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https://github.com/invoke-ai/InvokeAI
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feat(nodes): add resize image and scale image nodes
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@ -416,6 +416,115 @@ class ImageBlurInvocation(BaseInvocation, PILInvocationConfig):
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)
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PIL_RESAMPLING_MODES = Literal[
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"nearest",
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"box",
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"bilinear",
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"hamming",
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"bicubic",
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"lanczos",
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]
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PIL_RESAMPLING_MAP = {
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"nearest": Image.Resampling.NEAREST,
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"box": Image.Resampling.BOX,
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"bilinear": Image.Resampling.BILINEAR,
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"hamming": Image.Resampling.HAMMING,
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"bicubic": Image.Resampling.BICUBIC,
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"lanczos": Image.Resampling.LANCZOS,
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}
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class ImageResizeInvocation(BaseInvocation, PILInvocationConfig):
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"""Resizes an image to specific dimensions"""
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# fmt: off
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type: Literal["img_resize"] = "img_resize"
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# Inputs
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image: Union[ImageField, None] = Field(default=None, description="The image to resize")
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width: int = Field(ge=64, multiple_of=8, description="The width to resize to (px)")
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height: int = Field(ge=64, multiple_of=8, description="The height to resize to (px)")
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resample_mode: PIL_RESAMPLING_MODES = Field(default="bicubic", description="The resampling mode")
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# fmt: on
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def invoke(self, context: InvocationContext) -> ImageOutput:
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image = context.services.images.get_pil_image(
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self.image.image_origin, self.image.image_name
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)
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resample_mode = PIL_RESAMPLING_MAP[self.resample_mode]
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resize_image = image.resize(
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(self.width, self.height),
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resample=resample_mode,
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)
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image_dto = context.services.images.create(
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image=resize_image,
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image_origin=ResourceOrigin.INTERNAL,
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image_category=ImageCategory.GENERAL,
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node_id=self.id,
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session_id=context.graph_execution_state_id,
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is_intermediate=self.is_intermediate,
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)
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return ImageOutput(
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image=ImageField(
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image_name=image_dto.image_name,
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image_origin=image_dto.image_origin,
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),
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width=image_dto.width,
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height=image_dto.height,
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)
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class ImageScaleInvocation(BaseInvocation, PILInvocationConfig):
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"""Scales an image by a factor"""
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# fmt: off
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type: Literal["img_scale"] = "img_scale"
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# Inputs
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image: Union[ImageField, None] = Field(default=None, description="The image to scale")
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scale_factor: float = Field(gt=0, description="The factor by which to scale the image")
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resample_mode: PIL_RESAMPLING_MODES = Field(default="bicubic", description="The resampling mode")
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# fmt: on
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def invoke(self, context: InvocationContext) -> ImageOutput:
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image = context.services.images.get_pil_image(
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self.image.image_origin, self.image.image_name
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)
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resample_mode = PIL_RESAMPLING_MAP[self.resample_mode]
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width = int(image.width * self.scale_factor)
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height = int(image.height * self.scale_factor)
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resize_image = image.resize(
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(width, height),
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resample=resample_mode,
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)
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image_dto = context.services.images.create(
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image=resize_image,
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image_origin=ResourceOrigin.INTERNAL,
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image_category=ImageCategory.GENERAL,
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node_id=self.id,
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session_id=context.graph_execution_state_id,
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is_intermediate=self.is_intermediate,
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)
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return ImageOutput(
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image=ImageField(
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image_name=image_dto.image_name,
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image_origin=image_dto.image_origin,
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),
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width=image_dto.width,
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height=image_dto.height,
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)
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class ImageLerpInvocation(BaseInvocation, PILInvocationConfig):
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"""Linear interpolation of all pixels of an image"""
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