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adjust scale factor logic

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This commit is contained in:
Ethan Weber 2023-01-30 19:53:39 +00:00
parent 9e992b9550
commit 0bb199d9e9
1 changed files with 7 additions and 3 deletions
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10
nerfstudio/data/datamanagers/base_datamanager.py
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@ -432,9 +432,13 @@ class VanillaDataManager(DataManager): # pylint: disable=abstract-method
# image_batch["image"].shape == (1, H, W, 3)
# this will sample the entire image
# we downsample the image so it fits in memory
image_batch["image"] = torch.nn.functional.interpolate(
image_batch["image"].permute(0, 3, 1, 2), scale_factor=scale_factor, mode="bilinear", align_corners=False
).permute(0, 2, 3, 1)
if scale_factor != 1.0:
image_batch["image"] = torch.nn.functional.interpolate(
image_batch["image"].permute(0, 3, 1, 2),
scale_factor=scale_factor,
mode="bilinear",
align_corners=False,
).permute(0, 2, 3, 1)
batch = self.eval_pixel_sampler.sample(image_batch, sample_all_pixels=True)
ray_indices = batch["indices"]