Ethanfel
1de086569c
Integrate EMA-VFI alongside existing BIM-VFI with three new ComfyUI nodes: Load EMA-VFI Model, EMA-VFI Interpolate, and EMA-VFI Segment Interpolate. Architecture files vendored from MCG-NJU/EMA-VFI with device-awareness fixes (removed hardcoded .cuda() calls), warp cache management, and relative imports. InputPadder extended to support EMA-VFI's replicate center-symmetric padding. Auto-installs timm dependency on first load. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
import torch.nn.functional as F
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class InputPadder:
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""" Pads images such that dimensions are divisible by divisor """
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def __init__(self, dims, divisor=16, mode='constant', center=False):
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self.ht, self.wd = dims[-2:]
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self.mode = mode
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pad_ht = (((self.ht // divisor) + 1) * divisor - self.ht) % divisor
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pad_wd = (((self.wd // divisor) + 1) * divisor - self.wd) % divisor
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if center:
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self._pad = [pad_wd // 2, pad_wd - pad_wd // 2,
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pad_ht // 2, pad_ht - pad_ht // 2]
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else:
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self._pad = [0, pad_wd, 0, pad_ht]
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def pad(self, *inputs):
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if len(inputs) == 1:
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return F.pad(inputs[0], self._pad, mode=self.mode)
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else:
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return [F.pad(x, self._pad, mode=self.mode) for x in inputs]
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def unpad(self, *inputs):
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if len(inputs) == 1:
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return self._unpad(inputs[0])
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else:
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return [self._unpad(x) for x in inputs]
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def _unpad(self, x):
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ht, wd = x.shape[-2:]
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c = [self._pad[2], ht - self._pad[3], self._pad[0], wd - self._pad[1]]
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return x[..., c[0]:c[1], c[2]:c[3]]
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