hofee/nbv_reconstruction
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hofee
2024-10-29 08:14:43 +00:00
parent 9e39c6c6c9 63a246c0c8
commit b13e45bafc
5 changed files with 33 additions and 37 deletions
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9
core/global_pts_n_num_pipeline.py
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@@ -121,19 +121,20 @@ class NBVReconstructionGlobalPointsPipeline(nn.Module):
for seq_idx in range(seq_len):
partial_idx_in_combined_pts = scanned_mask == seq_idx # Ndarray(V), N->V idx mask
partial_perpoint_feat = perpoint_scanned_feat[partial_idx_in_combined_pts] # Ndarray(V x Dl)
partial_feat = torch.max(partial_perpoint_feat, dim=0) # Tensor(Dl)
partial_feat = torch.mean(partial_perpoint_feat, dim=0) # Tensor(Dl)
partial_feat_seq.append(partial_feat)
scanned_target_pts_num.append(partial_perpoint_feat.shape[0])
scanned_target_pts_num = torch.tensor(scanned_target_pts_num, dtype=torch.float32).to(device).unsqueeze(-1) # Tensor(S)
scanned_n_to_world_pose_9d = scanned_n_to_world_pose_9d.to(device) # Tensor(S x 9)
scanned_target_pts_num = torch.tensor(scanned_target_pts_num, dtype=torch.float32).unsqueeze(-1).to(device) # Tensor(S x 1)
scanned_n_to_world_pose_9d = scanned_n_to_world_pose_9d.to(device) # Tensor(S x 9)
pose_feat_seq = self.pose_encoder.encode_pose(scanned_n_to_world_pose_9d) # Tensor(S x Dp)
pts_num_feat_seq = self.pts_num_encoder.encode_pts_num(scanned_target_pts_num) # Tensor(S x Dn)
partial_feat_seq = torch.stack(partial_feat_seq) # Tensor(S x Dl)
seq_embedding = torch.cat([pose_feat_seq, pts_num_feat_seq, partial_feat_seq], dim=-1) # Tensor(S x (Dp+Dn+Dl))
embedding_list_batch.append(seq_embedding) # List(B): Tensor(S x (Dp+Dn+Dl))
seq_feat = self.transformer_seq_encoder.encode_sequence(embedding_list_batch) # Tensor(B x Ds)
main_feat = torch.cat([seq_feat, global_scanned_feat], dim=-1) # Tensor(B x (Ds+Dg))

3
core/nbv_dataset.py
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@@ -34,7 +34,7 @@ class NBVReconstructionDataset(BaseDataset):
#self.model_dir = config["model_dir"]
self.filter_degree = config["filter_degree"]
if self.type == namespace.Mode.TRAIN:
scale_ratio = 1
scale_ratio = 100
self.datalist = self.datalist*scale_ratio
if self.cache:
expr_root = ConfigManager.get("runner", "experiment", "root_dir")
@@ -174,6 +174,7 @@ class NBVReconstructionDataset(BaseDataset):
combined_scanned_views_pts_mask[start_idx:end_idx] = i
start_idx = end_idx
fps_downsampled_combined_scanned_pts_mask = combined_scanned_views_pts_mask[fps_idx]
data_item = {
"scanned_pts": np.asarray(scanned_views_pts, dtype=np.float32), # Ndarray(S x Nv x 3)
"scanned_pts_mask": np.asarray(fps_downsampled_combined_scanned_pts_mask,dtype=np.uint8), # Ndarray(N), range(0, S)