mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
Merge branch 'development' into fix-disabled-prompt
This commit is contained in:
Lincoln Stein
GitHub
commit
a956bf9fda
@ -6,15 +6,16 @@
|
||||
# and the width and height of the images it
|
||||
# was trained on.
|
||||
|
||||
laion400m:
|
||||
config: configs/latent-diffusion/txt2img-1p4B-eval.yaml
|
||||
weights: models/ldm/text2img-large/model.ckpt
|
||||
description: Latent Diffusion LAION400M model
|
||||
width: 256
|
||||
height: 256
|
||||
stable-diffusion-1.4:
|
||||
config: configs/stable-diffusion/v1-inference.yaml
|
||||
weights: models/ldm/stable-diffusion-v1/model.ckpt
|
||||
vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
|
||||
description: Stable Diffusion inference model version 1.4
|
||||
width: 512
|
||||
height: 512
|
||||
stable-diffusion-1.5:
|
||||
config: configs/stable-diffusion/v1-inference.yaml
|
||||
weights: models/ldm/stable-diffusion-v1/v1-5-pruned-emaonly.ckpt
|
||||
description: Stable Diffusion inference model version 1.5
|
||||
width: 512
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||||
height: 512
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||||
|
||||
@ -8,7 +8,7 @@ hide:
|
||||
|
||||
## **Interactive Command Line Interface**
|
||||
|
||||
The `invoke.py` script, located in `scripts/dream.py`, provides an interactive
|
||||
The `invoke.py` script, located in `scripts/`, provides an interactive
|
||||
interface to image generation similar to the "invoke mothership" bot that Stable
|
||||
AI provided on its Discord server.
|
||||
|
||||
@ -283,12 +283,20 @@ Some examples:
|
||||
Outputs:
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||||
[1] outputs/img-samples/000017.4829112.gfpgan-00.png: !fix "outputs/img-samples/0000045.4829112.png" -s 50 -S -W 512 -H 512 -C 7.5 -A k_lms -G 0.8
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||||
|
||||
# Model selection and importation
|
||||
### !mask
|
||||
|
||||
This command takes an image, a text prompt, and uses the `clipseg`
|
||||
algorithm to automatically generate a mask of the area that matches
|
||||
the text prompt. It is useful for debugging the text masking process
|
||||
prior to inpainting with the `--text_mask` argument. See
|
||||
[INPAINTING.md] for details.
|
||||
|
||||
## Model selection and importation
|
||||
|
||||
The CLI allows you to add new models on the fly, as well as to switch
|
||||
among them rapidly without leaving the script.
|
||||
|
||||
## !models
|
||||
### !models
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||||
|
||||
This prints out a list of the models defined in `config/models.yaml'.
|
||||
The active model is bold-faced
|
||||
@ -300,7 +308,7 @@ laion400m not loaded <no description>
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||||
waifu-diffusion not loaded Waifu Diffusion v1.3
|
||||
</pre>
|
||||
|
||||
## !switch <model>
|
||||
### !switch <model>
|
||||
|
||||
This quickly switches from one model to another without leaving the
|
||||
CLI script. `invoke.py` uses a memory caching system; once a model
|
||||
@ -346,7 +354,7 @@ laion400m not loaded <no description>
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||||
waifu-diffusion cached Waifu Diffusion v1.3
|
||||
</pre>
|
||||
|
||||
## !import_model <path/to/model/weights>
|
||||
### !import_model <path/to/model/weights>
|
||||
|
||||
This command imports a new model weights file into InvokeAI, makes it
|
||||
available for image generation within the script, and writes out the
|
||||
@ -398,7 +406,7 @@ OK to import [n]? <b>y</b>
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invoke>
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||||
</pre>
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||||
|
||||
##!edit_model <name_of_model>
|
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###!edit_model <name_of_model>
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||||
|
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The `!edit_model` command can be used to modify a model that is
|
||||
already defined in `config/models.yaml`. Call it with the short
|
||||
@ -434,20 +442,12 @@ OK to import [n]? y
|
||||
Outputs:
|
||||
[2] outputs/img-samples/000018.2273800735.embiggen-00.png: !fix "outputs/img-samples/000017.243781548.gfpgan-00.png" -s 50 -S 2273800735 -W 512 -H 512 -C 7.5 -A k_lms --embiggen 3.0 0.75 0.25
|
||||
```
|
||||
# History processing
|
||||
## History processing
|
||||
|
||||
The CLI provides a series of convenient commands for reviewing previous
|
||||
actions, retrieving them, modifying them, and re-running them.
|
||||
```bash
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invoke> !fetch 0000015.8929913.png
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||||
# the script returns the next line, ready for editing and running:
|
||||
invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
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||||
```
|
||||
|
||||
Note that this command may behave unexpectedly if given a PNG file that
|
||||
was not generated by InvokeAI.
|
||||
|
||||
### `!history`
|
||||
### !history
|
||||
|
||||
The invoke script keeps track of all the commands you issue during a
|
||||
session, allowing you to re-run them. On Mac and Linux systems, it
|
||||
@ -472,20 +472,41 @@ invoke> !20
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||||
invoke> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
|
||||
```
|
||||
|
||||
## !fetch
|
||||
### !fetch
|
||||
|
||||
This command retrieves the generation parameters from a previously
|
||||
generated image and either loads them into the command line. You may
|
||||
provide either the name of a file in the current output directory, or
|
||||
a full file path.
|
||||
generated image and either loads them into the command line
|
||||
(Linux|Mac), or prints them out in a comment for copy-and-paste
|
||||
(Windows). You may provide either the name of a file in the current
|
||||
output directory, or a full file path. Specify path to a folder with
|
||||
image png files, and wildcard *.png to retrieve the dream command used
|
||||
to generate the images, and save them to a file commands.txt for
|
||||
further processing.
|
||||
|
||||
~~~
|
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This example loads the generation command for a single png file:
|
||||
|
||||
```bash
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||||
invoke> !fetch 0000015.8929913.png
|
||||
# the script returns the next line, ready for editing and running:
|
||||
invoke> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
|
||||
```
|
||||
|
||||
This one fetches the generation commands from a batch of files and
|
||||
stores them into `selected.txt`:
|
||||
|
||||
```bash
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||||
invoke> !fetch outputs\selected-imgs\*.png selected.txt
|
||||
```
|
||||
|
||||
### !replay
|
||||
|
||||
This command replays a text file generated by !fetch or created manually
|
||||
|
||||
~~~
|
||||
invoke> !replay outputs\selected-imgs\selected.txt
|
||||
~~~
|
||||
|
||||
Note that this command may behave unexpectedly if given a PNG file that
|
||||
Note that these commands may behave unexpectedly if given a PNG file that
|
||||
was not generated by InvokeAI.
|
||||
|
||||
### !search <search string>
|
||||
@ -503,16 +524,6 @@ invoke> !search surreal
|
||||
This clears the search history from memory and disk. Be advised that
|
||||
this operation is irreversible and does not issue any warnings!
|
||||
|
||||
Other ! Commands
|
||||
|
||||
### !mask
|
||||
|
||||
This command takes an image, a text prompt, and uses the `clipseg`
|
||||
algorithm to automatically generate a mask of the area that matches
|
||||
the text prompt. It is useful for debugging the text masking process
|
||||
prior to inpainting with the `--text_mask` argument. See
|
||||
[INPAINTING.md] for details.
|
||||
|
||||
## Command-line editing and completion
|
||||
|
||||
The command-line offers convenient history tracking, editing, and
|
||||
|
||||
690
frontend/dist/assets/index.2d646c45.js
vendored
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690
frontend/dist/assets/index.2d646c45.js
vendored
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1
frontend/dist/assets/index.58175ea1.css
vendored
1
frontend/dist/assets/index.58175ea1.css
vendored
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1
frontend/dist/assets/index.7749e179.css
vendored
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1
frontend/dist/assets/index.7749e179.css
vendored
Normal file
File diff suppressed because one or more lines are too long
@ -14,6 +14,7 @@
|
||||
"@chakra-ui/react": "^2.3.1",
|
||||
"@emotion/react": "^11.10.4",
|
||||
"@emotion/styled": "^11.10.4",
|
||||
"@radix-ui/react-context-menu": "^2.0.1",
|
||||
"@reduxjs/toolkit": "^1.8.5",
|
||||
"@types/uuid": "^8.3.4",
|
||||
"dateformat": "^5.0.3",
|
||||
@ -25,7 +26,6 @@
|
||||
"react-dropzone": "^14.2.2",
|
||||
"react-hotkeys-hook": "^3.4.7",
|
||||
"react-icons": "^4.4.0",
|
||||
"react-masonry-css": "^1.0.16",
|
||||
"react-redux": "^8.0.2",
|
||||
"redux-persist": "^6.0.0",
|
||||
"socket.io": "^4.5.2",
|
||||
|
||||
@ -26,7 +26,7 @@ const makeSocketIOEmitters = (
|
||||
|
||||
const options = { ...getState().options };
|
||||
|
||||
if (tabMap[options.activeTab] === 'txt2img') {
|
||||
if (tabMap[options.activeTab] !== 'img2img') {
|
||||
options.shouldUseInitImage = false;
|
||||
}
|
||||
|
||||
|
||||
@ -7,12 +7,17 @@ export const PostProcessingWIP = () => {
|
||||
<p>
|
||||
Invoke AI offers a wide variety of post processing features. Image
|
||||
Upscaling and Face Restoration are already available in the WebUI. You
|
||||
can access them from the Advanced Options menu of the Text To Image tab.
|
||||
A dedicated UI will be released soon.
|
||||
can access them from the Advanced Options menu of the Text To Image and
|
||||
Image To Image tabs. You can also process images directly, using the
|
||||
image action buttons above the main image display.
|
||||
</p>
|
||||
<p>
|
||||
A dedicated UI will be released soon to facilitate more advanced post
|
||||
processing workflows.
|
||||
</p>
|
||||
<p>
|
||||
The Invoke AI Command Line Interface offers various other features
|
||||
including Embiggen, High Resolution Fixing and more.
|
||||
including Embiggen.
|
||||
</p>
|
||||
</div>
|
||||
);
|
||||
|
||||
@ -12,6 +12,7 @@ import {
|
||||
FormControl,
|
||||
FormLabel,
|
||||
Flex,
|
||||
useToast,
|
||||
} from '@chakra-ui/react';
|
||||
import { createSelector } from '@reduxjs/toolkit';
|
||||
import {
|
||||
@ -57,6 +58,7 @@ const DeleteImageModal = forwardRef(
|
||||
const dispatch = useAppDispatch();
|
||||
const shouldConfirmOnDelete = useAppSelector(systemSelector);
|
||||
const cancelRef = useRef<HTMLButtonElement>(null);
|
||||
const toast = useToast();
|
||||
|
||||
const handleClickDelete = (e: SyntheticEvent) => {
|
||||
e.stopPropagation();
|
||||
@ -65,6 +67,12 @@ const DeleteImageModal = forwardRef(
|
||||
|
||||
const handleDelete = () => {
|
||||
dispatch(deleteImage(image));
|
||||
toast({
|
||||
title: 'Image Deleted',
|
||||
status: 'success',
|
||||
duration: 2500,
|
||||
isClosable: true,
|
||||
});
|
||||
onClose();
|
||||
};
|
||||
|
||||
|
||||
@ -17,6 +17,12 @@
|
||||
max-height: 100%;
|
||||
}
|
||||
|
||||
.hoverable-image-delete-button {
|
||||
position: absolute;
|
||||
top: 0.25rem;
|
||||
right: 0.25rem;
|
||||
}
|
||||
|
||||
.hoverable-image-content {
|
||||
display: flex;
|
||||
position: absolute;
|
||||
@ -57,3 +63,39 @@
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
.hoverable-image-context-menu {
|
||||
z-index: 999;
|
||||
padding: 0.4rem;
|
||||
border-radius: 0.25rem;
|
||||
background-color: var(--context-menu-bg-color);
|
||||
box-shadow: var(--context-menu-box-shadow);
|
||||
|
||||
[role='menuitem'] {
|
||||
font-size: 0.8rem;
|
||||
line-height: 1rem;
|
||||
border-radius: 3px;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
height: 1.75rem;
|
||||
padding: 0 0.5rem;
|
||||
position: relative;
|
||||
user-select: none;
|
||||
cursor: pointer;
|
||||
outline: none;
|
||||
|
||||
&[data-disabled] {
|
||||
color: grey;
|
||||
pointer-events: none;
|
||||
cursor: not-allowed;
|
||||
}
|
||||
|
||||
&[data-warning] {
|
||||
color: var(--status-bad-color);
|
||||
}
|
||||
|
||||
&[data-highlighted] {
|
||||
background-color: var(--context-menu-bg-color-hover);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@ -1,17 +1,27 @@
|
||||
import { Box, Icon, IconButton, Image, Tooltip } from '@chakra-ui/react';
|
||||
import {
|
||||
Box,
|
||||
Icon,
|
||||
IconButton,
|
||||
Image,
|
||||
Tooltip,
|
||||
useToast,
|
||||
} from '@chakra-ui/react';
|
||||
import { RootState, useAppDispatch, useAppSelector } from '../../app/store';
|
||||
import { setCurrentImage } from './gallerySlice';
|
||||
import { FaCheck, FaImage, FaSeedling, FaTrashAlt } from 'react-icons/fa';
|
||||
import { FaCheck, FaTrashAlt } from 'react-icons/fa';
|
||||
import DeleteImageModal from './DeleteImageModal';
|
||||
import { memo, SyntheticEvent, useState } from 'react';
|
||||
import { memo, useState } from 'react';
|
||||
import {
|
||||
setActiveTab,
|
||||
setAllParameters,
|
||||
setAllImageToImageParameters,
|
||||
setAllTextToImageParameters,
|
||||
setInitialImagePath,
|
||||
setPrompt,
|
||||
setSeed,
|
||||
} from '../options/optionsSlice';
|
||||
import * as InvokeAI from '../../app/invokeai';
|
||||
import { IoArrowUndoCircleOutline } from 'react-icons/io5';
|
||||
import * as ContextMenu from '@radix-ui/react-context-menu';
|
||||
import { tabMap } from '../tabs/InvokeTabs';
|
||||
|
||||
interface HoverableImageProps {
|
||||
image: InvokeAI.Image;
|
||||
@ -27,115 +37,174 @@ const memoEqualityCheck = (
|
||||
* Gallery image component with delete/use all/use seed buttons on hover.
|
||||
*/
|
||||
const HoverableImage = memo((props: HoverableImageProps) => {
|
||||
const [isHovered, setIsHovered] = useState<boolean>(false);
|
||||
const dispatch = useAppDispatch();
|
||||
|
||||
const activeTab = useAppSelector(
|
||||
(state: RootState) => state.options.activeTab
|
||||
);
|
||||
|
||||
const [isHovered, setIsHovered] = useState<boolean>(false);
|
||||
|
||||
const toast = useToast();
|
||||
|
||||
const { image, isSelected } = props;
|
||||
const { url, uuid, metadata } = image;
|
||||
|
||||
const handleMouseOver = () => setIsHovered(true);
|
||||
|
||||
const handleMouseOut = () => setIsHovered(false);
|
||||
|
||||
const handleClickSetAllParameters = (e: SyntheticEvent) => {
|
||||
e.stopPropagation();
|
||||
dispatch(setAllParameters(metadata));
|
||||
const handleUsePrompt = () => {
|
||||
dispatch(setPrompt(image.metadata.image.prompt));
|
||||
toast({
|
||||
title: 'Prompt Set',
|
||||
status: 'success',
|
||||
duration: 2500,
|
||||
isClosable: true,
|
||||
});
|
||||
};
|
||||
|
||||
const handleClickSetSeed = (e: SyntheticEvent) => {
|
||||
e.stopPropagation();
|
||||
const handleUseSeed = () => {
|
||||
dispatch(setSeed(image.metadata.image.seed));
|
||||
toast({
|
||||
title: 'Seed Set',
|
||||
status: 'success',
|
||||
duration: 2500,
|
||||
isClosable: true,
|
||||
});
|
||||
};
|
||||
|
||||
const handleSetInitImage = (e: SyntheticEvent) => {
|
||||
e.stopPropagation();
|
||||
const handleSendToImageToImage = () => {
|
||||
dispatch(setInitialImagePath(image.url));
|
||||
if (activeTab !== 1) {
|
||||
dispatch(setActiveTab(1));
|
||||
}
|
||||
toast({
|
||||
title: 'Sent to Image To Image',
|
||||
status: 'success',
|
||||
duration: 2500,
|
||||
isClosable: true,
|
||||
});
|
||||
};
|
||||
|
||||
const handleClickImage = () => dispatch(setCurrentImage(image));
|
||||
const handleUseAllParameters = () => {
|
||||
dispatch(setAllTextToImageParameters(metadata));
|
||||
toast({
|
||||
title: 'Parameters Set',
|
||||
status: 'success',
|
||||
duration: 2500,
|
||||
isClosable: true,
|
||||
});
|
||||
};
|
||||
|
||||
const handleUseInitialImage = async () => {
|
||||
// check if the image exists before setting it as initial image
|
||||
if (metadata?.image?.init_image_path) {
|
||||
const response = await fetch(metadata.image.init_image_path);
|
||||
if (response.ok) {
|
||||
dispatch(setActiveTab(tabMap.indexOf('img2img')));
|
||||
dispatch(setAllImageToImageParameters(metadata));
|
||||
toast({
|
||||
title: 'Initial Image Set',
|
||||
status: 'success',
|
||||
duration: 2500,
|
||||
isClosable: true,
|
||||
});
|
||||
return;
|
||||
}
|
||||
}
|
||||
toast({
|
||||
title: 'Initial Image Not Set',
|
||||
description: 'Could not load initial image.',
|
||||
status: 'error',
|
||||
duration: 2500,
|
||||
isClosable: true,
|
||||
});
|
||||
};
|
||||
|
||||
const handleSelectImage = () => dispatch(setCurrentImage(image));
|
||||
|
||||
return (
|
||||
<Box
|
||||
position={'relative'}
|
||||
key={uuid}
|
||||
className="hoverable-image"
|
||||
onMouseOver={handleMouseOver}
|
||||
onMouseOut={handleMouseOut}
|
||||
>
|
||||
<Image
|
||||
objectFit="cover"
|
||||
rounded={'md'}
|
||||
src={url}
|
||||
loading={'lazy'}
|
||||
className="hoverable-image-image"
|
||||
/>
|
||||
<div className="hoverable-image-content" onClick={handleClickImage}>
|
||||
{isSelected && (
|
||||
<Icon
|
||||
width={'50%'}
|
||||
height={'50%'}
|
||||
as={FaCheck}
|
||||
className="hoverable-image-check"
|
||||
<ContextMenu.Root>
|
||||
<ContextMenu.Trigger>
|
||||
<Box
|
||||
position={'relative'}
|
||||
key={uuid}
|
||||
className="hoverable-image"
|
||||
onMouseOver={handleMouseOver}
|
||||
onMouseOut={handleMouseOut}
|
||||
>
|
||||
<Image
|
||||
className="hoverable-image-image"
|
||||
objectFit="cover"
|
||||
rounded={'md'}
|
||||
src={url}
|
||||
loading={'lazy'}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
{isHovered && (
|
||||
<div className="hoverable-image-icons">
|
||||
<Tooltip label={'Delete image'} hasArrow>
|
||||
<DeleteImageModal image={image}>
|
||||
<IconButton
|
||||
colorScheme="red"
|
||||
aria-label="Delete image"
|
||||
icon={<FaTrashAlt />}
|
||||
size="xs"
|
||||
variant={'imageHoverIconButton'}
|
||||
fontSize={14}
|
||||
<div className="hoverable-image-content" onClick={handleSelectImage}>
|
||||
{isSelected && (
|
||||
<Icon
|
||||
width={'50%'}
|
||||
height={'50%'}
|
||||
as={FaCheck}
|
||||
className="hoverable-image-check"
|
||||
/>
|
||||
</DeleteImageModal>
|
||||
</Tooltip>
|
||||
{['txt2img', 'img2img'].includes(image?.metadata?.image?.type) && (
|
||||
<Tooltip label="Use All Parameters" hasArrow>
|
||||
<IconButton
|
||||
aria-label="Use All Parameters"
|
||||
icon={<IoArrowUndoCircleOutline />}
|
||||
size="xs"
|
||||
fontSize={18}
|
||||
variant={'imageHoverIconButton'}
|
||||
onClickCapture={handleClickSetAllParameters}
|
||||
/>
|
||||
</Tooltip>
|
||||
)}
|
||||
</div>
|
||||
{isHovered && (
|
||||
<div className="hoverable-image-delete-button">
|
||||
<Tooltip label={'Delete image'} hasArrow>
|
||||
<DeleteImageModal image={image}>
|
||||
<IconButton
|
||||
aria-label="Delete image"
|
||||
icon={<FaTrashAlt />}
|
||||
size="xs"
|
||||
variant={'imageHoverIconButton'}
|
||||
fontSize={14}
|
||||
/>
|
||||
</DeleteImageModal>
|
||||
</Tooltip>
|
||||
</div>
|
||||
)}
|
||||
{image?.metadata?.image?.seed !== undefined && (
|
||||
<Tooltip label="Use Seed" hasArrow>
|
||||
<IconButton
|
||||
aria-label="Use Seed"
|
||||
icon={<FaSeedling />}
|
||||
size="xs"
|
||||
fontSize={16}
|
||||
variant={'imageHoverIconButton'}
|
||||
onClickCapture={handleClickSetSeed}
|
||||
/>
|
||||
</Tooltip>
|
||||
)}
|
||||
<Tooltip label="Send To Image To Image" hasArrow>
|
||||
<IconButton
|
||||
aria-label="Send To Image To Image"
|
||||
icon={<FaImage />}
|
||||
size="xs"
|
||||
fontSize={16}
|
||||
variant={'imageHoverIconButton'}
|
||||
onClickCapture={handleSetInitImage}
|
||||
/>
|
||||
</Tooltip>
|
||||
</div>
|
||||
)}
|
||||
</Box>
|
||||
</Box>
|
||||
</ContextMenu.Trigger>
|
||||
<ContextMenu.Content className="hoverable-image-context-menu">
|
||||
<ContextMenu.Item
|
||||
onClickCapture={handleUsePrompt}
|
||||
disabled={image?.metadata?.image?.prompt === undefined}
|
||||
>
|
||||
Use Prompt
|
||||
</ContextMenu.Item>
|
||||
|
||||
<ContextMenu.Item
|
||||
onClickCapture={handleUseSeed}
|
||||
disabled={image?.metadata?.image?.seed === undefined}
|
||||
>
|
||||
Use Seed
|
||||
</ContextMenu.Item>
|
||||
<ContextMenu.Item
|
||||
onClickCapture={handleUseAllParameters}
|
||||
disabled={
|
||||
!['txt2img', 'img2img'].includes(image?.metadata?.image?.type)
|
||||
}
|
||||
>
|
||||
Use All Parameters
|
||||
</ContextMenu.Item>
|
||||
<Tooltip label="Load initial image used for this generation">
|
||||
<ContextMenu.Item
|
||||
onClickCapture={handleUseInitialImage}
|
||||
disabled={image?.metadata?.image?.type !== 'img2img'}
|
||||
>
|
||||
Use Initial Image
|
||||
</ContextMenu.Item>
|
||||
</Tooltip>
|
||||
<ContextMenu.Item onClickCapture={handleSendToImageToImage}>
|
||||
Send to Image To Image
|
||||
</ContextMenu.Item>
|
||||
<DeleteImageModal image={image}>
|
||||
<ContextMenu.Item data-warning>Delete Image</ContextMenu.Item>
|
||||
</DeleteImageModal>
|
||||
</ContextMenu.Content>
|
||||
</ContextMenu.Root>
|
||||
);
|
||||
}, memoEqualityCheck);
|
||||
|
||||
|
||||
@ -55,31 +55,37 @@
|
||||
@include HideScrollbar;
|
||||
}
|
||||
|
||||
.masonry-grid {
|
||||
display: -webkit-box; /* Not needed if autoprefixing */
|
||||
display: -ms-flexbox; /* Not needed if autoprefixing */
|
||||
display: flex;
|
||||
margin-left: 0.5rem; /* gutter size offset */
|
||||
width: auto;
|
||||
}
|
||||
.masonry-grid_column {
|
||||
padding-left: 0.5rem; /* gutter size */
|
||||
background-clip: padding-box;
|
||||
}
|
||||
// from https://css-tricks.com/a-grid-of-logos-in-squares/
|
||||
.image-gallery {
|
||||
display: grid;
|
||||
grid-template-columns: repeat(auto-fill, minmax(80px, auto));
|
||||
grid-gap: 0.5rem;
|
||||
.hoverable-image {
|
||||
padding: 0.5rem;
|
||||
position: relative;
|
||||
&::before {
|
||||
// for apsect ratio
|
||||
content: '';
|
||||
display: block;
|
||||
padding-bottom: 100%;
|
||||
}
|
||||
.hoverable-image-image {
|
||||
position: absolute;
|
||||
max-width: 100%;
|
||||
|
||||
/* Style your items */
|
||||
.masonry-grid_column > .hoverable-image {
|
||||
/* change div to reference your elements you put in <Masonry> */
|
||||
background: var(--tab-color);
|
||||
margin-bottom: 0.5rem;
|
||||
}
|
||||
// Alternate Version
|
||||
// top: 0;
|
||||
// bottom: 0;
|
||||
// right: 0;
|
||||
// left: 0;
|
||||
// margin: auto;
|
||||
|
||||
// .image-gallery {
|
||||
// display: flex;
|
||||
// grid-template-columns: repeat(auto-fill, minmax(80px, auto));
|
||||
// gap: 0.5rem;
|
||||
// justify-items: center;
|
||||
// }
|
||||
top: 50%;
|
||||
left: 50%;
|
||||
transform: translate(-50%, -50%);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
.image-gallery-load-more-btn {
|
||||
background-color: var(--btn-load-more) !important;
|
||||
|
||||
@ -1,10 +1,9 @@
|
||||
import { Button, IconButton } from '@chakra-ui/button';
|
||||
import { Resizable } from 're-resizable';
|
||||
|
||||
import React, { useState } from 'react';
|
||||
import React from 'react';
|
||||
import { useHotkeys } from 'react-hotkeys-hook';
|
||||
import { MdClear, MdPhotoLibrary } from 'react-icons/md';
|
||||
import Masonry from 'react-masonry-css';
|
||||
import { requestImages } from '../../app/socketio/actions';
|
||||
import { RootState, useAppDispatch, useAppSelector } from '../../app/store';
|
||||
import IAIIconButton from '../../common/components/IAIIconButton';
|
||||
@ -27,12 +26,6 @@ export default function ImageGallery() {
|
||||
|
||||
const dispatch = useAppDispatch();
|
||||
|
||||
const [column, setColumn] = useState<number | undefined>();
|
||||
|
||||
const handleResize = (event: MouseEvent | TouchEvent | any) => {
|
||||
setColumn(Math.floor((window.innerWidth - event.x) / 120));
|
||||
};
|
||||
|
||||
const handleShowGalleryToggle = () => {
|
||||
dispatch(setShouldShowGallery(!shouldShowGallery));
|
||||
};
|
||||
@ -89,9 +82,7 @@ export default function ImageGallery() {
|
||||
minWidth={'300'}
|
||||
maxWidth={activeTab == 1 ? '300' : '600'}
|
||||
className="image-gallery-popup"
|
||||
onResize={handleResize}
|
||||
>
|
||||
{/* <div className="image-gallery-popup"></div> */}
|
||||
<div className="image-gallery-header">
|
||||
<h1>Your Invocations</h1>
|
||||
<IconButton
|
||||
@ -104,12 +95,7 @@ export default function ImageGallery() {
|
||||
</div>
|
||||
<div className="image-gallery-container">
|
||||
{images.length ? (
|
||||
<Masonry
|
||||
className="masonry-grid"
|
||||
columnClassName="masonry-grid_column"
|
||||
breakpointCols={column}
|
||||
>
|
||||
{/* <div className="image-gallery"> */}
|
||||
<div className="image-gallery">
|
||||
{images.map((image) => {
|
||||
const { uuid } = image;
|
||||
const isSelected = currentImageUuid === uuid;
|
||||
@ -121,8 +107,7 @@ export default function ImageGallery() {
|
||||
/>
|
||||
);
|
||||
})}
|
||||
{/* </div> */}
|
||||
</Masonry>
|
||||
</div>
|
||||
) : (
|
||||
<div className="image-gallery-container-placeholder">
|
||||
<MdPhotoLibrary />
|
||||
|
||||
@ -72,7 +72,13 @@ export const gallerySlice = createSlice({
|
||||
},
|
||||
addImage: (state, action: PayloadAction<InvokeAI.Image>) => {
|
||||
const newImage = action.payload;
|
||||
const { uuid, mtime } = newImage;
|
||||
const { uuid, url, mtime } = newImage;
|
||||
|
||||
// Do not add duplicate images
|
||||
if (state.images.find((i) => i.url === url && i.mtime === mtime)) {
|
||||
return;
|
||||
}
|
||||
|
||||
state.images.unshift(newImage);
|
||||
state.currentImageUuid = uuid;
|
||||
state.intermediateImage = undefined;
|
||||
@ -120,8 +126,15 @@ export const gallerySlice = createSlice({
|
||||
) => {
|
||||
const { images, areMoreImagesAvailable } = action.payload;
|
||||
if (images.length > 0) {
|
||||
// Filter images that already exist in the gallery
|
||||
const newImages = images.filter(
|
||||
(newImage) =>
|
||||
!state.images.find(
|
||||
(i) => i.url === newImage.url && i.mtime === newImage.mtime
|
||||
)
|
||||
);
|
||||
state.images = state.images
|
||||
.concat(images)
|
||||
.concat(newImages)
|
||||
.sort((a, b) => b.mtime - a.mtime);
|
||||
|
||||
if (!state.currentImage) {
|
||||
|
||||
@ -15,7 +15,7 @@ export default function MainCFGScale() {
|
||||
label="CFG Scale"
|
||||
step={0.5}
|
||||
min={1}
|
||||
max={200}
|
||||
max={30}
|
||||
onChange={handleChangeCfgScale}
|
||||
value={cfgScale}
|
||||
width={inputWidth}
|
||||
|
||||
@ -183,6 +183,67 @@ export const optionsSlice = createSlice({
|
||||
setSeedWeights: (state, action: PayloadAction<string>) => {
|
||||
state.seedWeights = action.payload;
|
||||
},
|
||||
setAllTextToImageParameters: (
|
||||
state,
|
||||
action: PayloadAction<InvokeAI.Metadata>
|
||||
) => {
|
||||
const {
|
||||
sampler,
|
||||
prompt,
|
||||
seed,
|
||||
variations,
|
||||
steps,
|
||||
cfg_scale,
|
||||
threshold,
|
||||
perlin,
|
||||
seamless,
|
||||
hires_fix,
|
||||
width,
|
||||
height,
|
||||
} = action.payload.image;
|
||||
|
||||
if (variations && variations.length > 0) {
|
||||
state.seedWeights = seedWeightsToString(variations);
|
||||
state.shouldGenerateVariations = true;
|
||||
} else {
|
||||
state.shouldGenerateVariations = false;
|
||||
}
|
||||
|
||||
if (seed) {
|
||||
state.seed = seed;
|
||||
state.shouldRandomizeSeed = false;
|
||||
}
|
||||
|
||||
if (prompt) state.prompt = promptToString(prompt);
|
||||
if (sampler) state.sampler = sampler;
|
||||
if (steps) state.steps = steps;
|
||||
if (cfg_scale) state.cfgScale = cfg_scale;
|
||||
if (threshold) state.threshold = threshold;
|
||||
if (typeof threshold === 'undefined') state.threshold = 0;
|
||||
if (perlin) state.perlin = perlin;
|
||||
if (typeof perlin === 'undefined') state.perlin = 0;
|
||||
if (typeof seamless === 'boolean') state.seamless = seamless;
|
||||
if (typeof hires_fix === 'boolean') state.hiresFix = hires_fix;
|
||||
if (width) state.width = width;
|
||||
if (height) state.height = height;
|
||||
},
|
||||
setAllImageToImageParameters: (
|
||||
state,
|
||||
action: PayloadAction<InvokeAI.Metadata>
|
||||
) => {
|
||||
const { type, strength, fit, init_image_path, mask_image_path } =
|
||||
action.payload.image;
|
||||
|
||||
if (type === 'img2img') {
|
||||
if (init_image_path) state.initialImagePath = init_image_path;
|
||||
if (mask_image_path) state.maskPath = mask_image_path;
|
||||
if (strength) state.img2imgStrength = strength;
|
||||
if (typeof fit === 'boolean') state.shouldFitToWidthHeight = fit;
|
||||
state.shouldUseInitImage = true;
|
||||
} else {
|
||||
state.shouldUseInitImage = false;
|
||||
}
|
||||
},
|
||||
setAllParameters: (state, action: PayloadAction<InvokeAI.Metadata>) => {
|
||||
const {
|
||||
type,
|
||||
@ -226,43 +287,6 @@ export const optionsSlice = createSlice({
|
||||
state.shouldRandomizeSeed = false;
|
||||
}
|
||||
|
||||
/**
|
||||
* We support arbitrary numbers of postprocessing steps, so it
|
||||
* doesnt make sense to be include postprocessing metadata when
|
||||
* we use all parameters. Because this code needed a bit of braining
|
||||
* to figure out, I am leaving it, in case it is needed again.
|
||||
*/
|
||||
|
||||
// let postprocessingNotDone = ['gfpgan', 'esrgan'];
|
||||
// if (postprocessing && postprocessing.length > 0) {
|
||||
// postprocessing.forEach(
|
||||
// (postprocess: InvokeAI.PostProcessedImageMetadata) => {
|
||||
// if (postprocess.type === 'gfpgan') {
|
||||
// const { strength } = postprocess;
|
||||
// if (strength) state.facetoolStrength = strength;
|
||||
// state.shouldRunFacetool = true;
|
||||
// postprocessingNotDone = postprocessingNotDone.filter(
|
||||
// (p) => p !== 'gfpgan'
|
||||
// );
|
||||
// }
|
||||
// if (postprocess.type === 'esrgan') {
|
||||
// const { scale, strength } = postprocess;
|
||||
// if (scale) state.upscalingLevel = scale;
|
||||
// if (strength) state.upscalingStrength = strength;
|
||||
// state.shouldRunESRGAN = true;
|
||||
// postprocessingNotDone = postprocessingNotDone.filter(
|
||||
// (p) => p !== 'esrgan'
|
||||
// );
|
||||
// }
|
||||
// }
|
||||
// );
|
||||
// }
|
||||
|
||||
// postprocessingNotDone.forEach((p) => {
|
||||
// if (p === 'esrgan') state.shouldRunESRGAN = false;
|
||||
// if (p === 'gfpgan') state.shouldRunFacetool = false;
|
||||
// });
|
||||
|
||||
if (prompt) state.prompt = promptToString(prompt);
|
||||
if (sampler) state.sampler = sampler;
|
||||
if (steps) state.steps = steps;
|
||||
@ -346,6 +370,8 @@ export const {
|
||||
setActiveTab,
|
||||
setShouldShowImageDetails,
|
||||
setShouldShowGallery,
|
||||
setAllTextToImageParameters,
|
||||
setAllImageToImageParameters,
|
||||
} = optionsSlice.actions;
|
||||
|
||||
export default optionsSlice.reducer;
|
||||
|
||||
@ -1,4 +1,4 @@
|
||||
import { IconButton, Image } from '@chakra-ui/react';
|
||||
import { IconButton, Image, useToast } from '@chakra-ui/react';
|
||||
import React, { SyntheticEvent } from 'react';
|
||||
import { MdClear } from 'react-icons/md';
|
||||
import { RootState, useAppDispatch, useAppSelector } from '../../../app/store';
|
||||
@ -11,10 +11,23 @@ export default function InitImagePreview() {
|
||||
|
||||
const dispatch = useAppDispatch();
|
||||
|
||||
const toast = useToast();
|
||||
|
||||
const handleClickResetInitialImage = (e: SyntheticEvent) => {
|
||||
e.stopPropagation();
|
||||
dispatch(setInitialImagePath(null));
|
||||
};
|
||||
|
||||
const alertMissingInitImage = () => {
|
||||
toast({
|
||||
title: 'Problem loading parameters',
|
||||
description: 'Unable to load init image.',
|
||||
status: 'error',
|
||||
isClosable: true,
|
||||
});
|
||||
dispatch(setInitialImagePath(null));
|
||||
};
|
||||
|
||||
return (
|
||||
<div className="init-image-preview">
|
||||
<div className="init-image-preview-header">
|
||||
@ -29,7 +42,12 @@ export default function InitImagePreview() {
|
||||
</div>
|
||||
{initialImagePath && (
|
||||
<div className="init-image-image">
|
||||
<Image fit={'contain'} src={initialImagePath} rounded={'md'} />
|
||||
<Image
|
||||
fit={'contain'}
|
||||
src={initialImagePath}
|
||||
rounded={'md'}
|
||||
onError={alertMissingInitImage}
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
|
||||
@ -50,8 +50,13 @@ export const tab_dict = {
|
||||
},
|
||||
};
|
||||
|
||||
// Array where index maps to the key of tab_dict
|
||||
export const tabMap = _.map(tab_dict, (tab, key) => key);
|
||||
|
||||
// Use tabMap to generate a union type of tab names
|
||||
const tabMapTypes = [...tabMap] as const;
|
||||
export type InvokeTabName = typeof tabMapTypes[number];
|
||||
|
||||
export default function InvokeTabs() {
|
||||
const activeTab = useAppSelector(
|
||||
(state: RootState) => state.options.activeTab
|
||||
|
||||
@ -95,4 +95,9 @@
|
||||
|
||||
// Gallery
|
||||
--gallery-resizeable-color: rgb(36, 38, 48);
|
||||
|
||||
// Context Menus
|
||||
--context-menu-bg-color: rgb(46, 48, 58);
|
||||
--context-menu-box-shadow: none;
|
||||
--context-menu-bg-color-hover: rgb(30, 32, 42);
|
||||
}
|
||||
|
||||
@ -94,4 +94,11 @@
|
||||
|
||||
// Gallery
|
||||
--gallery-resizeable-color: rgb(192, 194, 196);
|
||||
|
||||
// Context Menus
|
||||
--context-menu-bg-color: var(--background-color);
|
||||
--context-menu-box-shadow: 0px 10px 38px -10px rgba(22, 23, 24, 0.35),
|
||||
0px 10px 20px -15px rgba(22, 23, 24, 0.2);
|
||||
--context-menu-bg-color-hover: var(--background-color-secondary);
|
||||
|
||||
}
|
||||
|
||||
@ -213,6 +213,13 @@
|
||||
dependencies:
|
||||
regenerator-runtime "^0.13.4"
|
||||
|
||||
"@babel/runtime@^7.13.10":
|
||||
version "7.19.4"
|
||||
resolved "https://registry.yarnpkg.com/@babel/runtime/-/runtime-7.19.4.tgz#a42f814502ee467d55b38dd1c256f53a7b885c78"
|
||||
integrity sha512-EXpLCrk55f+cYqmHsSR+yD/0gAIMxxA9QK9lnQWzhMCvt+YmoBN7Zx94s++Kv0+unHk39vxNO8t+CMA2WSS3wA==
|
||||
dependencies:
|
||||
regenerator-runtime "^0.13.4"
|
||||
|
||||
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||||
integrity sha512-TB7pID8NRMEHxb/qQJpvSt3hQU4sqNPM1VCTjTRjEOa7cEop/QMuq8S6fb/5Tsz64kqSvB9WnwsDHtjnrM9qew==
|
||||
dependencies:
|
||||
"@babel/runtime" "^7.13.10"
|
||||
"@radix-ui/rect" "1.0.0"
|
||||
|
||||
"@radix-ui/react-use-size@1.0.0":
|
||||
version "1.0.0"
|
||||
resolved "https://registry.yarnpkg.com/@radix-ui/react-use-size/-/react-use-size-1.0.0.tgz#a0b455ac826749419f6354dc733e2ca465054771"
|
||||
integrity sha512-imZ3aYcoYCKhhgNpkNDh/aTiU05qw9hX+HHI1QDBTyIlcFjgeFlKKySNGMwTp7nYFLQg/j0VA2FmCY4WPDDHMg==
|
||||
dependencies:
|
||||
"@babel/runtime" "^7.13.10"
|
||||
"@radix-ui/react-use-layout-effect" "1.0.0"
|
||||
|
||||
"@radix-ui/rect@1.0.0":
|
||||
version "1.0.0"
|
||||
resolved "https://registry.yarnpkg.com/@radix-ui/rect/-/rect-1.0.0.tgz#0dc8e6a829ea2828d53cbc94b81793ba6383bf3c"
|
||||
integrity sha512-d0O68AYy/9oeEy1DdC07bz1/ZXX+DqCskRd3i4JzLSTXwefzaepQrKjXC7aNM8lTHjFLDO0pDgaEiQ7jEk+HVg==
|
||||
dependencies:
|
||||
"@babel/runtime" "^7.13.10"
|
||||
|
||||
"@reduxjs/toolkit@^1.8.5":
|
||||
version "1.8.5"
|
||||
resolved "https://registry.yarnpkg.com/@reduxjs/toolkit/-/toolkit-1.8.5.tgz#c14bece03ee08be88467f22dc0ecf9cf875527cd"
|
||||
@ -2850,11 +3117,6 @@ react-is@^18.0.0:
|
||||
resolved "https://registry.yarnpkg.com/react-is/-/react-is-18.2.0.tgz#199431eeaaa2e09f86427efbb4f1473edb47609b"
|
||||
integrity sha512-xWGDIW6x921xtzPkhiULtthJHoJvBbF3q26fzloPCK0hsvxtPVelvftw3zjbHWSkR2km9Z+4uxbDDK/6Zw9B8w==
|
||||
|
||||
react-masonry-css@^1.0.16:
|
||||
version "1.0.16"
|
||||
resolved "https://registry.yarnpkg.com/react-masonry-css/-/react-masonry-css-1.0.16.tgz#72b28b4ae3484e250534700860597553a10f1a2c"
|
||||
integrity sha512-KSW0hR2VQmltt/qAa3eXOctQDyOu7+ZBevtKgpNDSzT7k5LA/0XntNa9z9HKCdz3QlxmJHglTZ18e4sX4V8zZQ==
|
||||
|
||||
react-redux@^8.0.2:
|
||||
version "8.0.2"
|
||||
resolved "https://registry.yarnpkg.com/react-redux/-/react-redux-8.0.2.tgz#bc2a304bb21e79c6808e3e47c50fe1caf62f7aad"
|
||||
@ -2880,7 +3142,7 @@ react-remove-scroll-bar@^2.3.3:
|
||||
react-style-singleton "^2.2.1"
|
||||
tslib "^2.0.0"
|
||||
|
||||
react-remove-scroll@^2.5.4:
|
||||
react-remove-scroll@2.5.5, react-remove-scroll@^2.5.4:
|
||||
version "2.5.5"
|
||||
resolved "https://registry.yarnpkg.com/react-remove-scroll/-/react-remove-scroll-2.5.5.tgz#1e31a1260df08887a8a0e46d09271b52b3a37e77"
|
||||
integrity sha512-ImKhrzJJsyXJfBZ4bzu8Bwpka14c/fQt0k+cyFp/PBhTfyDnU5hjOtM4AG/0AMyy8oKzOTR0lDgJIM7pYXI0kw==
|
||||
@ -3255,6 +3517,11 @@ use-callback-ref@^1.3.0:
|
||||
dependencies:
|
||||
tslib "^2.0.0"
|
||||
|
||||
use-isomorphic-layout-effect@^1.1.1:
|
||||
version "1.1.2"
|
||||
resolved "https://registry.yarnpkg.com/use-isomorphic-layout-effect/-/use-isomorphic-layout-effect-1.1.2.tgz#497cefb13d863d687b08477d9e5a164ad8c1a6fb"
|
||||
integrity sha512-49L8yCO3iGT/ZF9QttjwLF/ZD9Iwto5LnH5LmEdk/6cFmXddqi2ulF0edxTwjj+7mqvpVVGQWvbXZdn32wRSHA==
|
||||
|
||||
use-sidecar@^1.1.2:
|
||||
version "1.1.2"
|
||||
resolved "https://registry.yarnpkg.com/use-sidecar/-/use-sidecar-1.1.2.tgz#2f43126ba2d7d7e117aa5855e5d8f0276dfe73c2"
|
||||
|
||||
@ -55,23 +55,8 @@ torch.randint_like = fix_func(torch.randint_like)
|
||||
torch.bernoulli = fix_func(torch.bernoulli)
|
||||
torch.multinomial = fix_func(torch.multinomial)
|
||||
|
||||
def fix_func(orig):
|
||||
if hasattr(torch.backends, 'mps') and torch.backends.mps.is_available():
|
||||
def new_func(*args, **kw):
|
||||
device = kw.get("device", "mps")
|
||||
kw["device"]="cpu"
|
||||
return orig(*args, **kw).to(device)
|
||||
return new_func
|
||||
return orig
|
||||
|
||||
torch.rand = fix_func(torch.rand)
|
||||
torch.rand_like = fix_func(torch.rand_like)
|
||||
torch.randn = fix_func(torch.randn)
|
||||
torch.randn_like = fix_func(torch.randn_like)
|
||||
torch.randint = fix_func(torch.randint)
|
||||
torch.randint_like = fix_func(torch.randint_like)
|
||||
torch.bernoulli = fix_func(torch.bernoulli)
|
||||
torch.multinomial = fix_func(torch.multinomial)
|
||||
# this is fallback model in case no default is defined
|
||||
FALLBACK_MODEL_NAME='stable-diffusion-1.4'
|
||||
|
||||
"""Simplified text to image API for stable diffusion/latent diffusion
|
||||
|
||||
@ -147,7 +132,7 @@ class Generate:
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
model = 'stable-diffusion-1.4',
|
||||
model = None,
|
||||
conf = 'configs/models.yaml',
|
||||
embedding_path = None,
|
||||
sampler_name = 'k_lms',
|
||||
@ -163,7 +148,6 @@ class Generate:
|
||||
free_gpu_mem=False,
|
||||
):
|
||||
mconfig = OmegaConf.load(conf)
|
||||
self.model_name = model
|
||||
self.height = None
|
||||
self.width = None
|
||||
self.model_cache = None
|
||||
@ -210,6 +194,7 @@ class Generate:
|
||||
|
||||
# model caching system for fast switching
|
||||
self.model_cache = ModelCache(mconfig,self.device,self.precision)
|
||||
self.model_name = model or self.model_cache.default_model() or FALLBACK_MODEL_NAME
|
||||
|
||||
# for VRAM usage statistics
|
||||
self.session_peakmem = torch.cuda.max_memory_allocated() if self._has_cuda else None
|
||||
@ -570,16 +555,19 @@ class Generate:
|
||||
from ldm.invoke.restoration.outcrop import Outcrop
|
||||
extend_instructions = {}
|
||||
for direction,pixels in _pairwise(opt.outcrop):
|
||||
extend_instructions[direction]=int(pixels)
|
||||
|
||||
restorer = Outcrop(image,self,)
|
||||
return restorer.process (
|
||||
extend_instructions,
|
||||
opt = opt,
|
||||
orig_opt = args,
|
||||
image_callback = callback,
|
||||
prefix = prefix,
|
||||
)
|
||||
try:
|
||||
extend_instructions[direction]=int(pixels)
|
||||
except ValueError:
|
||||
print(f'** invalid extension instruction. Use <directions> <pixels>..., as in "top 64 left 128 right 64 bottom 64"')
|
||||
if len(extend_instructions)>0:
|
||||
restorer = Outcrop(image,self,)
|
||||
return restorer.process (
|
||||
extend_instructions,
|
||||
opt = opt,
|
||||
orig_opt = args,
|
||||
image_callback = callback,
|
||||
prefix = prefix,
|
||||
)
|
||||
|
||||
elif tool == 'embiggen':
|
||||
# fetch the metadata from the image
|
||||
@ -715,8 +703,7 @@ class Generate:
|
||||
|
||||
model_data = self.model_cache.get_model(model_name)
|
||||
if model_data is None or len(model_data) == 0:
|
||||
print(f'** Model switch failed **')
|
||||
return self.model
|
||||
return None
|
||||
|
||||
self.model = model_data['model']
|
||||
self.width = model_data['width']
|
||||
@ -728,7 +715,7 @@ class Generate:
|
||||
|
||||
seed_everything(random.randrange(0, np.iinfo(np.uint32).max))
|
||||
if self.embedding_path is not None:
|
||||
model.embedding_manager.load(
|
||||
self.model.embedding_manager.load(
|
||||
self.embedding_path, self.precision == 'float32' or self.precision == 'autocast'
|
||||
)
|
||||
|
||||
|
||||
@ -366,17 +366,16 @@ class Args(object):
|
||||
deprecated_group.add_argument('--laion400m')
|
||||
deprecated_group.add_argument('--weights') # deprecated
|
||||
model_group.add_argument(
|
||||
'--conf',
|
||||
'--config',
|
||||
'-c',
|
||||
'-conf',
|
||||
'-config',
|
||||
dest='conf',
|
||||
default='./configs/models.yaml',
|
||||
help='Path to configuration file for alternate models.',
|
||||
)
|
||||
model_group.add_argument(
|
||||
'--model',
|
||||
default='stable-diffusion-1.4',
|
||||
help='Indicates which diffusion model to load. (currently "stable-diffusion-1.4" (default) or "laion400m")',
|
||||
help='Indicates which diffusion model to load (defaults to "default" stanza in configs/models.yaml)',
|
||||
)
|
||||
model_group.add_argument(
|
||||
'--png_compression','-z',
|
||||
@ -529,7 +528,7 @@ class Args(object):
|
||||
formatter_class=ArgFormatter,
|
||||
description=
|
||||
"""
|
||||
*Image generation:*
|
||||
*Image generation*
|
||||
invoke> a fantastic alien landscape -W576 -H512 -s60 -n4
|
||||
|
||||
*postprocessing*
|
||||
@ -544,6 +543,13 @@ class Args(object):
|
||||
!history lists all the commands issued during the current session.
|
||||
|
||||
!NN retrieves the NNth command from the history
|
||||
|
||||
*Model manipulation*
|
||||
!models -- list models in configs/models.yaml
|
||||
!switch <model_name> -- switch to model named <model_name>
|
||||
!import_model path/to/weights/file.ckpt -- adds a model to your config
|
||||
!edit_model <model_name> -- edit a model's description
|
||||
!del_model <model_name> -- delete a model
|
||||
"""
|
||||
)
|
||||
render_group = parser.add_argument_group('General rendering')
|
||||
@ -967,17 +973,17 @@ def sha256(path):
|
||||
return sha.hexdigest()
|
||||
|
||||
def legacy_metadata_load(meta,pathname) -> Args:
|
||||
opt = Args()
|
||||
if 'Dream' in meta and len(meta['Dream']) > 0:
|
||||
dream_prompt = meta['Dream']
|
||||
opt = Args()
|
||||
opt.parse_cmd(dream_prompt)
|
||||
return opt
|
||||
else: # if nothing else, we can get the seed
|
||||
match = re.search('\d+\.(\d+)',pathname)
|
||||
if match:
|
||||
seed = match.groups()[0]
|
||||
opt = Args()
|
||||
opt.seed = seed
|
||||
return opt
|
||||
return None
|
||||
else:
|
||||
opt.prompt = ''
|
||||
opt.seed = 0
|
||||
return opt
|
||||
|
||||
|
||||
@ -13,6 +13,7 @@ import gc
|
||||
import hashlib
|
||||
import psutil
|
||||
import transformers
|
||||
import os
|
||||
from sys import getrefcount
|
||||
from omegaconf import OmegaConf
|
||||
from omegaconf.errors import ConfigAttributeError
|
||||
@ -73,7 +74,8 @@ class ModelCache(object):
|
||||
except Exception as e:
|
||||
print(f'** model {model_name} could not be loaded: {str(e)}')
|
||||
print(f'** restoring {self.current_model}')
|
||||
return self.get_model(self.current_model)
|
||||
self.get_model(self.current_model)
|
||||
return None
|
||||
|
||||
self.current_model = model_name
|
||||
self._push_newest_model(model_name)
|
||||
@ -84,6 +86,26 @@ class ModelCache(object):
|
||||
'hash': hash
|
||||
}
|
||||
|
||||
def default_model(self) -> str:
|
||||
'''
|
||||
Returns the name of the default model, or None
|
||||
if none is defined.
|
||||
'''
|
||||
for model_name in self.config:
|
||||
if self.config[model_name].get('default',False):
|
||||
return model_name
|
||||
return None
|
||||
|
||||
def set_default_model(self,model_name:str):
|
||||
'''
|
||||
Set the default model. The change will not take
|
||||
effect until you call model_cache.commit()
|
||||
'''
|
||||
assert model_name in self.models,f"unknown model '{model_name}'"
|
||||
for model in self.models:
|
||||
self.models[model].pop('default',None)
|
||||
self.models[model_name]['default'] = True
|
||||
|
||||
def list_models(self) -> dict:
|
||||
'''
|
||||
Return a dict of models in the format:
|
||||
@ -121,12 +143,23 @@ class ModelCache(object):
|
||||
else:
|
||||
print(line)
|
||||
|
||||
def add_model(self, model_name:str, model_attributes:dict, clobber=False) ->str:
|
||||
def del_model(self, model_name:str) ->bool:
|
||||
'''
|
||||
Delete the named model.
|
||||
'''
|
||||
omega = self.config
|
||||
del omega[model_name]
|
||||
if model_name in self.stack:
|
||||
self.stack.remove(model_name)
|
||||
return True
|
||||
|
||||
def add_model(self, model_name:str, model_attributes:dict, clobber=False) ->True:
|
||||
'''
|
||||
Update the named model with a dictionary of attributes. Will fail with an
|
||||
assertion error if the name already exists. Pass clobber=True to overwrite.
|
||||
On a successful update, the config will be changed in memory and a YAML
|
||||
string will be returned.
|
||||
On a successful update, the config will be changed in memory and the
|
||||
method will return True. Will fail with an assertion error if provided
|
||||
attributes are incorrect or the model name is missing.
|
||||
'''
|
||||
omega = self.config
|
||||
# check that all the required fields are present
|
||||
@ -139,7 +172,9 @@ class ModelCache(object):
|
||||
config[field] = model_attributes[field]
|
||||
|
||||
omega[model_name] = config
|
||||
return OmegaConf.to_yaml(omega)
|
||||
if clobber:
|
||||
self._invalidate_cached_model(model_name)
|
||||
return True
|
||||
|
||||
def _check_memory(self):
|
||||
avail_memory = psutil.virtual_memory()[1]
|
||||
@ -159,6 +194,7 @@ class ModelCache(object):
|
||||
mconfig = self.config[model_name]
|
||||
config = mconfig.config
|
||||
weights = mconfig.weights
|
||||
vae = mconfig.get('vae',None)
|
||||
width = mconfig.width
|
||||
height = mconfig.height
|
||||
|
||||
@ -188,9 +224,17 @@ class ModelCache(object):
|
||||
else:
|
||||
print(' | Using more accurate float32 precision')
|
||||
|
||||
# look and load a matching vae file. Code borrowed from AUTOMATIC1111 modules/sd_models.py
|
||||
if vae and os.path.exists(vae):
|
||||
print(f' | Loading VAE weights from: {vae}')
|
||||
vae_ckpt = torch.load(vae, map_location="cpu")
|
||||
vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
|
||||
model.first_stage_model.load_state_dict(vae_dict, strict=False)
|
||||
|
||||
model.to(self.device)
|
||||
# model.to doesn't change the cond_stage_model.device used to move the tokenizer output, so set it here
|
||||
model.cond_stage_model.device = self.device
|
||||
|
||||
model.eval()
|
||||
|
||||
for m in model.modules():
|
||||
@ -219,6 +263,36 @@ class ModelCache(object):
|
||||
if self._has_cuda():
|
||||
torch.cuda.empty_cache()
|
||||
|
||||
def commit(self,config_file_path:str):
|
||||
'''
|
||||
Write current configuration out to the indicated file.
|
||||
'''
|
||||
yaml_str = OmegaConf.to_yaml(self.config)
|
||||
tmpfile = os.path.join(os.path.dirname(config_file_path),'new_config.tmp')
|
||||
with open(tmpfile, 'w') as outfile:
|
||||
outfile.write(self.preamble())
|
||||
outfile.write(yaml_str)
|
||||
os.rename(tmpfile,config_file_path)
|
||||
|
||||
def preamble(self):
|
||||
'''
|
||||
Returns the preamble for the config file.
|
||||
'''
|
||||
return '''# This file describes the alternative machine learning models
|
||||
# available to the dream script.
|
||||
#
|
||||
# To add a new model, follow the examples below. Each
|
||||
# model requires a model config file, a weights file,
|
||||
# and the width and height of the images it
|
||||
# was trained on.
|
||||
'''
|
||||
|
||||
def _invalidate_cached_model(self,model_name:str):
|
||||
self.unload_model(model_name)
|
||||
if model_name in self.stack:
|
||||
self.stack.remove(model_name)
|
||||
self.models.pop(model_name,None)
|
||||
|
||||
def _model_to_cpu(self,model):
|
||||
if self.device != 'cpu':
|
||||
model.cond_stage_model.device = 'cpu'
|
||||
|
||||
@ -22,6 +22,7 @@ except (ImportError,ModuleNotFoundError):
|
||||
|
||||
IMG_EXTENSIONS = ('.png','.jpg','.jpeg','.PNG','.JPG','.JPEG','.gif','.GIF')
|
||||
WEIGHT_EXTENSIONS = ('.ckpt','.bae')
|
||||
TEXT_EXTENSIONS = ('.txt','.TXT')
|
||||
CONFIG_EXTENSIONS = ('.yaml','.yml')
|
||||
COMMANDS = (
|
||||
'--steps','-s',
|
||||
@ -55,13 +56,14 @@ COMMANDS = (
|
||||
'--inpaint_replace','-r',
|
||||
'--png_compression','-z',
|
||||
'--text_mask','-tm',
|
||||
'!fix','!fetch','!history','!search','!clear',
|
||||
'!fix','!fetch','!replay','!history','!search','!clear',
|
||||
'!models','!switch','!import_model','!edit_model','!del_model',
|
||||
'!mask',
|
||||
'!models','!switch','!import_model','!edit_model'
|
||||
)
|
||||
MODEL_COMMANDS = (
|
||||
'!switch',
|
||||
'!edit_model',
|
||||
'!del_model',
|
||||
)
|
||||
WEIGHT_COMMANDS = (
|
||||
'!import_model',
|
||||
@ -69,6 +71,9 @@ WEIGHT_COMMANDS = (
|
||||
IMG_PATH_COMMANDS = (
|
||||
'--outdir[=\s]',
|
||||
)
|
||||
TEXT_PATH_COMMANDS=(
|
||||
'!replay',
|
||||
)
|
||||
IMG_FILE_COMMANDS=(
|
||||
'!fix',
|
||||
'!fetch',
|
||||
@ -78,8 +83,9 @@ IMG_FILE_COMMANDS=(
|
||||
'--init_color[=\s]',
|
||||
'--embedding_path[=\s]',
|
||||
)
|
||||
path_regexp = '('+'|'.join(IMG_PATH_COMMANDS+IMG_FILE_COMMANDS) + ')\s*\S*$'
|
||||
weight_regexp = '('+'|'.join(WEIGHT_COMMANDS) + ')\s*\S*$'
|
||||
path_regexp = '(' + '|'.join(IMG_PATH_COMMANDS+IMG_FILE_COMMANDS) + ')\s*\S*$'
|
||||
weight_regexp = '(' + '|'.join(WEIGHT_COMMANDS) + ')\s*\S*$'
|
||||
text_regexp = '(' + '|'.join(TEXT_PATH_COMMANDS) + ')\s*\S*$'
|
||||
|
||||
class Completer(object):
|
||||
def __init__(self, options, models=[]):
|
||||
@ -122,6 +128,9 @@ class Completer(object):
|
||||
elif re.search(weight_regexp,buffer):
|
||||
self.matches = self._path_completions(text, state, WEIGHT_EXTENSIONS)
|
||||
|
||||
elif re.search(text_regexp,buffer):
|
||||
self.matches = self._path_completions(text, state, TEXT_EXTENSIONS)
|
||||
|
||||
# This is the first time for this text, so build a match list.
|
||||
elif text:
|
||||
self.matches = [
|
||||
@ -210,9 +219,24 @@ class Completer(object):
|
||||
pydoc.pager('\n'.join(lines))
|
||||
|
||||
def set_line(self,line)->None:
|
||||
'''
|
||||
Set the default string displayed in the next line of input.
|
||||
'''
|
||||
self.linebuffer = line
|
||||
readline.redisplay()
|
||||
|
||||
def add_model(self,model_name:str)->None:
|
||||
'''
|
||||
add a model name to the completion list
|
||||
'''
|
||||
self.models.append(model_name)
|
||||
|
||||
def del_model(self,model_name:str)->None:
|
||||
'''
|
||||
removes a model name from the completion list
|
||||
'''
|
||||
self.models.remove(model_name)
|
||||
|
||||
def _seed_completions(self, text, state):
|
||||
m = re.search('(-S\s?|--seed[=\s]?)(\d*)',text)
|
||||
if m:
|
||||
|
||||
@ -60,14 +60,18 @@ class ESRGAN():
|
||||
print(
|
||||
f'>> Real-ESRGAN Upscaling seed:{seed} : scale:{upsampler_scale}x'
|
||||
)
|
||||
|
||||
# REALSRGAN expects a BGR np array; make array and flip channels
|
||||
bgr_image_array = np.array(image, dtype=np.uint8)[...,::-1]
|
||||
|
||||
output, _ = upsampler.enhance(
|
||||
np.array(image, dtype=np.uint8),
|
||||
bgr_image_array,
|
||||
outscale=upsampler_scale,
|
||||
alpha_upsampler='realesrgan',
|
||||
)
|
||||
|
||||
res = Image.fromarray(output)
|
||||
# Flip the channels back to RGB
|
||||
res = Image.fromarray(output[...,::-1])
|
||||
|
||||
if strength < 1.0:
|
||||
# Resize the image to the new image if the sizes have changed
|
||||
|
||||
@ -64,7 +64,8 @@ def make_ddim_timesteps(
|
||||
):
|
||||
if ddim_discr_method == 'uniform':
|
||||
c = num_ddpm_timesteps // num_ddim_timesteps
|
||||
# ddim_timesteps = np.asarray(list(range(0, num_ddpm_timesteps, c)))
|
||||
if c < 1:
|
||||
c = 1
|
||||
ddim_timesteps = (np.arange(0, num_ddim_timesteps) * c).astype(int)
|
||||
elif ddim_discr_method == 'quad':
|
||||
ddim_timesteps = (
|
||||
|
||||
26
main.py
26
main.py
@ -439,7 +439,7 @@ class ImageLogger(Callback):
|
||||
self.rescale = rescale
|
||||
self.batch_freq = batch_frequency
|
||||
self.max_images = max_images
|
||||
self.logger_log_images = { pl.loggers.TestTubeLogger: self._testtube, } if torch.cuda.is_available() else { }
|
||||
self.logger_log_images = { }
|
||||
self.log_steps = [
|
||||
2**n for n in range(int(np.log2(self.batch_freq)) + 1)
|
||||
]
|
||||
@ -451,17 +451,6 @@ class ImageLogger(Callback):
|
||||
self.log_images_kwargs = log_images_kwargs if log_images_kwargs else {}
|
||||
self.log_first_step = log_first_step
|
||||
|
||||
@rank_zero_only
|
||||
def _testtube(self, pl_module, images, batch_idx, split):
|
||||
for k in images:
|
||||
grid = torchvision.utils.make_grid(images[k])
|
||||
grid = (grid + 1.0) / 2.0 # -1,1 -> 0,1; c,h,w
|
||||
|
||||
tag = f'{split}/{k}'
|
||||
pl_module.logger.experiment.add_image(
|
||||
tag, grid, global_step=pl_module.global_step
|
||||
)
|
||||
|
||||
@rank_zero_only
|
||||
def log_local(
|
||||
self, save_dir, split, images, global_step, current_epoch, batch_idx
|
||||
@ -714,7 +703,7 @@ if __name__ == '__main__':
|
||||
# merge trainer cli with config
|
||||
trainer_config = lightning_config.get('trainer', OmegaConf.create())
|
||||
# default to ddp
|
||||
trainer_config['accelerator'] = 'ddp'
|
||||
trainer_config['accelerator'] = 'auto'
|
||||
for k in nondefault_trainer_args(opt):
|
||||
trainer_config[k] = getattr(opt, k)
|
||||
if not 'gpus' in trainer_config:
|
||||
@ -751,12 +740,8 @@ if __name__ == '__main__':
|
||||
trainer_kwargs = dict()
|
||||
|
||||
# default logger configs
|
||||
if torch.cuda.is_available():
|
||||
def_logger = 'testtube'
|
||||
def_logger_target = 'TestTubeLogger'
|
||||
else:
|
||||
def_logger = 'csv'
|
||||
def_logger_target = 'CSVLogger'
|
||||
def_logger = 'csv'
|
||||
def_logger_target = 'CSVLogger'
|
||||
default_logger_cfgs = {
|
||||
'wandb': {
|
||||
'target': 'pytorch_lightning.loggers.WandbLogger',
|
||||
@ -918,7 +903,8 @@ if __name__ == '__main__':
|
||||
config.model.base_learning_rate,
|
||||
)
|
||||
if not cpu:
|
||||
ngpu = len(lightning_config.trainer.gpus.strip(',').split(','))
|
||||
gpus = str(lightning_config.trainer.gpus).strip(', ').split(',')
|
||||
ngpu = len(gpus)
|
||||
else:
|
||||
ngpu = 1
|
||||
if 'accumulate_grad_batches' in lightning_config.trainer:
|
||||
|
||||
@ -17,9 +17,15 @@ from ldm.invoke.pngwriter import PngWriter, retrieve_metadata, write_metadata
|
||||
from ldm.invoke.image_util import make_grid
|
||||
from ldm.invoke.log import write_log
|
||||
from omegaconf import OmegaConf
|
||||
from pathlib import Path
|
||||
|
||||
# global used in multiple functions (fix)
|
||||
infile = None
|
||||
|
||||
def main():
|
||||
"""Initialize command-line parsers and the diffusion model"""
|
||||
global infile
|
||||
|
||||
opt = Args()
|
||||
args = opt.parse_args()
|
||||
if not args:
|
||||
@ -48,7 +54,6 @@ def main():
|
||||
os.makedirs(opt.outdir)
|
||||
|
||||
# load the infile as a list of lines
|
||||
infile = None
|
||||
if opt.infile:
|
||||
try:
|
||||
if os.path.isfile(opt.infile):
|
||||
@ -96,14 +101,16 @@ def main():
|
||||
)
|
||||
|
||||
try:
|
||||
main_loop(gen, opt, infile)
|
||||
main_loop(gen, opt)
|
||||
except KeyboardInterrupt:
|
||||
print("\ngoodbye!")
|
||||
|
||||
# TODO: main_loop() has gotten busy. Needs to be refactored.
|
||||
def main_loop(gen, opt, infile):
|
||||
def main_loop(gen, opt):
|
||||
"""prompt/read/execute loop"""
|
||||
global infile
|
||||
done = False
|
||||
doneAfterInFile = infile is not None
|
||||
path_filter = re.compile(r'[<>:"/\\|?*]')
|
||||
last_results = list()
|
||||
model_config = OmegaConf.load(opt.conf)
|
||||
@ -130,7 +137,8 @@ def main_loop(gen, opt, infile):
|
||||
try:
|
||||
command = get_next_command(infile)
|
||||
except EOFError:
|
||||
done = True
|
||||
done = infile is None or doneAfterInFile
|
||||
infile = None
|
||||
continue
|
||||
|
||||
# skip empty lines
|
||||
@ -368,7 +376,10 @@ def main_loop(gen, opt, infile):
|
||||
|
||||
print('goodbye!')
|
||||
|
||||
# TO DO: remove repetitive code and the awkward command.replace() trope
|
||||
# Just do a simple parse of the command!
|
||||
def do_command(command:str, gen, opt:Args, completer) -> tuple:
|
||||
global infile
|
||||
operation = 'generate' # default operation, alternative is 'postprocess'
|
||||
|
||||
if command.startswith('!dream'): # in case a stored prompt still contains the !dream command
|
||||
@ -413,9 +424,26 @@ def do_command(command:str, gen, opt:Args, completer) -> tuple:
|
||||
completer.add_history(command)
|
||||
operation = None
|
||||
|
||||
elif command.startswith('!del'):
|
||||
path = shlex.split(command)
|
||||
if len(path) < 2:
|
||||
print('** please provide the name of a model')
|
||||
else:
|
||||
del_config(path[1], gen, opt, completer)
|
||||
completer.add_history(command)
|
||||
operation = None
|
||||
|
||||
elif command.startswith('!fetch'):
|
||||
file_path = command.replace('!fetch ','',1)
|
||||
file_path = command.replace('!fetch','',1).strip()
|
||||
retrieve_dream_command(opt,file_path,completer)
|
||||
completer.add_history(command)
|
||||
operation = None
|
||||
|
||||
elif command.startswith('!replay'):
|
||||
file_path = command.replace('!replay','',1).strip()
|
||||
if infile is None and os.path.isfile(file_path):
|
||||
infile = open(file_path, 'r', encoding='utf-8')
|
||||
completer.add_history(command)
|
||||
operation = None
|
||||
|
||||
elif command.startswith('!history'):
|
||||
@ -423,7 +451,7 @@ def do_command(command:str, gen, opt:Args, completer) -> tuple:
|
||||
operation = None
|
||||
|
||||
elif command.startswith('!search'):
|
||||
search_str = command.replace('!search ','',1)
|
||||
search_str = command.replace('!search','',1).strip()
|
||||
completer.show_history(search_str)
|
||||
operation = None
|
||||
|
||||
@ -465,6 +493,16 @@ def add_weights_to_config(model_path:str, gen, opt, completer):
|
||||
new_config['config'] = input('Configuration file for this model: ')
|
||||
done = os.path.exists(new_config['config'])
|
||||
|
||||
done = False
|
||||
completer.complete_extensions(('.vae.pt','.vae','.ckpt'))
|
||||
while not done:
|
||||
vae = input('VAE autoencoder file for this model [None]: ')
|
||||
if os.path.exists(vae):
|
||||
new_config['vae'] = vae
|
||||
done = True
|
||||
else:
|
||||
done = len(vae)==0
|
||||
|
||||
completer.complete_extensions(None)
|
||||
|
||||
for field in ('width','height'):
|
||||
@ -479,9 +517,25 @@ def add_weights_to_config(model_path:str, gen, opt, completer):
|
||||
except:
|
||||
print('** Please enter a valid integer between 64 and 2048')
|
||||
|
||||
if write_config_file(opt.conf, gen, model_name, new_config):
|
||||
gen.set_model(model_name)
|
||||
make_default = input('Make this the default model? [n] ') in ('y','Y')
|
||||
|
||||
if write_config_file(opt.conf, gen, model_name, new_config, make_default=make_default):
|
||||
completer.add_model(model_name)
|
||||
|
||||
def del_config(model_name:str, gen, opt, completer):
|
||||
current_model = gen.model_name
|
||||
if model_name == current_model:
|
||||
print("** Can't delete active model. !switch to another model first. **")
|
||||
return
|
||||
yaml_str = gen.model_cache.del_model(model_name)
|
||||
|
||||
tmpfile = os.path.join(os.path.dirname(opt.conf),'new_config.tmp')
|
||||
with open(tmpfile, 'w') as outfile:
|
||||
outfile.write(yaml_str)
|
||||
os.rename(tmpfile,opt.conf)
|
||||
print(f'** {model_name} deleted')
|
||||
completer.del_model(model_name)
|
||||
|
||||
def edit_config(model_name:str, gen, opt, completer):
|
||||
config = gen.model_cache.config
|
||||
|
||||
@ -493,33 +547,46 @@ def edit_config(model_name:str, gen, opt, completer):
|
||||
|
||||
conf = config[model_name]
|
||||
new_config = {}
|
||||
completer.complete_extensions(('.yaml','.yml','.ckpt','.vae'))
|
||||
for field in ('description', 'weights', 'config', 'width','height'):
|
||||
completer.complete_extensions(('.yaml','.yml','.ckpt','.vae.pt'))
|
||||
for field in ('description', 'weights', 'vae', 'config', 'width','height'):
|
||||
completer.linebuffer = str(conf[field]) if field in conf else ''
|
||||
new_value = input(f'{field}: ')
|
||||
new_config[field] = int(new_value) if field in ('width','height') else new_value
|
||||
make_default = input('Make this the default model? [n] ') in ('y','Y')
|
||||
completer.complete_extensions(None)
|
||||
|
||||
if write_config_file(opt.conf, gen, model_name, new_config, clobber=True):
|
||||
gen.set_model(model_name)
|
||||
write_config_file(opt.conf, gen, model_name, new_config, clobber=True, make_default=make_default)
|
||||
|
||||
def write_config_file(conf_path, gen, model_name, new_config, clobber=False, make_default=False):
|
||||
current_model = gen.model_name
|
||||
|
||||
def write_config_file(conf_path, gen, model_name, new_config, clobber=False):
|
||||
op = 'modify' if clobber else 'import'
|
||||
print('\n>> New configuration:')
|
||||
if make_default:
|
||||
new_config['default'] = True
|
||||
print(yaml.dump({model_name:new_config}))
|
||||
if input(f'OK to {op} [n]? ') not in ('y','Y'):
|
||||
return False
|
||||
|
||||
try:
|
||||
print('>> Verifying that new model loads...')
|
||||
yaml_str = gen.model_cache.add_model(model_name, new_config, clobber)
|
||||
assert gen.set_model(model_name) is not None, 'model failed to load'
|
||||
except AssertionError as e:
|
||||
print(f'** configuration failed: {str(e)}')
|
||||
print(f'** aborting **')
|
||||
gen.model_cache.del_model(model_name)
|
||||
return False
|
||||
|
||||
if make_default:
|
||||
print('making this default')
|
||||
gen.model_cache.set_default_model(model_name)
|
||||
|
||||
gen.model_cache.commit(conf_path)
|
||||
|
||||
tmpfile = os.path.join(os.path.dirname(conf_path),'new_config.tmp')
|
||||
with open(tmpfile, 'w') as outfile:
|
||||
outfile.write(yaml_str)
|
||||
os.rename(tmpfile,conf_path)
|
||||
do_switch = input(f'Keep model loaded? [y]')
|
||||
if len(do_switch)==0 or do_switch[0] in ('y','Y'):
|
||||
pass
|
||||
else:
|
||||
gen.set_model(current_model)
|
||||
return True
|
||||
|
||||
def do_textmask(gen, opt, callback):
|
||||
@ -579,7 +646,10 @@ def add_postprocessing_to_metadata(opt,original_file,new_file,tool,command):
|
||||
original_file = original_file if os.path.exists(original_file) else os.path.join(opt.outdir,original_file)
|
||||
new_file = new_file if os.path.exists(new_file) else os.path.join(opt.outdir,new_file)
|
||||
meta = retrieve_metadata(original_file)['sd-metadata']
|
||||
img_data = meta['image']
|
||||
if 'image' not in meta:
|
||||
meta = metadata_dumps(opt,seeds=[opt.seed])['image']
|
||||
meta['image'] = {}
|
||||
img_data = meta.get('image')
|
||||
pp = img_data.get('postprocessing',[]) or []
|
||||
pp.append(
|
||||
{
|
||||
@ -723,27 +793,63 @@ def make_step_callback(gen, opt, prefix):
|
||||
image.save(filename,'PNG')
|
||||
return callback
|
||||
|
||||
def retrieve_dream_command(opt,file_path,completer):
|
||||
def retrieve_dream_command(opt,command,completer):
|
||||
'''
|
||||
Given a full or partial path to a previously-generated image file,
|
||||
will retrieve and format the dream command used to generate the image,
|
||||
and pop it into the readline buffer (linux, Mac), or print out a comment
|
||||
for cut-and-paste (windows)
|
||||
Given a wildcard path to a folder with image png files,
|
||||
will retrieve and format the dream command used to generate the images,
|
||||
and save them to a file commands.txt for further processing
|
||||
'''
|
||||
if len(command) == 0:
|
||||
return
|
||||
tokens = command.split()
|
||||
if len(tokens) > 1:
|
||||
outfilepath = tokens[1]
|
||||
else:
|
||||
outfilepath = "commands.txt"
|
||||
|
||||
file_path = tokens[0]
|
||||
dir,basename = os.path.split(file_path)
|
||||
if len(dir) == 0:
|
||||
path = os.path.join(opt.outdir,basename)
|
||||
else:
|
||||
path = file_path
|
||||
dir = opt.outdir
|
||||
|
||||
outdir,outname = os.path.split(outfilepath)
|
||||
if len(outdir) == 0:
|
||||
outfilepath = os.path.join(dir,outname)
|
||||
try:
|
||||
cmd = dream_cmd_from_png(path)
|
||||
except OSError:
|
||||
print(f'** {path}: file could not be read')
|
||||
paths = list(Path(dir).glob(basename))
|
||||
except ValueError:
|
||||
print(f'## "{basename}": unacceptable pattern')
|
||||
return
|
||||
except (KeyError, AttributeError):
|
||||
print(f'** {path}: file has no metadata')
|
||||
return
|
||||
completer.set_line(cmd)
|
||||
|
||||
commands = []
|
||||
for path in paths:
|
||||
try:
|
||||
cmd = dream_cmd_from_png(path)
|
||||
except OSError:
|
||||
print(f'## {path}: file could not be read')
|
||||
continue
|
||||
except (KeyError, AttributeError, IndexError):
|
||||
print(f'## {path}: file has no metadata')
|
||||
continue
|
||||
except:
|
||||
print(f'## {path}: file could not be processed')
|
||||
continue
|
||||
|
||||
commands.append(f'# {path}')
|
||||
commands.append(cmd)
|
||||
|
||||
with open(outfilepath, 'w', encoding='utf-8') as f:
|
||||
f.write('\n'.join(commands))
|
||||
print(f'>> File {outfilepath} with commands created')
|
||||
|
||||
if len(commands) == 2:
|
||||
completer.set_line(commands[1])
|
||||
|
||||
######################################
|
||||
|
||||
if __name__ == '__main__':
|
||||
main()
|
||||
|
||||
Loading…
Reference in New Issue
Block a user