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Fix semantic NeRF config bug (#838)

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Fix semantic nerf config bug

Co-authored-by: adolhasz <adolhasz@matterport.com>
This commit is contained in:
dolhaszandadolhasz authored and GitHub committed 2022-10-27 08:44:34 +03:00
1 parent 359f955f3f
commit def6ba5c51
1 file changed
+5 -5
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nerfstudio/models/semantic_nerfw.py
+5 -5
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@@ -102,9 +102,9 @@ class SemanticNerfWModel(Model):
if self.config.use_same_proposal_network:
network = HashMLPDensityField(self.scene_box.aabb, spatial_distortion=scene_contraction)
self.proposal_networks.append(network)
self.density_fns = [network.density_fn for _ in range(self.config.num_proposal_network_iterations)]
self.density_fns = [network.density_fn for _ in range(self.config.num_proposal_iterations)]
else:
for _ in range(self.config.num_proposal_network_iterations):
for _ in range(self.config.num_proposal_iterations):
network = HashMLPDensityField(self.scene_box.aabb, spatial_distortion=scene_contraction)
self.proposal_networks.append(network)
self.density_fns = [network.density_fn for network in self.proposal_networks]
@@ -116,7 +116,7 @@ class SemanticNerfWModel(Model):
self.proposal_sampler = ProposalNetworkSampler(
num_nerf_samples_per_ray=self.config.num_nerf_samples_per_ray,
num_proposal_samples_per_ray=self.config.num_proposal_samples_per_ray,
num_proposal_network_iterations=self.config.num_proposal_network_iterations,
num_proposal_network_iterations=self.config.num_proposal_iterations,
single_jitter=self.config.use_single_jitter,
)
@@ -193,7 +193,7 @@ class SemanticNerfWModel(Model):
outputs["weights_list"] = weights_list
outputs["ray_samples_list"] = ray_samples_list
for i in range(self.config.num_proposal_network_iterations):
for i in range(self.config.num_proposal_iterations):
outputs[f"prop_depth_{i}"] = self.renderer_depth(weights=weights_list[i], ray_samples=ray_samples_list[i])
# transients
@@ -286,7 +286,7 @@ class SemanticNerfWModel(Model):
images_dict = {"img": combined_rgb, "accumulation": combined_acc, "depth": combined_depth}
for i in range(self.config.num_proposal_network_iterations):
for i in range(self.config.num_proposal_iterations):
key = f"prop_depth_{i}"
prop_depth_i = colormaps.apply_depth_colormap(
outputs[key],