delet pre-installed unidepth

flash3d/networks/unidepth_extension.py

@@ -4,7 +4,6 @@ import torch.nn.functional as F
 from einops import rearrange
 
 from .unidepth import UniDepthDepth
-from unidepth.models import UniDepthV1
 from .resnet_encoder import ResnetEncoder
 from .gaussian_decoder import GaussianDecoder
 from .depth_decoder import DepthDecoder
@@ -20,7 +19,6 @@ class UniDepthExtended(nn.Module):
         self.cfg = cfg
 
         self.unidepth = UniDepthDepth(cfg)
-        # self.unidepth = UniDepthV1.from_pretrained("lpiccinelli/unidepth-v1-vitl14")
 
         self.parameters_to_train = []
         if self.cfg.model.splat_branch == "resnet":
@@ -129,17 +127,7 @@ class UniDepthExtended(nn.Module):
             depth_outs["depth"] = inputs[('unidepth', 0, 0)]
         else:
             with torch.no_grad():
-                # if self.training and self.cfg.dataset.pad_border_aug > 0:
-                #     pad = self.cfg.dataset.pad_border_aug
-                #     input = inputs["color_aug", 0, 0][:,:,pad:-pad, pad:-pad]
-                #     intrincs = inputs[("K_tgt", 0)]
-                # else:
-                #     input = inputs["color_aug", 0, 0]
-                #     intrincs = inputs[("K_src", 0)]
                 _, depth_outs = self.unidepth(inputs)
-                # depth_outs = self.unidepth.infer(input, intrincs)
-                # if self.training and self.cfg.dataset.pad_border_aug > 0:
-                #     depth_outs["depth"] = F.pad(depth_outs["depth"], (pad,pad,pad,pad), mode="replicate")
 
         outputs_gauss = {}