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fix:correction of PairPixelSampler in case of using masks with depth-nerfacto #2477

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merged 3 commits into from Sep 29, 2023
Merged

fix:correction of PairPixelSampler in case of using masks with depth-nerfacto #2477

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7188d62
fix:correction of PairPixelSampler in case of using masks
pierremerriaux-leddartech Sep 28, 2023
27ebd29
Merge branch 'main' into pierremerriaux/depthNerfacto_PairPixelSample…
pierremerriaux-leddartech Sep 29, 2023
bcb5add
Merge branch 'main' into pierremerriaux/depthNerfacto_PairPixelSample…
pierremerriaux-leddartech Sep 29, 2023
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17 changes: 9 additions & 8 deletions nerfstudio/data/pixel_samplers.py
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Expand Up @@ -399,10 +399,11 @@ def sample_method( # pylint: disable=no-self-use
mask: Optional[Tensor] = None,
device: Union[torch.device, str] = "cpu",
) -> Int[Tensor, "batch_size 3"]:
rays_to_sample = self.rays_to_sample
if isinstance(mask, Tensor):
m = erode_mask(mask.permute(0, 3, 1, 2).float(), pixel_radius=self.radius)
nonzero_indices = torch.nonzero(m[:, 0], as_tuple=False).to(device)
chosen_indices = random.sample(range(len(nonzero_indices)), k=self.rays_to_sample)
chosen_indices = random.sample(range(len(nonzero_indices)), k=rays_to_sample)
indices = nonzero_indices[chosen_indices]
else:
rays_to_sample = self.rays_to_sample
Expand All @@ -418,12 +419,12 @@ def sample_method( # pylint: disable=no-self-use
ws = torch.randint(self.radius, image_width - self.radius, s, dtype=torch.long, device=device)
indices = torch.concat((ns, hs, ws), dim=1)

pair_indices = torch.hstack(
(
torch.zeros(rays_to_sample, 1, device=device, dtype=torch.long),
torch.randint(-self.radius, self.radius, (rays_to_sample, 2), device=device, dtype=torch.long),
)
pair_indices = torch.hstack(
(
torch.zeros(rays_to_sample, 1, device=device, dtype=torch.long),
torch.randint(-self.radius, self.radius, (rays_to_sample, 2), device=device, dtype=torch.long),
)
pair_indices += indices
indices = torch.hstack((indices, pair_indices)).view(rays_to_sample * 2, 3)
)
pair_indices += indices
indices = torch.hstack((indices, pair_indices)).view(rays_to_sample * 2, 3)
return indices