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ToniRV / NeRF-SLAM

NeRF-SLAM: Real-Time Dense Monocular SLAM with Neural Radiance Fields. https://arxiv.org/abs/2210.13641 + Sigma-Fusion: Probabilistic Volumetric Fusion for Dense Monocular SLAM https://arxiv.org/abs/2210.01276
BSD 2-Clause "Simplified" License
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TypeError: push_back(): incompatible function arguments. The following argument types are supported: 1. (self: gtsam.gtsam.GaussianFactorGraph, factor: gtsam.gtsam.GaussianFactor) -> None 2. (self: gtsam.gtsam.GaussianFactorGraph, conditional: gtsam::GaussianConditional) -> None 3. (self: gtsam.gtsam.GaussianFactorGraph, graph: gtsam.gtsam.GaussianFactorGraph) -> None 4. (self: gtsam.gtsam.GaussianFactorGraph, bayesNet: gtsam::GaussianBayesNet) -> None 5. (self: gtsam.gtsam.GaussianFactorGraph, bayesTree: gtsam::GaussianBayesTree) -> None #47

Open 1005452649 opened 1 year ago

1005452649 commented 1 year ago

Traceback (most recent call last): File "./examples/slam_demo.py", line 200, in run(args) File "./examples/slam_demo.py", line 143, in run slam_module.spin() # visualizer should be the main spin, but pytorch has a memory bug/leak if threaded... File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../pipeline/pipeline_module.py", line 101, in spin output = self.spin_once(input); File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/slam_module.py", line 11, in spin_once output = self.slam(input) File "/home/user/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl return forward_call(*input, kwargs) File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/meta_slam.py", line 30, in forward output = self._frontend(batch["data"], self.state, self.delta) File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/vio_slam.py", line 119, in _frontend x0_visual, visual_factors, viz_out = self.visual_frontend(batch) # TODO: currently also calls BA, and global BA File "/home/user/.local/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl return forward_call(*input, *kwargs) File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/visual_frontends/visual_frontend.py", line 331, in forward self.initialize() File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/visual_frontends/visual_frontend.py", line 655, in initialize x0, rcm_factor = self.update(kf0=None, kf1=None, use_inactive=True) File "/home/user/.local/lib/python3.8/site-packages/torch/amp/autocast_mode.py", line 14, in decorate_autocast return func(args, kwargs) File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/visual_frontends/visual_frontend.py", line 444, in update x0, rcm_factor = self.ba(gru_estimated_flow, gru_estimated_flow_weight, damping, File "/home/user/linzejun01/linzejun_mutiply_view01/NeRF-SLAM/./examples/../slam/visual_frontends/visual_frontend.py", line 1143, in ba linear_factor_graph.push_back(vision_factors) TypeError: push_back(): incompatible function arguments. The following argument types are supported:

  1. (self: gtsam.gtsam.GaussianFactorGraph, factor: gtsam.gtsam.GaussianFactor) -> None
  2. (self: gtsam.gtsam.GaussianFactorGraph, conditional: gtsam::GaussianConditional) -> None
  3. (self: gtsam.gtsam.GaussianFactorGraph, graph: gtsam.gtsam.GaussianFactorGraph) -> None
  4. (self: gtsam.gtsam.GaussianFactorGraph, bayesNet: gtsam::GaussianBayesNet) -> None
  5. (self: gtsam.gtsam.GaussianFactorGraph, bayesTree: gtsam::GaussianBayesTree) -> None
1005452649 commented 1 year ago

@jrpowers can you help me?

Wqiyu commented 1 year ago

I have the same question, is it solved?