From 67c4e7d98dcc5d7ec4089c2dea269553a43b3b7b Mon Sep 17 00:00:00 2001 From: Eugene Fairley Date: Fri, 11 Jul 2025 10:19:13 -0700 Subject: [PATCH] Remove extra functions --- comfy_extras/nodes_wan.py | 45 --------------------------------------- 1 file changed, 45 deletions(-) diff --git a/comfy_extras/nodes_wan.py b/comfy_extras/nodes_wan.py index a2485933e..483502ae6 100644 --- a/comfy_extras/nodes_wan.py +++ b/comfy_extras/nodes_wan.py @@ -416,7 +416,6 @@ def parse_json_tracks(tracks): tracks_data = [] return tracks_data - def tracks_to_tensor(tracks_data, length, width, height, batch_size=1): """Convert parsed track data to tensor format (B, T, N, 4)""" if not tracks_data: @@ -447,50 +446,6 @@ def tracks_to_tensor(tracks_data, length, width, height, batch_size=1): return tracks_tensor - -def ind_sel(target: torch.Tensor, ind: torch.Tensor, dim: int = 1): - """Index selection utility function""" - assert ( - len(ind.shape) > dim - ), "Index must have the target dim, but get dim: %d, ind shape: %s" % (dim, str(ind.shape)) - - target = target.expand( - *tuple( - [ind.shape[k] if target.shape[k] == 1 else -1 for k in range(dim)] - + [ - -1, - ] - * (len(target.shape) - dim) - ) - ) - - ind_pad = ind - - if len(target.shape) > dim + 1: - for _ in range(len(target.shape) - (dim + 1)): - ind_pad = ind_pad.unsqueeze(-1) - ind_pad = ind_pad.expand(*(-1,) * (dim + 1), *target.shape[(dim + 1) : :]) - - return torch.gather(target, dim=dim, index=ind_pad) - - -def merge_final(vert_attr: torch.Tensor, weight: torch.Tensor, vert_assign: torch.Tensor): - """Merge vertex attributes with weights""" - target_dim = len(vert_assign.shape) - 1 - if len(vert_attr.shape) == 2: - assert vert_attr.shape[0] > vert_assign.max() - new_shape = [1] * target_dim + list(vert_attr.shape) - tensor = vert_attr.reshape(new_shape) - sel_attr = ind_sel(tensor, vert_assign.type(torch.long), dim=target_dim) - else: - assert vert_attr.shape[1] > vert_assign.max() - new_shape = [vert_attr.shape[0]] + [1] * (target_dim - 1) + list(vert_attr.shape[1:]) - tensor = vert_attr.reshape(new_shape) - sel_attr = ind_sel(tensor, vert_assign.type(torch.long), dim=target_dim) - - final_attr = torch.sum(sel_attr * weight.unsqueeze(-1), dim=-2) - return final_attr - def process_tracks(tracks_np: np.ndarray, frame_size: Tuple[int, int], num_frames, quant_multi: int = 8, **kwargs): # tracks: shape [t, h, w, 3] => samples align with 24 fps, model trained with 16 fps. # frame_size: tuple (W, H)