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Includes 30 custom nodes committed directly, 7 Civitai-exclusive loras stored via Git LFS, and a setup script that installs all dependencies and downloads HuggingFace-hosted models on vast.ai. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
28 lines
1007 B
Python
28 lines
1007 B
Python
import torchvision.transforms.functional as TF
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def img_tensor_mae(tensor1, tensor2):
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"""Calculate the mean absolute difference between two image tensors."""
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# Remove batch dimensions if present
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tensor1 = tensor1.squeeze(0).cpu()
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tensor2 = tensor2.squeeze(0).cpu()
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if tensor1.shape != tensor2.shape:
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raise ValueError(
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f"Tensors must have the same shape for comparison. Got {tensor1.shape=} and {tensor2.shape=}."
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)
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return (tensor1 - tensor2).abs().mean().item()
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def blur(tensor, kernel_size=9, sigma=None):
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"""Apply Gaussian blur to an image tensor."""
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# [1, H, W, C] -> [1, C, H, W]
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if tensor.ndim == 4:
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tensor = tensor.permute(0, 3, 1, 2)
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elif tensor.ndim == 3:
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tensor = tensor.permute(2, 0, 1).unsqueeze(0)
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else:
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raise ValueError(f"Expected a 3D or 4D tensor, got {tensor.ndim=}")
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return TF.gaussian_blur(tensor, kernel_size=kernel_size, sigma=sigma).permute( # type: ignore
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0, 2, 3, 1
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)
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