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46 lines
2.0 KiB
Python
46 lines
2.0 KiB
Python
from typing import Literal
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from invokeai.app.invocations.baseinvocation import BaseInvocation, invocation
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from invokeai.app.invocations.fields import ImageField, InputField, WithBoard, WithMetadata
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from invokeai.app.invocations.primitives import ImageOutput
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from invokeai.app.services.shared.invocation_context import InvocationContext
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from invokeai.backend.image_util.depth_anything.depth_anything_pipeline import DepthAnythingPipeline
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DEPTH_ANYTHING_MODEL_SIZES = Literal["large", "base", "small", "small_v2"]
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# DepthAnything V2 Small model is licensed under Apache 2.0 but not the base and large models.
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DEPTH_ANYTHING_MODELS = {
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"large": "LiheYoung/depth-anything-large-hf",
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"base": "LiheYoung/depth-anything-base-hf",
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"small": "LiheYoung/depth-anything-small-hf",
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"small_v2": "depth-anything/Depth-Anything-V2-Small-hf",
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}
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@invocation(
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"depth_anything_depth_estimation",
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title="Depth Anything Depth Estimation",
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tags=["controlnet", "depth", "depth anything"],
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category="controlnet_preprocessors",
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version="1.0.0",
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)
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class DepthAnythingDepthEstimationInvocation(BaseInvocation, WithMetadata, WithBoard):
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"""Generates a depth map using a Depth Anything model."""
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image: ImageField = InputField(description="The image to process")
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model_size: DEPTH_ANYTHING_MODEL_SIZES = InputField(
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default="small_v2", description="The size of the depth model to use"
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)
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def invoke(self, context: InvocationContext) -> ImageOutput:
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model_url = DEPTH_ANYTHING_MODELS[self.model_size]
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image = context.images.get_pil(self.image.image_name, "RGB")
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loaded_model = context.models.load_remote_model(model_url, DepthAnythingPipeline.load_model)
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with loaded_model as depth_anything_detector:
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assert isinstance(depth_anything_detector, DepthAnythingPipeline)
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depth_map = depth_anything_detector.generate_depth(image)
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image_dto = context.images.save(image=depth_map)
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return ImageOutput.build(image_dto)
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