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Merge branch 'main' into feat/controlnet_extras

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blessedcoolant 2023-06-28 17:36:21 +12:00 committed by GitHub
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6 changed files with 87 additions and 87 deletions
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37
invokeai/app/invocations/param_easing.py
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@ -133,20 +133,19 @@ class StepParamEasingInvocation(BaseInvocation):
postlist = list(num_poststeps * [self.post_end_value]) postlist = list(num_poststeps * [self.post_end_value])
if log_diagnostics: if log_diagnostics:
logger = InvokeAILogger.getLogger(name="StepParamEasing") context.services.logger.debug("start_step: " + str(start_step))
logger.debug("start_step: " + str(start_step)) context.services.logger.debug("end_step: " + str(end_step))
logger.debug("end_step: " + str(end_step)) context.services.logger.debug("num_easing_steps: " + str(num_easing_steps))
logger.debug("num_easing_steps: " + str(num_easing_steps)) context.services.logger.debug("num_presteps: " + str(num_presteps))
logger.debug("num_presteps: " + str(num_presteps)) context.services.logger.debug("num_poststeps: " + str(num_poststeps))
logger.debug("num_poststeps: " + str(num_poststeps)) context.services.logger.debug("prelist size: " + str(len(prelist)))
logger.debug("prelist size: " + str(len(prelist))) context.services.logger.debug("postlist size: " + str(len(postlist)))
logger.debug("postlist size: " + str(len(postlist))) context.services.logger.debug("prelist: " + str(prelist))
logger.debug("prelist: " + str(prelist)) context.services.logger.debug("postlist: " + str(postlist))
logger.debug("postlist: " + str(postlist))
easing_class = EASING_FUNCTIONS_MAP[self.easing] easing_class = EASING_FUNCTIONS_MAP[self.easing]
if log_diagnostics: if log_diagnostics:
logger.debug("easing class: " + str(easing_class)) context.services.logger.debug("easing class: " + str(easing_class))
easing_list = list() easing_list = list()
if self.mirror: # "expected" mirroring if self.mirror: # "expected" mirroring
# if number of steps is even, squeeze duration down to (number_of_steps)/2 # if number of steps is even, squeeze duration down to (number_of_steps)/2
@ -156,7 +155,7 @@ class StepParamEasingInvocation(BaseInvocation):
# but if even then number_of_steps/2 === ceil(number_of_steps/2), so can just use ceil always # but if even then number_of_steps/2 === ceil(number_of_steps/2), so can just use ceil always
base_easing_duration = int(np.ceil(num_easing_steps/2.0)) base_easing_duration = int(np.ceil(num_easing_steps/2.0))
if log_diagnostics: logger.debug("base easing duration: " + str(base_easing_duration)) if log_diagnostics: context.services.logger.debug("base easing duration: " + str(base_easing_duration))
even_num_steps = (num_easing_steps % 2 == 0) # even number of steps even_num_steps = (num_easing_steps % 2 == 0) # even number of steps
easing_function = easing_class(start=self.start_value, easing_function = easing_class(start=self.start_value,
end=self.end_value, end=self.end_value,
@ -166,14 +165,14 @@ class StepParamEasingInvocation(BaseInvocation):
easing_val = easing_function.ease(step_index) easing_val = easing_function.ease(step_index)
base_easing_vals.append(easing_val) base_easing_vals.append(easing_val)
if log_diagnostics: if log_diagnostics:
logger.debug("step_index: " + str(step_index) + ", easing_val: " + str(easing_val)) context.services.logger.debug("step_index: " + str(step_index) + ", easing_val: " + str(easing_val))
if even_num_steps: if even_num_steps:
mirror_easing_vals = list(reversed(base_easing_vals)) mirror_easing_vals = list(reversed(base_easing_vals))
else: else:
mirror_easing_vals = list(reversed(base_easing_vals[0:-1])) mirror_easing_vals = list(reversed(base_easing_vals[0:-1]))
if log_diagnostics: if log_diagnostics:
logger.debug("base easing vals: " + str(base_easing_vals)) context.services.logger.debug("base easing vals: " + str(base_easing_vals))
logger.debug("mirror easing vals: " + str(mirror_easing_vals)) context.services.logger.debug("mirror easing vals: " + str(mirror_easing_vals))
easing_list = base_easing_vals + mirror_easing_vals easing_list = base_easing_vals + mirror_easing_vals
# FIXME: add alt_mirror option (alternative to default or mirror), or remove entirely # FIXME: add alt_mirror option (alternative to default or mirror), or remove entirely
@ -206,12 +205,12 @@ class StepParamEasingInvocation(BaseInvocation):
step_val = easing_function.ease(step_index) step_val = easing_function.ease(step_index)
easing_list.append(step_val) easing_list.append(step_val)
if log_diagnostics: if log_diagnostics:
logger.debug("step_index: " + str(step_index) + ", easing_val: " + str(step_val)) context.services.logger.debug("step_index: " + str(step_index) + ", easing_val: " + str(step_val))
if log_diagnostics: if log_diagnostics:
logger.debug("prelist size: " + str(len(prelist))) context.services.logger.debug("prelist size: " + str(len(prelist)))
logger.debug("easing_list size: " + str(len(easing_list))) context.services.logger.debug("easing_list size: " + str(len(easing_list)))
logger.debug("postlist size: " + str(len(postlist))) context.services.logger.debug("postlist size: " + str(len(postlist)))
param_list = prelist + easing_list + postlist param_list = prelist + easing_list + postlist

2
invokeai/frontend/web/src/features/dynamicPrompts/components/ParamDynamicPromptsCollapse.tsx
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@ -35,8 +35,8 @@ const ParamDynamicPromptsCollapse = () => {
withSwitch withSwitch
> >
<Flex sx={{ gap: 2, flexDir: 'column' }}> <Flex sx={{ gap: 2, flexDir: 'column' }}>
<ParamDynamicPromptsMaxPrompts />
<ParamDynamicPromptsCombinatorial /> <ParamDynamicPromptsCombinatorial />
<ParamDynamicPromptsMaxPrompts />
</Flex> </Flex>
</IAICollapse> </IAICollapse>
); );

8
invokeai/frontend/web/src/features/dynamicPrompts/components/ParamDynamicPromptsMaxPrompts.tsx
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@ -9,17 +9,18 @@ import { stateSelector } from 'app/store/store';
const selector = createSelector( const selector = createSelector(
stateSelector, stateSelector,
(state) => { (state) => {
const { maxPrompts } = state.dynamicPrompts; const { maxPrompts, combinatorial } = state.dynamicPrompts;
const { min, sliderMax, inputMax } = const { min, sliderMax, inputMax } =
state.config.sd.dynamicPrompts.maxPrompts; state.config.sd.dynamicPrompts.maxPrompts;
return { maxPrompts, min, sliderMax, inputMax }; return { maxPrompts, min, sliderMax, inputMax, combinatorial };
}, },
defaultSelectorOptions defaultSelectorOptions
); );
const ParamDynamicPromptsMaxPrompts = () => { const ParamDynamicPromptsMaxPrompts = () => {
const { maxPrompts, min, sliderMax, inputMax } = useAppSelector(selector); const { maxPrompts, min, sliderMax, inputMax, combinatorial } =
useAppSelector(selector);
const dispatch = useAppDispatch(); const dispatch = useAppDispatch();
const handleChange = useCallback( const handleChange = useCallback(
@ -36,6 +37,7 @@ const ParamDynamicPromptsMaxPrompts = () => {
return ( return (
<IAISlider <IAISlider
label="Max Prompts" label="Max Prompts"
isDisabled={!combinatorial}
min={min} min={min}
max={sliderMax} max={sliderMax}
value={maxPrompts} value={maxPrompts}

2
invokeai/frontend/web/src/features/nodes/util/graphBuilders/addDynamicPromptsToGraph.ts
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@ -37,7 +37,7 @@ export const addDynamicPromptsToGraph = (
const dynamicPromptNode: DynamicPromptInvocation = { const dynamicPromptNode: DynamicPromptInvocation = {
id: DYNAMIC_PROMPT, id: DYNAMIC_PROMPT,
type: 'dynamic_prompt', type: 'dynamic_prompt',
max_prompts: maxPrompts, max_prompts: combinatorial ? maxPrompts : iterations,
combinatorial, combinatorial,
prompt: positivePrompt, prompt: positivePrompt,
}; };

3
invokeai/frontend/web/src/features/parameters/components/Parameters/Core/ParamIterations.tsx
View File

@ -16,7 +16,8 @@ const selector = createSelector([stateSelector], (state) => {
state.config.sd.iterations; state.config.sd.iterations;
const { iterations } = state.generation; const { iterations } = state.generation;
const { shouldUseSliders } = state.ui; const { shouldUseSliders } = state.ui;
const isDisabled = state.dynamicPrompts.isEnabled; const isDisabled =
state.dynamicPrompts.isEnabled && state.dynamicPrompts.combinatorial;
const step = state.hotkeys.shift ? fineStep : coarseStep; const step = state.hotkeys.shift ? fineStep : coarseStep;

122
invokeai/frontend/web/src/services/api/types.d.ts vendored
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@ -4,91 +4,89 @@ import { components } from './schema';
type schemas = components['schemas']; type schemas = components['schemas'];
/** /**
* Helper type to extract the invocation type from the schema. * Extracts the schema type from the schema.
* Also flags the `type` property as required.
*/ */
type Invocation<T extends keyof schemas> = O.Required<schemas[T], 'type'>; type S<T extends keyof components['schemas']> = components['schemas'][T];
/** /**
* Types from the API, re-exported from the types generated by `openapi-typescript`. * Extracts the node type from the schema.
* Also flags the `type` property as required.
*/ */
type N<T extends keyof components['schemas']> = O.Required<
components['schemas'][T],
'type'
>;
// Images // Images
export type ImageDTO = schemas['ImageDTO']; export type ImageDTO = S<'ImageDTO'>;
export type BoardDTO = schemas['BoardDTO']; export type BoardDTO = S<'BoardDTO'>;
export type BoardChanges = schemas['BoardChanges']; export type BoardChanges = S<'BoardChanges'>;
export type ImageChanges = schemas['ImageRecordChanges']; export type ImageChanges = S<'ImageRecordChanges'>;
export type ImageCategory = schemas['ImageCategory']; export type ImageCategory = S<'ImageCategory'>;
export type ResourceOrigin = schemas['ResourceOrigin']; export type ResourceOrigin = S<'ResourceOrigin'>;
export type ImageField = schemas['ImageField']; export type ImageField = S<'ImageField'>;
export type OffsetPaginatedResults_BoardDTO_ = export type OffsetPaginatedResults_BoardDTO_ =
schemas['OffsetPaginatedResults_BoardDTO_']; S<'OffsetPaginatedResults_BoardDTO_'>;
export type OffsetPaginatedResults_ImageDTO_ = export type OffsetPaginatedResults_ImageDTO_ =
schemas['OffsetPaginatedResults_ImageDTO_']; S<'OffsetPaginatedResults_ImageDTO_'>;
// Models // Models
export type ModelType = schemas['ModelType']; export type ModelType = S<'ModelType'>;
export type BaseModelType = schemas['BaseModelType']; export type BaseModelType = S<'BaseModelType'>;
export type PipelineModelField = schemas['PipelineModelField']; export type PipelineModelField = S<'PipelineModelField'>;
export type ModelsList = schemas['ModelsList']; export type ModelsList = S<'ModelsList'>;
// Graphs // Graphs
export type Graph = schemas['Graph']; export type Graph = S<'Graph'>;
export type Edge = schemas['Edge']; export type Edge = S<'Edge'>;
export type GraphExecutionState = schemas['GraphExecutionState']; export type GraphExecutionState = S<'GraphExecutionState'>;
// General nodes // General nodes
export type CollectInvocation = Invocation<'CollectInvocation'>; export type CollectInvocation = N<'CollectInvocation'>;
export type IterateInvocation = Invocation<'IterateInvocation'>; export type IterateInvocation = N<'IterateInvocation'>;
export type RangeInvocation = Invocation<'RangeInvocation'>; export type RangeInvocation = N<'RangeInvocation'>;
export type RandomRangeInvocation = Invocation<'RandomRangeInvocation'>; export type RandomRangeInvocation = N<'RandomRangeInvocation'>;
export type RangeOfSizeInvocation = Invocation<'RangeOfSizeInvocation'>; export type RangeOfSizeInvocation = N<'RangeOfSizeInvocation'>;
export type InpaintInvocation = Invocation<'InpaintInvocation'>; export type InpaintInvocation = N<'InpaintInvocation'>;
export type ImageResizeInvocation = Invocation<'ImageResizeInvocation'>; export type ImageResizeInvocation = N<'ImageResizeInvocation'>;
export type RandomIntInvocation = Invocation<'RandomIntInvocation'>; export type RandomIntInvocation = N<'RandomIntInvocation'>;
export type CompelInvocation = Invocation<'CompelInvocation'>; export type CompelInvocation = N<'CompelInvocation'>;
export type DynamicPromptInvocation = Invocation<'DynamicPromptInvocation'>; export type DynamicPromptInvocation = N<'DynamicPromptInvocation'>;
export type NoiseInvocation = Invocation<'NoiseInvocation'>; export type NoiseInvocation = N<'NoiseInvocation'>;
export type TextToLatentsInvocation = Invocation<'TextToLatentsInvocation'>; export type TextToLatentsInvocation = N<'TextToLatentsInvocation'>;
export type LatentsToLatentsInvocation = export type LatentsToLatentsInvocation = N<'LatentsToLatentsInvocation'>;
Invocation<'LatentsToLatentsInvocation'>; export type ImageToLatentsInvocation = N<'ImageToLatentsInvocation'>;
export type ImageToLatentsInvocation = Invocation<'ImageToLatentsInvocation'>; export type LatentsToImageInvocation = N<'LatentsToImageInvocation'>;
export type LatentsToImageInvocation = Invocation<'LatentsToImageInvocation'>; export type PipelineModelLoaderInvocation = N<'PipelineModelLoaderInvocation'>;
export type PipelineModelLoaderInvocation =
Invocation<'PipelineModelLoaderInvocation'>;
// ControlNet Nodes // ControlNet Nodes
export type ControlNetInvocation = Invocation<'ControlNetInvocation'>; export type ControlNetInvocation = N<'ControlNetInvocation'>;
export type CannyImageProcessorInvocation = export type CannyImageProcessorInvocation = N<'CannyImageProcessorInvocation'>;
Invocation<'CannyImageProcessorInvocation'>;
export type ContentShuffleImageProcessorInvocation = export type ContentShuffleImageProcessorInvocation =
Invocation<'ContentShuffleImageProcessorInvocation'>; N<'ContentShuffleImageProcessorInvocation'>;
export type HedImageProcessorInvocation = export type HedImageProcessorInvocation = N<'HedImageProcessorInvocation'>;
Invocation<'HedImageProcessorInvocation'>;
export type LineartAnimeImageProcessorInvocation = export type LineartAnimeImageProcessorInvocation =
Invocation<'LineartAnimeImageProcessorInvocation'>; N<'LineartAnimeImageProcessorInvocation'>;
export type LineartImageProcessorInvocation = export type LineartImageProcessorInvocation =
Invocation<'LineartImageProcessorInvocation'>; N<'LineartImageProcessorInvocation'>;
export type MediapipeFaceProcessorInvocation = export type MediapipeFaceProcessorInvocation =
Invocation<'MediapipeFaceProcessorInvocation'>; N<'MediapipeFaceProcessorInvocation'>;
export type MidasDepthImageProcessorInvocation = export type MidasDepthImageProcessorInvocation =
Invocation<'MidasDepthImageProcessorInvocation'>; N<'MidasDepthImageProcessorInvocation'>;
export type MlsdImageProcessorInvocation = export type MlsdImageProcessorInvocation = N<'MlsdImageProcessorInvocation'>;
Invocation<'MlsdImageProcessorInvocation'>;
export type NormalbaeImageProcessorInvocation = export type NormalbaeImageProcessorInvocation =
Invocation<'NormalbaeImageProcessorInvocation'>; N<'NormalbaeImageProcessorInvocation'>;
export type OpenposeImageProcessorInvocation = export type OpenposeImageProcessorInvocation =
Invocation<'OpenposeImageProcessorInvocation'>; N<'OpenposeImageProcessorInvocation'>;
export type PidiImageProcessorInvocation = export type PidiImageProcessorInvocation = N<'PidiImageProcessorInvocation'>;
Invocation<'PidiImageProcessorInvocation'>;
export type ZoeDepthImageProcessorInvocation = export type ZoeDepthImageProcessorInvocation =
Invocation<'ZoeDepthImageProcessorInvocation'>; N<'ZoeDepthImageProcessorInvocation'>;
// Node Outputs // Node Outputs
export type ImageOutput = schemas['ImageOutput']; export type ImageOutput = S<'ImageOutput'>;
export type MaskOutput = schemas['MaskOutput']; export type MaskOutput = S<'MaskOutput'>;
export type PromptOutput = schemas['PromptOutput']; export type PromptOutput = S<'PromptOutput'>;
export type IterateInvocationOutput = schemas['IterateInvocationOutput']; export type IterateInvocationOutput = S<'IterateInvocationOutput'>;
export type CollectInvocationOutput = schemas['CollectInvocationOutput']; export type CollectInvocationOutput = S<'CollectInvocationOutput'>;
export type LatentsOutput = schemas['LatentsOutput']; export type LatentsOutput = S<'LatentsOutput'>;
export type GraphInvocationOutput = schemas['GraphInvocationOutput']; export type GraphInvocationOutput = S<'GraphInvocationOutput'>;