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AttributeError: 'NoneType' object has no attribute 'cluster_poses' #89

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aghaphd opened this issue Apr 25, 2024 · 10 comments
Closed

AttributeError: 'NoneType' object has no attribute 'cluster_poses' #89

aghaphd opened this issue Apr 25, 2024 · 10 comments

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@aghaphd
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aghaphd commented Apr 25, 2024

(my) root@5f6626e587fd:/workspace# python run_demo.py
Warp 1.0.2 initialized:
CUDA Toolkit 11.5, Driver 11.4
Devices:
"cpu" : "x86_64"
"cuda:0" : "NVIDIA GeForce RTX 3070 Ti Laptop GPU" (8 GiB, sm_86, mempool enabled)
Kernel cache:
/root/.cache/warp/1.0.2
[init()] self.cfg:
lr: 0.0001
c_in: 6
zfar: 'Infinity'
debug: null
n_view: 1
run_id: 3wy8qqex
use_BN: true
exp_name: 2024-01-11-20-02-45
n_epochs: 62
save_dir: /home/ali/Downloads/FoundationPose/debug/2024-01-11-20-02-45/
use_mask: false
loss_type: pairwise_valid
optimizer: adam
batch_size: 64
crop_ratio: 1.1
enable_amp: true
use_normal: false
max_num_key: null
warmup_step: -1
input_resize:

  • 160
  • 160
    max_step_val: 1000
    vis_interval: 1000
    weight_decay: 0
    normalize_xyz: true
    resume_run_id: null
    clip_grad_norm: 'Infinity'
    lr_epoch_decay: 500
    render_backend: nvdiffrast
    train_num_pair: 5
    lr_decay_epochs:
  • 50
    n_epochs_warmup: 1
    make_pair_online: false
    gradient_max_norm: 'Infinity'
    max_step_per_epoch: 10000
    n_rendering_workers: 1
    save_epoch_interval: 100
    n_dataloader_workers: 100
    split_objects_across_gpus: true
    ckpt_dir: /workspace/learning/training/../../weights/2024-01-11-20-02-45/model_best.pth

[init()] self.h5_file:None
[init()] Using pretrained model from /workspace/learning/training/../../weights/2024-01-11-20-02-45/model_best.pth
[init()] init done
[init()] welcome
[init()] self.cfg:
lr: 0.0001
c_in: 6
zfar: .inf
debug: null
w_rot: 0.1
n_view: 1
run_id: null
use_BN: true
rot_rep: axis_angle
ckpt_dir: /workspace/learning/training/../../weights/2023-10-28-18-33-37/model_best.pth
exp_name: 2023-10-28-18-33-37
save_dir: /tmp/2023-10-28-18-33-37/
loss_type: l2
optimizer: adam
trans_rep: tracknet
batch_size: 64
crop_ratio: 1.2
use_normal: false
BN_momentum: 0.1
max_num_key: null
warmup_step: -1
input_resize:

  • 160
  • 160
    max_step_val: 1000
    normal_uint8: false
    vis_interval: 1000
    weight_decay: 0
    n_max_objects: null
    normalize_xyz: true
    clip_grad_norm: 'Infinity'
    rot_normalizer: 0.3490658503988659
    trans_normalizer:
  • 0.019999999552965164
  • 0.019999999552965164
  • 0.05000000074505806
    max_step_per_epoch: 25000
    val_epoch_interval: 10
    n_dataloader_workers: 60
    enable_amp: true
    use_mask: false

[init()] self.h5_file:
[init()] Using pretrained model from /workspace/learning/training/../../weights/2023-10-28-18-33-37/model_best.pth
[init()] init done
[reset_object()] self.diameter:0.19646325799497472, vox_size:0.009823162899748735
[reset_object()] self.pts:torch.Size([607, 3])
[reset_object()] reset done
[make_rotation_grid()] cam_in_obs:(42, 4, 4)
[make_rotation_grid()] rot_grid:(252, 4, 4)
Traceback (most recent call last):
File "run_demo.py", line 41, in
est = FoundationPose(model_pts=mesh.vertices, model_normals=mesh.vertex_normals, mesh=mesh, scorer=scorer, refiner=refiner, debug_dir=debug_dir, debug=debug, glctx=glctx)
File "/workspace/estimater.py", line 27, in init
self.make_rotation_grid(min_n_views=40, inplane_step=60)
File "/workspace/estimater.py", line 120, in make_rotation_grid
rot_grid = mycpp.cluster_poses(30, 99999, rot_grid, self.symmetry_tfs.data.cpu().numpy())
AttributeError: 'NoneType' object has no attribute 'cluster_poses'
(my) root@5f6626e587fd:/workspace#

@aghaphd
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aghaphd commented Apr 25, 2024

Before I run python run_demo.py, I have run the build_all.sh:

(my) root@5f6626e587fd:/workspace# bash build_all.sh
CMake Error: The current CMakeCache.txt directory /workspace/mycpp/build/CMakeCache.txt is different than the directory /home/ali/Downloads/FoundationPose/mycpp/build where CMakeCache.txt was created. This may result in binaries being created in the wrong place. If you are not sure, reedit the CMakeCache.txt
CMake Error: The source "/workspace/mycpp/CMakeLists.txt" does not match the source "/home/ali/Downloads/FoundationPose/mycpp/CMakeLists.txt" used to generate cache. Re-run cmake with a different source directory.
Obtaining file:///kaolin
Preparing metadata (setup.py) ... done
Requirement already satisfied: ipycanvas in /opt/conda/envs/my/lib/python3.8/site-packages/ipycanvas-0.13.1-py3.8.egg (from kaolin==0.15.0) (0.13.1)
Requirement already satisfied: ipyevents in /opt/conda/envs/my/lib/python3.8/site-packages/ipyevents-2.0.2-py3.8.egg (from kaolin==0.15.0) (2.0.2)
Requirement already satisfied: jupyter_client<8 in /opt/conda/envs/my/lib/python3.8/site-packages/jupyter_client-7.4.9-py3.8.egg (from kaolin==0.15.0) (7.4.9)
Requirement already satisfied: pyzmq<25 in /opt/conda/envs/my/lib/python3.8/site-packages/pyzmq-24.0.1-py3.8-linux-x86_64.egg (from kaolin==0.15.0) (24.0.1)
Requirement already satisfied: flask in /opt/conda/envs/my/lib/python3.8/site-packages (from kaolin==0.15.0) (3.0.3)
Requirement already satisfied: tornado in /opt/conda/envs/my/lib/python3.8/site-packages/tornado-6.4-py3.8-linux-x86_64.egg (from kaolin==0.15.0) (6.4)
Requirement already satisfied: comm>=0.1.3 in /opt/conda/envs/my/lib/python3.8/site-packages (from kaolin==0.15.0) (0.2.2)
Requirement already satisfied: numpy in /opt/conda/envs/my/lib/python3.8/site-packages (from kaolin==0.15.0) (1.24.3)
Requirement already satisfied: pybind11 in /opt/conda/envs/my/lib/python3.8/site-packages/pybind11-2.12.0-py3.8.egg (from kaolin==0.15.0) (2.12.0)
Requirement already satisfied: Pillow>=8.0.0 in /opt/conda/envs/my/lib/python3.8/site-packages (from kaolin==0.15.0) (10.2.0)
Requirement already satisfied: tqdm>=4.51.0 in /opt/conda/envs/my/lib/python3.8/site-packages (from kaolin==0.15.0) (4.66.2)
Requirement already satisfied: scipy in /opt/conda/envs/my/lib/python3.8/site-packages (from kaolin==0.15.0) (1.10.1)
Requirement already satisfied: pygltflib in /opt/conda/envs/my/lib/python3.8/site-packages/pygltflib-1.16.2-py3.8.egg (from kaolin==0.15.0) (1.16.2)
Requirement already satisfied: usd-core<=23.5 in /opt/conda/envs/my/lib/python3.8/site-packages/usd_core-23.5-py3.8-linux-x86_64.egg (from kaolin==0.15.0) (23.5)
Requirement already satisfied: ipython<8.13 in /opt/conda/envs/my/lib/python3.8/site-packages (from kaolin==0.15.0) (8.12.3)
Requirement already satisfied: traitlets>=4 in /opt/conda/envs/my/lib/python3.8/site-packages (from comm>=0.1.3->kaolin==0.15.0) (5.14.3)
Requirement already satisfied: backcall in /opt/conda/envs/my/lib/python3.8/site-packages (from ipython<8.13->kaolin==0.15.0) (0.2.0)
Requirement already satisfied: decorator in /opt/conda/envs/my/lib/python3.8/site-packages (from ipython<8.13->kaolin==0.15.0) (5.1.1)
Requirement already satisfied: jedi>=0.16 in /opt/conda/envs/my/lib/python3.8/site-packages (from ipython<8.13->kaolin==0.15.0) (0.19.1)
Requirement already satisfied: matplotlib-inline in /opt/conda/envs/my/lib/python3.8/site-packages (from ipython<8.13->kaolin==0.15.0) (0.1.7)
Requirement already satisfied: pickleshare in /opt/conda/envs/my/lib/python3.8/site-packages (from ipython<8.13->kaolin==0.15.0) (0.7.5)
Requirement already satisfied: prompt-toolkit!=3.0.37,<3.1.0,>=3.0.30 in /opt/conda/envs/my/lib/python3.8/site-packages (from ipython<8.13->kaolin==0.15.0) (3.0.43)
Requirement already satisfied: pygments>=2.4.0 in /opt/conda/envs/my/lib/python3.8/site-packages (from ipython<8.13->kaolin==0.15.0) (2.17.2)
Requirement already satisfied: stack-data in /opt/conda/envs/my/lib/python3.8/site-packages (from ipython<8.13->kaolin==0.15.0) (0.6.3)
Requirement already satisfied: typing-extensions in /opt/conda/envs/my/lib/python3.8/site-packages (from ipython<8.13->kaolin==0.15.0) (4.9.0)
Requirement already satisfied: pexpect>4.3 in /opt/conda/envs/my/lib/python3.8/site-packages (from ipython<8.13->kaolin==0.15.0) (4.9.0)
Requirement already satisfied: entrypoints in /opt/conda/envs/my/lib/python3.8/site-packages/entrypoints-0.4-py3.8.egg (from jupyter_client<8->kaolin==0.15.0) (0.4)
Requirement already satisfied: jupyter-core>=4.9.2 in /opt/conda/envs/my/lib/python3.8/site-packages (from jupyter_client<8->kaolin==0.15.0) (5.7.2)
Requirement already satisfied: nest-asyncio>=1.5.4 in /opt/conda/envs/my/lib/python3.8/site-packages (from jupyter_client<8->kaolin==0.15.0) (1.6.0)
Requirement already satisfied: python-dateutil>=2.8.2 in /opt/conda/envs/my/lib/python3.8/site-packages (from jupyter_client<8->kaolin==0.15.0) (2.9.0.post0)
Requirement already satisfied: Werkzeug>=3.0.0 in /opt/conda/envs/my/lib/python3.8/site-packages (from flask->kaolin==0.15.0) (3.0.2)
Requirement already satisfied: Jinja2>=3.1.2 in /opt/conda/envs/my/lib/python3.8/site-packages (from flask->kaolin==0.15.0) (3.1.3)
Requirement already satisfied: itsdangerous>=2.1.2 in /opt/conda/envs/my/lib/python3.8/site-packages (from flask->kaolin==0.15.0) (2.2.0)
Requirement already satisfied: click>=8.1.3 in /opt/conda/envs/my/lib/python3.8/site-packages (from flask->kaolin==0.15.0) (8.1.7)
Requirement already satisfied: blinker>=1.6.2 in /opt/conda/envs/my/lib/python3.8/site-packages (from flask->kaolin==0.15.0) (1.7.0)
Requirement already satisfied: importlib-metadata>=3.6.0 in /opt/conda/envs/my/lib/python3.8/site-packages (from flask->kaolin==0.15.0) (7.1.0)
Requirement already satisfied: ipywidgets<9,>=7.6.0 in /opt/conda/envs/my/lib/python3.8/site-packages (from ipycanvas->kaolin==0.15.0) (8.1.2)
Requirement already satisfied: dataclasses-json>=0.0.25 in /opt/conda/envs/my/lib/python3.8/site-packages/dataclasses_json-0.6.4-py3.8.egg (from pygltflib->kaolin==0.15.0) (0.6.4)
Requirement already satisfied: deprecated in /opt/conda/envs/my/lib/python3.8/site-packages/Deprecated-1.2.14-py3.8.egg (from pygltflib->kaolin==0.15.0) (1.2.14)
Requirement already satisfied: marshmallow<4.0.0,>=3.18.0 in /opt/conda/envs/my/lib/python3.8/site-packages/marshmallow-3.21.1-py3.8.egg (from dataclasses-json>=0.0.25->pygltflib->kaolin==0.15.0) (3.21.1)
Requirement already satisfied: typing-inspect<1,>=0.4.0 in /opt/conda/envs/my/lib/python3.8/site-packages/typing_inspect-0.9.0-py3.8.egg (from dataclasses-json>=0.0.25->pygltflib->kaolin==0.15.0) (0.9.0)
Requirement already satisfied: zipp>=0.5 in /opt/conda/envs/my/lib/python3.8/site-packages (from importlib-metadata>=3.6.0->flask->kaolin==0.15.0) (3.18.1)
Requirement already satisfied: widgetsnbextension~=4.0.10 in /opt/conda/envs/my/lib/python3.8/site-packages (from ipywidgets<9,>=7.6.0->ipycanvas->kaolin==0.15.0) (4.0.10)
Requirement already satisfied: jupyterlab-widgets~=3.0.10 in /opt/conda/envs/my/lib/python3.8/site-packages (from ipywidgets<9,>=7.6.0->ipycanvas->kaolin==0.15.0) (3.0.10)
Requirement already satisfied: parso<0.9.0,>=0.8.3 in /opt/conda/envs/my/lib/python3.8/site-packages (from jedi>=0.16->ipython<8.13->kaolin==0.15.0) (0.8.4)
Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/envs/my/lib/python3.8/site-packages (from Jinja2>=3.1.2->flask->kaolin==0.15.0) (2.1.5)
Requirement already satisfied: platformdirs>=2.5 in /opt/conda/envs/my/lib/python3.8/site-packages (from jupyter-core>=4.9.2->jupyter_client<8->kaolin==0.15.0) (4.2.1)
Requirement already satisfied: ptyprocess>=0.5 in /opt/conda/envs/my/lib/python3.8/site-packages (from pexpect>4.3->ipython<8.13->kaolin==0.15.0) (0.7.0)
Requirement already satisfied: wcwidth in /opt/conda/envs/my/lib/python3.8/site-packages (from prompt-toolkit!=3.0.37,<3.1.0,>=3.0.30->ipython<8.13->kaolin==0.15.0) (0.2.13)
Requirement already satisfied: six>=1.5 in /opt/conda/envs/my/lib/python3.8/site-packages (from python-dateutil>=2.8.2->jupyter_client<8->kaolin==0.15.0) (1.16.0)
Requirement already satisfied: wrapt<2,>=1.10 in /opt/conda/envs/my/lib/python3.8/site-packages/wrapt-1.16.0-py3.8.egg (from deprecated->pygltflib->kaolin==0.15.0) (1.16.0)
Requirement already satisfied: executing>=1.2.0 in /opt/conda/envs/my/lib/python3.8/site-packages (from stack-data->ipython<8.13->kaolin==0.15.0) (2.0.1)
Requirement already satisfied: asttokens>=2.1.0 in /opt/conda/envs/my/lib/python3.8/site-packages (from stack-data->ipython<8.13->kaolin==0.15.0) (2.4.1)
Requirement already satisfied: pure-eval in /opt/conda/envs/my/lib/python3.8/site-packages (from stack-data->ipython<8.13->kaolin==0.15.0) (0.2.2)
Requirement already satisfied: packaging>=17.0 in /opt/conda/envs/my/lib/python3.8/site-packages (from marshmallow<4.0.0,>=3.18.0->dataclasses-json>=0.0.25->pygltflib->kaolin==0.15.0) (24.0)
Requirement already satisfied: mypy-extensions>=0.3.0 in /opt/conda/envs/my/lib/python3.8/site-packages/mypy_extensions-1.0.0-py3.8.egg (from typing-inspect<1,>=0.4.0->dataclasses-json>=0.0.25->pygltflib->kaolin==0.15.0) (1.0.0)
Installing collected packages: kaolin
Running setup.py develop for kaolin
Successfully installed kaolin-0.15.0
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
Obtaining file:///workspace/bundlesdf/mycuda
Preparing metadata (setup.py) ... done
Installing collected packages: common
Running setup.py develop for common
Successfully installed common-0.0.0
WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv

@wenbowen123
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image
did you run this?

@aghaphd
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aghaphd commented Apr 25, 2024 via email

@wenbowen123
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Then it should generate a .so file under the mycpp/build folder. Do you have it?

@aghaphd
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aghaphd commented Apr 25, 2024 via email

@aghaphd
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aghaphd commented Apr 25, 2024

Screenshot from 2024-04-26 02-17-11
yes, I have the mycpp.cpython-39-x86_64-linux-gnu.so inside mycpp/build.

@wenbowen123
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if you cd to mycpp/build, then python, then import mycpp, what happens?

@aghaphd
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aghaphd commented Apr 25, 2024

(my) root@5f6626e587fd:/workspace# ls
LICENSE bundlesdf kaolin run_demo.py
Utils.py datareader.py learning run_linemod.py
pycache debug mycpp run_ycb_video.py
assets demo_data offscreen_renderer.py weights
build_all.sh docker readme.md
build_all_conda.sh estimater.py requirements.txt
(my) root@5f6626e587fd:/workspace# cd mycpp
(my) root@5f6626e587fd:/workspace/mycpp# cd build
(my) root@5f6626e587fd:/workspace/mycpp/build# python
Python 3.8.19 (default, Mar 20 2024, 19:58:24)
[GCC 11.2.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.

import mycpp
Traceback (most recent call last):
File "", line 1, in
ModuleNotFoundError: No module named 'mycpp'

I see there is a problem?

@wenbowen123
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CMake Error: The current CMakeCache.txt directory /workspace/mycpp/build/CMakeCache.txt is different than the directory /home/ali/Downloads/FoundationPose/mycpp/build where CMakeCache.txt was created. This may result in binaries being created in the wrong place. If you are not sure, reedit the CMakeCache.txt

This is from your error log. It seems like you mixed the paths. I'd suggest mount your local /home/ali/Downloads/FoundationPose to docker and rebuild

@aghaphd
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aghaphd commented Apr 25, 2024

Thank you so much for the guidance, the problem above is solved and I will close the issue.

I faced another problem, will try to solve it:

(my) root@5f6626e587fd:/workspace# python run_demo.py
Warp 1.0.2 initialized:
CUDA Toolkit 11.5, Driver 11.4
Devices:
"cpu" : "x86_64"
"cuda:0" : "NVIDIA GeForce RTX 3070 Ti Laptop GPU" (8 GiB, sm_86, mempool enabled)
Kernel cache:
/root/.cache/warp/1.0.2
[init()] self.cfg:
lr: 0.0001
c_in: 6
zfar: 'Infinity'
debug: null
n_view: 1
run_id: 3wy8qqex
use_BN: true
exp_name: 2024-01-11-20-02-45
n_epochs: 62
save_dir: /home/ali/Downloads/FoundationPose/debug/2024-01-11-20-02-45/
use_mask: false
loss_type: pairwise_valid
optimizer: adam
batch_size: 64
crop_ratio: 1.1
enable_amp: true
use_normal: false
max_num_key: null
warmup_step: -1
input_resize:

  • 160
  • 160
    max_step_val: 1000
    vis_interval: 1000
    weight_decay: 0
    normalize_xyz: true
    resume_run_id: null
    clip_grad_norm: 'Infinity'
    lr_epoch_decay: 500
    render_backend: nvdiffrast
    train_num_pair: 5
    lr_decay_epochs:
  • 50
    n_epochs_warmup: 1
    make_pair_online: false
    gradient_max_norm: 'Infinity'
    max_step_per_epoch: 10000
    n_rendering_workers: 1
    save_epoch_interval: 100
    n_dataloader_workers: 100
    split_objects_across_gpus: true
    ckpt_dir: /workspace/learning/training/../../weights/2024-01-11-20-02-45/model_best.pth

[init()] self.h5_file:None
[init()] Using pretrained model from /workspace/learning/training/../../weights/2024-01-11-20-02-45/model_best.pth
[init()] init done
[init()] welcome
[init()] self.cfg:
lr: 0.0001
c_in: 6
zfar: .inf
debug: null
w_rot: 0.1
n_view: 1
run_id: null
use_BN: true
rot_rep: axis_angle
ckpt_dir: /workspace/learning/training/../../weights/2023-10-28-18-33-37/model_best.pth
exp_name: 2023-10-28-18-33-37
save_dir: /tmp/2023-10-28-18-33-37/
loss_type: l2
optimizer: adam
trans_rep: tracknet
batch_size: 64
crop_ratio: 1.2
use_normal: false
BN_momentum: 0.1
max_num_key: null
warmup_step: -1
input_resize:

  • 160
  • 160
    max_step_val: 1000
    normal_uint8: false
    vis_interval: 1000
    weight_decay: 0
    n_max_objects: null
    normalize_xyz: true
    clip_grad_norm: 'Infinity'
    rot_normalizer: 0.3490658503988659
    trans_normalizer:
  • 0.019999999552965164
  • 0.019999999552965164
  • 0.05000000074505806
    max_step_per_epoch: 25000
    val_epoch_interval: 10
    n_dataloader_workers: 60
    enable_amp: true
    use_mask: false

[init()] self.h5_file:
[init()] Using pretrained model from /workspace/learning/training/../../weights/2023-10-28-18-33-37/model_best.pth
[init()] init done
[reset_object()] self.diameter:0.19646325799497472, vox_size:0.009823162899748735
[reset_object()] self.pts:torch.Size([607, 3])
[reset_object()] reset done
[make_rotation_grid()] cam_in_obs:(42, 4, 4)
[make_rotation_grid()] rot_grid:(252, 4, 4)
num original candidates = 252
num of pose after clustering: 252
[make_rotation_grid()] after cluster, rot_grid:(252, 4, 4)
[make_rotation_grid()] self.rot_grid: torch.Size([252, 4, 4])
[()] estimator initialization done
[()] i:0
[register()] Welcome
Module Utils load on device 'cuda:0' took 5.82 ms
[register()] poses:(252, 4, 4)
[register()] after viewpoint, add_errs min:-1.0
[predict()] ob_in_cams:(252, 4, 4)
[predict()] self.cfg.use_normal:False
[predict()] trans_normalizer:[0.019999999552965164, 0.019999999552965164, 0.05000000074505806], rot_normalizer:0.3490658503988659
[predict()] making cropped data
[make_crop_data_batch()] Welcome make_crop_data_batch
[make_crop_data_batch()] make tf_to_crops done
[make_crop_data_batch()] render done
[make_crop_data_batch()] warp done
[make_crop_data_batch()] pose batch data done
[predict()] forward start
[predict()] forward done
[predict()] making cropped data
[make_crop_data_batch()] Welcome make_crop_data_batch
[make_crop_data_batch()] make tf_to_crops done
[make_crop_data_batch()] render done
[make_crop_data_batch()] warp done
[make_crop_data_batch()] pose batch data done
[predict()] forward start
[predict()] forward done
[predict()] making cropped data
[make_crop_data_batch()] Welcome make_crop_data_batch
[make_crop_data_batch()] make tf_to_crops done
[make_crop_data_batch()] render done
[make_crop_data_batch()] warp done
[make_crop_data_batch()] pose batch data done
[predict()] forward start
[predict()] forward done
[predict()] making cropped data
[make_crop_data_batch()] Welcome make_crop_data_batch
[make_crop_data_batch()] make tf_to_crops done
[make_crop_data_batch()] render done
[make_crop_data_batch()] warp done
[make_crop_data_batch()] pose batch data done
[predict()] forward start
[predict()] forward done
[predict()] making cropped data
[make_crop_data_batch()] Welcome make_crop_data_batch
[make_crop_data_batch()] make tf_to_crops done
[make_crop_data_batch()] render done
[make_crop_data_batch()] warp done
[make_crop_data_batch()] pose batch data done
[predict()] forward start
[predict()] forward done
[predict()] ob_in_cams:(252, 4, 4)
[predict()] self.cfg.use_normal:False
[predict()] making cropped data
[make_crop_data_batch()] Welcome make_crop_data_batch
[make_crop_data_batch()] make tf_to_crops done
[make_crop_data_batch()] render done
[make_crop_data_batch()] pose batch data done
[find_best_among_pairs()] pose_data.rgbAs.shape[0]: 252
[predict()] forward done
[register()] final, add_errs min:-1.0
[register()] sort ids:tensor([ 98, 0, 6, 7, 30, 31, 67, 72, 73, 102, 103, 127, 133, 168,
186, 199, 223, 241, 242, 1, 68, 97, 109, 169, 224, 96, 126, 145,
198, 132, 187, 228, 24, 25, 55, 78, 79, 84, 150, 229, 234, 12,
13, 18, 19, 85, 90, 91, 92, 112, 115, 120, 121, 151, 175, 176,
181, 182, 56, 108, 114, 236, 86, 74, 104, 235, 247, 54, 193, 111,
188, 205, 66, 26, 174, 80, 222, 14, 230, 163, 248, 194, 32, 69,
211, 144, 231, 245, 113, 170, 81, 204, 57, 110, 131, 106, 61, 192,
246, 196, 49, 178, 240, 171, 53, 149, 180, 123, 15, 48, 172, 39,
88, 94, 135, 155, 117, 191, 9, 45, 65, 87, 147, 52, 154, 221,
119, 202, 207, 214, 10, 58, 148, 166, 29, 161, 35, 64, 226, 16,
23, 208, 232, 251, 77, 105, 179, 70, 203, 250, 5, 60, 141, 125,
137, 183, 197, 158, 107, 165, 209, 243, 75, 129, 160, 244, 11, 59,
83, 215, 82, 184, 210, 20, 100, 218, 17, 27, 140, 177, 227, 34,
47, 136, 50, 62, 71, 122, 143, 212, 213, 2, 51, 76, 118, 124,
138, 220, 238, 239, 249, 4, 37, 63, 167, 195, 22, 41, 46, 99,
139, 40, 93, 130, 190, 201, 3, 21, 95, 142, 225, 219, 101, 153,
159, 164, 216, 44, 185, 116, 233, 162, 43, 200, 28, 134, 8, 89,
128, 152, 173, 38, 146, 189, 217, 33, 237, 156, 42, 157, 206, 36])
[register()] sorted scores:tensor([77.7969, 77.7812, 77.7812, 77.7812, 77.7812, 77.7812, 77.7812, 77.7812,
77.7812, 77.7812, 77.7812, 77.7812, 77.7812, 77.7812, 77.7812, 77.7812,
77.7812, 77.7812, 77.7812, 77.7656, 77.7656, 77.7656, 77.7656, 77.7656,
77.7656, 77.7500, 77.7500, 77.7500, 77.7500, 77.7344, 77.6562, 77.6250,
77.6094, 77.6094, 77.6094, 77.6094, 77.6094, 77.6094, 77.6094, 77.6094,
77.6094, 77.5938, 77.5938, 77.5938, 77.5938, 77.5938, 77.5938, 77.5938,
77.5938, 77.5938, 77.5938, 77.5938, 77.5938, 77.5938, 77.5938, 77.5938,
77.5938, 77.5938, 77.5781, 77.5781, 77.5781, 77.5625, 77.5469, 77.5312,
77.5312, 77.5312, 77.5312, 77.5156, 77.5156, 77.5000, 77.5000, 77.4844,
77.4688, 77.3281, 77.2812, 77.2656, 77.2656, 77.1719, 77.1719, 77.1562,
77.1562, 77.1094, 77.0938, 77.0938, 77.0938, 77.0625, 77.0625, 77.0625,
77.0469, 77.0469, 77.0156, 77.0156, 76.9844, 76.9844, 76.9531, 76.9219,
76.8906, 76.8750, 76.8750, 76.8594, 76.8438, 76.8438, 76.8438, 76.8125,
76.7969, 76.7969, 76.7969, 76.7500, 76.7188, 76.7188, 76.7188, 76.6875,
76.6562, 76.6562, 76.6562, 76.6406, 76.6094, 76.6094, 76.5938, 76.5781,
76.5625, 76.5625, 76.5625, 76.5469, 76.5469, 76.5469, 76.5312, 76.5312,
76.5312, 76.5312, 76.5156, 76.5156, 76.5156, 76.5156, 76.5000, 76.5000,
76.4844, 76.4844, 76.4844, 76.4688, 76.4688, 76.4688, 76.4688, 76.4688,
76.4531, 76.4531, 76.4531, 76.4375, 76.4375, 76.4375, 76.4219, 76.4219,
76.4219, 76.3906, 76.3906, 76.3906, 76.3906, 76.3750, 76.3594, 76.3594,
76.3594, 76.3594, 76.3438, 76.3438, 76.3125, 76.3125, 76.2969, 76.2969,
76.2969, 76.2969, 76.2812, 76.2812, 76.2812, 76.2656, 76.2656, 76.2656,
76.2500, 76.2500, 76.2500, 76.2500, 76.2500, 76.2344, 76.2344, 76.2344,
76.2188, 76.2188, 76.2188, 76.2188, 76.2188, 76.2188, 76.2188, 76.2031,
76.2031, 76.2031, 76.2031, 76.2031, 76.2031, 76.2031, 76.2031, 76.2031,
76.2031, 76.1875, 76.1875, 76.1875, 76.1875, 76.1875, 76.1719, 76.1719,
76.1719, 76.1719, 76.1719, 76.1562, 76.1562, 76.1562, 76.1562, 76.1406,
76.1250, 76.1250, 76.1250, 76.1250, 76.1250, 76.1094, 76.0938, 76.0938,
76.0938, 76.0938, 76.0938, 76.0781, 76.0781, 76.0625, 76.0625, 76.0469,
76.0312, 76.0312, 76.0156, 76.0156, 76.0000, 76.0000, 75.9844, 75.9844,
75.9844, 75.9688, 75.9219, 75.9219, 75.9219, 75.9062, 75.9062, 75.8906,
75.8594, 75.8594, 75.8594, 75.8125])
qt.qpa.xcb: could not connect to display
qt.qpa.plugin: Could not load the Qt platform plugin "xcb" in "/opt/conda/envs/my/lib/python3.8/site-packages/cv2/qt/plugins" even though it was found.
This application failed to start because no Qt platform plugin could be initialized. Reinstalling the application may fix this problem.

Available platform plugins are: xcb.

Aborted (core dumped)

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