Files
ComfyUI-Tween/utils/padder.py
Ethanfel db64fc195a Initial commit: ComfyUI BIM-VFI node for video frame interpolation
Wraps BiM-VFI (CVPR 2025) as a ComfyUI custom node for long video
frame interpolation with memory-safe sequential processing.

- LoadBIMVFIModel: checkpoint loader with auto-download from Google Drive
- BIMVFIInterpolate: 2x/4x/8x recursive interpolation with per-pair
  GPU processing, configurable VRAM management (all_on_gpu for high-VRAM
  setups), progress bar, and backwarp cache clearing
- Vendored inference-only architecture from KAIST-VICLab/BiM-VFI
- Auto-detection of CUDA version for cupy installation

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-12 18:26:49 +01:00

29 lines
955 B
Python

import torch.nn.functional as F
class InputPadder:
""" Pads images such that dimensions are divisible by divisor """
def __init__(self, dims, divisor=16):
self.ht, self.wd = dims[-2:]
pad_ht = (((self.ht // divisor) + 1) * divisor - self.ht) % divisor
pad_wd = (((self.wd // divisor) + 1) * divisor - self.wd) % divisor
self._pad = [0, pad_wd, 0, pad_ht]
def pad(self, *inputs):
if len(inputs) == 1:
return F.pad(inputs[0], self._pad, mode='constant')
else:
return [F.pad(x, self._pad, mode='constant') for x in inputs]
def unpad(self, *inputs):
if len(inputs) == 1:
return self._unpad(inputs[0])
else:
return [self._unpad(x) for x in inputs]
def _unpad(self, x):
ht, wd = x.shape[-2:]
c = [self._pad[2], ht - self._pad[3], self._pad[0], wd - self._pad[1]]
return x[..., c[0]:c[1], c[2]:c[3]]