for image deletion has been changed, much simpler now using a `imageDeletionSlice` and redux listeners; this needs to be implemented still for the other image modals
- Minimum gallery size in px implemented as a hook
- Many style fixes & several bug fixes
TODO:
- The UI and UX need to be figured out, especially for controlnet
- Batch processing is not hooked up; generation does not do anything with batch
- Routes to support batch image operations, specifically delete and add/remove to/from boards
- Set min size for floating gallery panel
- Correct the default pinned width (it cannot be less than the min width and this was sometimes happening during window resize)
Add `useMinimumPanelSize()` hook to provide minimum resizable panel sizes (in pixels).
The library we are using for the gallery panel uses percentages only. To provide a minimum size in pixels, we need to do some math to calculate the percentage of window size that corresponds to the desired min width in pixels.
The node polyfills needed to run the `swagger-parser` library (used to dereference the OpenAPI schema) cause the canvas tab to immediately crash when the package build is used in another react application.
I'm sure this is fixable but it's not clear what is causing the issue and troubleshooting is very time consuming.
Selectively rolling back the implementation of `swagger-parser`.
Themes are very fun but due to the differences in perceived saturation and lightness across the
the color spectrum, it's impossible to have have multiple themes that look great without hand-
crafting *every* shade for *every* theme. We've ended up with 4 OK themes (well, 3, because the
light theme was pretty bad).
I've removed the themes and added color mode support. There is now a single dark and light mode,
each with their own color palette and the classic grey / purple / yellow invoke colors that
@blessedcoolant first designed.
I've re-styled almost everything except the model manager and lightbox, which I keep forgetting
to work on.
One new concept is the Chakra `layerStyle`. This lets us define "layers" - think body, first layer,
second layer, etc - that can be applied on various components. By defining layers, we can be more
consistent about the z-axis and its relationship to color and lightness.
The TS Language Server slows down immensely with our translation JSON, which is used to provide kinda-type-safe translation keys. I say "kinda", because you don't get autocomplete - you only get red squigglies when the key is incorrect.
To improve the performance, we can opt out of this process entirely, at the cost of no red squigglies for translation keys. Hopefully we can resolve this in the future.
It's not clear why this became an issue only recently (like past couple weeks). We've tried rolling back the app dependencies, VSCode extensions, VSCode itself, and the TS version to before the time when the issue started, but nothing seems to improve the performance.
1. Disable `resolveJsonModule` in `tsconfig.json`
2. Ignore TS in `i18n.ts` when importing the JSON
3. Comment out the custom types in `i18.d.ts` entirely
It's possible that only `3` is needed to fix the issue.
I've tested building the app and running the build - it works fine, and translation works fine.
Everything seems to be working.
- Due to a change to `reactflow`, I regenerated `yarn.lock`
- New chakra CLI fixes issue I had made a patch for; removed the patch
- Change to fontsource changed how we import that font
- Change to fontawesome means we lost the txt2img tab icon, just chose a similar one
Only "real" conflicts were in:
invokeai/frontend/web/src/features/controlNet/components/ControlNet.tsx
invokeai/frontend/web/src/features/controlNet/store/controlNetSlice.ts
- Reset and Upload buttons along top of initial image
- Also had to mess around with the control net & DnD image stuff after changing the styles
- Abstract image upload logic into hook - does not handle native HTML drag and drop upload - only the button click upload
`openapi-fetch` does not handle non-JSON `body`s, always stringifying them, and sets the `content-type` to `application/json`.
The patch here does two things:
- Do not stringify `body` if it is one of the types that should not be stringified (https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API/Using_Fetch#body)
- Do not add `content-type: application/json` unless it really is stringified JSON.
Upstream issue: https://github.com/drwpow/openapi-typescript/issues/1123
I'm not a bit lost on fixing the types and adding tests, so not raising a PR upstream.
*migrate from `openapi-typescript-codegen` to `openapi-typescript` and `openapi-fetch`*
`openapi-typescript-codegen` is not very actively maintained - it's been over a year since the last update.
`openapi-typescript` and `openapi-fetch` are part of the actively maintained repo. key differences:
- provides a `fetch` client instead of `axios`, which means we need to be a bit more verbose with typing thunks
- fetch client is created at runtime and has a very nice typescript DX
- generates a single file with all types in it, from which we then extract individual types. i don't like how verbose this is, but i do like how it is more explicit.
- removed npm api generation scripts - now we have a single `typegen` script
overall i have more confidence in this new library.
*use nanostores for api base and token*
very simple reactive store for api base url and token. this was suggested in the `openapi-fetch` docs and i quite like the strategy.
*organise rtk-query api*
split out each endpoint (models, images, boards, boardImages) into their own api extensions. tidy!
Basically updated all slices to be more descriptive in their names. Did so in order to make sure theres good naming scheme available for secondary models.
To determine whether the Load More button should work, we need to keep track of how many images are left to load for a given board or category.
The Assets tab doesn't work, though. Need to figure out a better way to handle this.
We need to access the initial image dimensions during the creation of the `ImageToImage` graph to determine if we need to resize the image.
Because the `initialImage` is now just an image name, we need to either store (easy) or dynamically retrieve its dimensions during graph creation (a bit less easy).
Took the easiest path. May need to revise this in the future.
Images that are used as parameters (e.g. init image, canvas images) are stored as full `ImageDTO` objects in state, separate from and duplicating any object representing those same objects in the `imagesSlice`.
We cannot store only image names as parameters, then pull the full `ImageDTO` from `imagesSlice`, because if an image is not on a loaded page, it doesn't exist in `imagesSlice`. For example, if you scroll down a few pages in the gallery and send that image to canvas, on reloading the app, the canvas will be unable to load that image.
We solved this temporarily by storing the full `ImageDTO` object wherever it was needed, but this is both inefficient and allows for stale `ImageDTO`s across the app.
One other possible solution was to just fetch the `ImageDTO` for all images at startup, and insert them into the `imagesSlice`, but then we run into an issue where we are displaying images in the gallery totally out of context.
For example, if an image from several pages into the gallery was sent to canvas, and the user refreshes, we'd display the first 20 images in gallery. Then to populate the canvas, we'd fetch that image we sent to canvas and add it to `imagesSlice`. Now we'd have 21 images in the gallery: 1 to 20 and whichever image we sent to canvas. Weird.
Using `rtk-query` solves this by allowing us to very easily fetch individual images in the components that need them, and not directly interact with `imagesSlice`.
This commit changes all references to images-as-parameters to store only the name of the image, and not the full `ImageDTO` object. Then, we use an `rtk-query` generated `useGetImageDTOQuery()` hook in each of those components to fetch the image.
We can use cache invalidation when we mutate any image to trigger automated re-running of the query and all the images are automatically kept up to date.
This also obviates the need for the convoluted URL fetching scheme for images that are used as parameters. The `imagesSlice` still need this handling unfortunately.
- Add graph builders for canvas txt2img & img2img - they are mostly copy and paste from the linear graph builders but different in a few ways that are very tricky to work around. Just made totally new functions for them.
- Canvas txt2img and img2img support ControlNet (not inpaint/outpaint). There's no way to determine in real-time which mode the canvas is in just yet, so we cannot disable the ControlNet UI when the mode will be inpaint/outpaint - it will always display. It's possible to determine this in near-real-time, will add this at some point.
- Canvas inpaint/outpaint migrated to use model loader, though inpaint/outpaint are still using the non-latents nodes.
Instead of manually creating every node and edge, we can simply copy/paste the base graph from node editor, then sub in parameters.
This is a much more intelligible process. We still need to handle seed, img2img fit and controlnet separately.
