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Move CropLatentsCoreInvocation to its own file. No functional changes.

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This commit is contained in:
Ryan Dick 2024-06-05 10:53:24 -04:00
parent 0b37496c57
commit ed03d281e6
2 changed files with 61 additions and 56 deletions
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61
invokeai/app/invocations/crop_latents.py Normal file
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@ -0,0 +1,61 @@
from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
from invokeai.app.invocations.constants import LATENT_SCALE_FACTOR
from invokeai.app.invocations.fields import FieldDescriptions, Input, InputField, LatentsField
from invokeai.app.invocations.primitives import LatentsOutput
from invokeai.app.services.shared.invocation_context import InvocationContext
# The Crop Latents node was copied from @skunkworxdark's implementation here:
# https://github.com/skunkworxdark/XYGrid_nodes/blob/74647fa9c1fa57d317a94bd43ca689af7f0aae5e/images_to_grids.py#L1117C1-L1167C80
@invocation(
"crop_latents",
title="Crop Latents",
tags=["latents", "crop"],
category="latents",
version="1.0.2",
)
# TODO(ryand): Named `CropLatentsCoreInvocation` to prevent a conflict with custom node `CropLatentsInvocation`.
# Currently, if the class names conflict then 'GET /openapi.json' fails.
class CropLatentsCoreInvocation(BaseInvocation):
"""Crops a latent-space tensor to a box specified in image-space. The box dimensions and coordinates must be
divisible by the latent scale factor of 8.
"""
latents: LatentsField = InputField(
description=FieldDescriptions.latents,
input=Input.Connection,
)
x: int = InputField(
ge=0,
multiple_of=LATENT_SCALE_FACTOR,
description="The left x coordinate (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
)
y: int = InputField(
ge=0,
multiple_of=LATENT_SCALE_FACTOR,
description="The top y coordinate (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
)
width: int = InputField(
ge=1,
multiple_of=LATENT_SCALE_FACTOR,
description="The width (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
)
height: int = InputField(
ge=1,
multiple_of=LATENT_SCALE_FACTOR,
description="The height (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
)
def invoke(self, context: InvocationContext) -> LatentsOutput:
latents = context.tensors.load(self.latents.latents_name)
x1 = self.x // LATENT_SCALE_FACTOR
y1 = self.y // LATENT_SCALE_FACTOR
x2 = x1 + (self.width // LATENT_SCALE_FACTOR)
y2 = y1 + (self.height // LATENT_SCALE_FACTOR)
cropped_latents = latents[..., y1:y2, x1:x2]
name = context.tensors.save(tensor=cropped_latents)
return LatentsOutput.build(latents_name=name, latents=cropped_latents)

56
invokeai/app/invocations/latent.py
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@ -1391,59 +1391,3 @@ class BlendLatentsInvocation(BaseInvocation):
name = context.tensors.save(tensor=blended_latents)
return LatentsOutput.build(latents_name=name, latents=blended_latents, seed=self.latents_a.seed)
# The Crop Latents node was copied from @skunkworxdark's implementation here:
# https://github.com/skunkworxdark/XYGrid_nodes/blob/74647fa9c1fa57d317a94bd43ca689af7f0aae5e/images_to_grids.py#L1117C1-L1167C80
@invocation(
"crop_latents",
title="Crop Latents",
tags=["latents", "crop"],
category="latents",
version="1.0.2",
)
# TODO(ryand): Named `CropLatentsCoreInvocation` to prevent a conflict with custom node `CropLatentsInvocation`.
# Currently, if the class names conflict then 'GET /openapi.json' fails.
class CropLatentsCoreInvocation(BaseInvocation):
"""Crops a latent-space tensor to a box specified in image-space. The box dimensions and coordinates must be
divisible by the latent scale factor of 8.
"""
latents: LatentsField = InputField(
description=FieldDescriptions.latents,
input=Input.Connection,
)
x: int = InputField(
ge=0,
multiple_of=LATENT_SCALE_FACTOR,
description="The left x coordinate (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
)
y: int = InputField(
ge=0,
multiple_of=LATENT_SCALE_FACTOR,
description="The top y coordinate (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
)
width: int = InputField(
ge=1,
multiple_of=LATENT_SCALE_FACTOR,
description="The width (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
)
height: int = InputField(
ge=1,
multiple_of=LATENT_SCALE_FACTOR,
description="The height (in px) of the crop rectangle in image space. This value will be converted to a dimension in latent space.",
)
def invoke(self, context: InvocationContext) -> LatentsOutput:
latents = context.tensors.load(self.latents.latents_name)
x1 = self.x // LATENT_SCALE_FACTOR
y1 = self.y // LATENT_SCALE_FACTOR
x2 = x1 + (self.width // LATENT_SCALE_FACTOR)
y2 = y1 + (self.height // LATENT_SCALE_FACTOR)
cropped_latents = latents[..., y1:y2, x1:x2]
name = context.tensors.save(tensor=cropped_latents)
return LatentsOutput.build(latents_name=name, latents=cropped_latents)