jiangwenpl / multiperson Goto Github PK
View Code? Open in Web Editor NEWCode repository for the paper: "Coherent Reconstruction of Multiple Humans from a Single Image" in CVPR'20
Home Page: https://jiangwenpl.github.io/multiperson/
Code repository for the paper: "Coherent Reconstruction of Multiple Humans from a Single Image" in CVPR'20
Home Page: https://jiangwenpl.github.io/multiperson/
Error pre-processing data
python h36m.py /datasets/Human36M/ ../../../mmdetection/data/h36m/rcnn --split=train
Traceback (most recent call last):
File "h36m.py", line 135, in <module>
h36m_extract(args.dataset_path, args.out_path, split=args.split)
File "h36m.py", line 131, in h36m_extract
pickle.dump(data, f)
NameError: name 'data' is not defined
All the downloading linke of pretrained model seems dead. Could you update them for us to make tests?
Hi,
Thanks a ton for the great work!
I am trying out the script to fit SMPL-X to 3D keypoints and are noticing a speed of about 40 secs per frame; This is rather slow even with parallelzation. Any suggestions?
hi,when i run python3 tools/full_eval.py configs/smpl/tune.py haggling --ckpt ./work_dirs/tune/latest.pth to evaluation Panoptic, there is something wrong,
2022-03-05 16:17:40,458 - WARNING - unexpected key in source state_dict: fc.weight, fc.bias
missing keys in source state_dict: layer3.4.bn3.num_batches_tracked, layer3.5.bn3.num_batches_tracked, layer4.0.downsample.1.num_batches_tracked, layer1.0.downsample.1.num_batches_tracked, layer1.2.bn1.num_batches_tracked, layer2.2.bn2.num_batches_tracked, layer1.1.bn2.num_batches_tracked, layer2.3.bn1.num_batches_tracked, layer4.2.bn2.num_batches_tracked, layer3.5.bn1.num_batches_tracked, layer1.2.bn2.num_batches_tracked, layer3.5.bn2.num_batches_tracked, layer3.0.downsample.1.num_batches_tracked, layer3.2.bn2.num_batches_tracked, layer1.0.bn2.num_batches_tracked, layer2.1.bn1.num_batches_tracked, layer3.3.bn1.num_batches_tracked, layer4.2.bn3.num_batches_tracked, layer3.1.bn3.num_batches_tracked, layer3.3.bn3.num_batches_tracked, layer4.1.bn2.num_batches_tracked, layer2.3.bn3.num_batches_tracked, layer3.2.bn1.num_batches_tracked, layer4.2.bn1.num_batches_tracked, layer2.2.bn1.num_batches_tracked, layer3.0.bn2.num_batches_tracked, layer4.0.bn3.num_batches_tracked, layer2.2.bn3.num_batches_tracked, layer2.0.bn1.num_batches_tracked, layer2.3.bn2.num_batches_tracked, layer1.0.bn1.num_batches_tracked, layer2.1.bn2.num_batches_tracked, layer2.0.downsample.1.num_batches_tracked, layer3.3.bn2.num_batches_tracked, layer3.1.bn2.num_batches_tracked, layer3.0.bn1.num_batches_tracked, layer3.4.bn1.num_batches_tracked, layer4.1.bn3.num_batches_tracked, layer4.0.bn1.num_batches_tracked, layer2.0.bn3.num_batches_tracked, layer3.1.bn1.num_batches_tracked, layer1.1.bn3.num_batches_tracked, layer3.2.bn3.num_batches_tracked, layer1.0.bn3.num_batches_tracked, layer3.4.bn2.num_batches_tracked, layer2.0.bn2.num_batches_tracked, layer2.1.bn3.num_batches_tracked, layer4.0.bn2.num_batches_tracked, layer1.1.bn1.num_batches_tracked, layer4.1.bn1.num_batches_tracked, layer1.2.bn3.num_batches_tracked, layer3.0.bn3.num_batches_tracked, bn1.num_batches_tracked
Traceback (most recent call last):
File "tools/full_eval.py", line 297, in
main()
File "tools/full_eval.py", line 222, in main
train_dataset = get_dataset(cfg.datasets[0].train)
File "/home/cuihuili/coherent_reconstruction/multiperson-master/mmdetection/mmdet/datasets/utils.py", line 111, in get_dataset
dset = obj_from_dict(data_info, datasets)
File "/home/cuihuili/miniconda3/envs/multiperson1/lib/python3.7/site-packages/mmcv-0.2.10-py3.7-linux-x86_64.egg/mmcv/runner/utils.py", line 81, in obj_from_dict
return obj_type(**args)
File "/home/cuihuili/coherent_reconstruction/multiperson-master/mmdetection/mmdet/datasets/h36m.py", line 107, in init
self.img_infos = self.load_annotations(ann_file)
File "/home/cuihuili/coherent_reconstruction/multiperson-master/mmdetection/mmdet/datasets/h36m.py", line 239, in load_annotations
with open(ann_file, 'rb') as f:
FileNotFoundError: [Errno 2] No such file or directory: 'data/h36m/extras/rcnn/h36m_train.pkl'
Q1,why missing keys in source state_dict?
Q2,when evaluation Panoptic, also need h36m dataset?
Hi, thanks for sharing the great work and code!
Could you please provide the detailed structure of the ann_file and proposal_file or provide an example file for better understanding the code? Also, when exactly will you release the data preprocessing code?
Thank you and look fwd to your reply!
Hi,
thank you for your work!
We have installed your program in the past but now we verified the cuda version along with the cudnn is no longer available. For example we have the following error when creating the environment:
ResolvePackageNotFound:
do you have any solution for this? do you have a new version of the environment with more recent versions of cuda?
Hi,
I ran the demo but got the assertion indicating that the data/smpl/SMPL_NEUTRAL.pkl
does not exist. Then I noticed the fetch data section indicates that the 'neutral model' (http://smplify.is.tue.mpg.de/) is needed for training, evaluation, and running the demo code. That website contains multiple files, Could you please confirm if that model is the one located on lsp_results.targ.gz (obtained from http://smplify.is.tue.mpg.de/) > results > lsp > all_results_gender-neutral.pkl? If so, I would have to rename all_results_gender-neutral.pkl
as SMPL_NEUTRAL.pkl
. After renaming the pkl, the code returned the error below, which makes me think I got the wrong pkl:
File "/multiperson/mmdetection/mmdet/models/utils/smpl/smpl.py", line 51, in __init__
super(SMPL, self).__init__(*args, create_global_orient=False, create_body_pose=False, create_betas=False, create_transl=False, **kwargs)
File "/python3.6/site-packages/smplx/body_models.py", line 205, in __init__
self.faces = data_struct.f
AttributeError: 'Struct' object has no attribute 'f'
Cheers,
Gabriel
I was wondering, why do you need to flip the x- axis in .../utils/smpl/renderer.py
?
# Need to flip x-axis
rot = trimesh.transformations.rotation_matrix(
np.radians(180), [1, 0, 0])
Also, what are the gains provided by using the full perspective camera model vs. weak perspective for 2D supervision?
Hello,
I am trying to run the demo file on the teaser image. I followed the instructions of #4 because I had the same error as #1. I am a bit confused about the downloads. Particularly:
WARNING: You are using a SMPL model, with only 10 shape coefficients.
WARNING: You are using a SMPL model, with only 10 shape coefficients.
unexpected key in source state_dict: fc.weight, fc.bias
missing keys in source state_dict: layer2.0.bn1.num_batches_tracked, layer2.1.bn3.num_batches_tracked, layer3.5.bn1.num_batches_tracked, layer2.3.bn3.num_batches_tracked, layer3.0.bn3.num_batches_tracked, layer3.4.bn2.num_batches_tracked, layer1.0.bn1.num_batches_tracked, layer4.1.bn2.num_batches_tracked, layer3.2.bn3.num_batches_tracked, layer4.0.bn3.num_batches_tracked, layer3.0.bn1.num_batches_tracked, layer1.1.bn3.num_batches_tracked, layer2.3.bn2.num_batches_tracked, layer1.2.bn1.num_batches_tracked, layer2.0.bn2.num_batches_tracked, layer1.2.bn2.num_batches_tracked, layer3.3.bn3.num_batches_tracked, layer2.2.bn3.num_batches_tracked, layer1.0.bn2.num_batches_tracked, layer1.0.downsample.1.num_batches_tracked, layer4.1.bn3.num_batches_tracked, layer3.1.bn3.num_batches_tracked, layer4.2.bn1.num_batches_tracked, layer3.3.bn2.num_batches_tracked, layer2.1.bn2.num_batches_tracked, layer3.2.bn2.num_batches_tracked, layer3.3.bn1.num_batches_tracked, layer4.1.bn1.num_batches_tracked, layer3.4.bn3.num_batches_tracked, layer4.2.bn2.num_batches_tracked, layer3.0.downsample.1.num_batches_tracked, layer3.5.bn3.num_batches_tracked, layer4.0.downsample.1.num_batches_tracked, layer3.2.bn1.num_batches_tracked, layer2.3.bn1.num_batches_tracked, layer1.1.bn1.num_batches_tracked, layer4.0.bn2.num_batches_tracked, layer4.2.bn3.num_batches_tracked, layer2.2.bn1.num_batches_tracked, layer3.1.bn2.num_batches_tracked, layer4.0.bn1.num_batches_tracked, layer2.0.bn3.num_batches_tracked, layer1.2.bn3.num_batches_tracked, layer3.0.bn2.num_batches_tracked, layer2.0.downsample.1.num_batches_tracked, layer2.1.bn1.num_batches_tracked, layer3.1.bn1.num_batches_tracked, layer1.0.bn3.num_batches_tracked, layer3.5.bn2.num_batches_tracked, bn1.num_batches_tracked, layer2.2.bn2.num_batches_tracked, layer3.4.bn1.num_batches_tracked, layer1.1.bn2.num_batches_tracked
2021-08-12 16:47:52,049 - INFO - load checkpoint from data/checkpoint.pt
2021-08-12 16:47:52,503 - WARNING - missing keys in source state_dict: smpl_head.loss.smpl.faces_tensor, smpl_head.loss.smpl.shapedirs, smpl_head.smpl.shapedirs, smpl_head.loss.smpl.vertex_joint_selector.extra_joints_idxs, smpl_head.smpl.posedirs, smpl_head.loss.smpl.J_regressor, smpl_head.smpl.v_template, smpl_head.smpl.faces_tensor, smpl_head.loss.smpl.v_template, smpl_head.smpl.J_regressor, smpl_head.loss.smpl.lbs_weights, smpl_head.smpl.lbs_weights, smpl_head.smpl.vertex_joint_selector.extra_joints_idxs, smpl_head.smpl.J_regressor_extra, smpl_head.smpl.parents, smpl_head.loss.smpl.J_regressor_extra, smpl_head.loss.smpl.parents, smpl_head.loss.smpl.posedirs
2021-08-12 16:47:52,535 - INFO - resumed epoch 27, iter 90901
WARNING: You are using a SMPL model, with only 10 shape coefficients.
Traceback (most recent call last):
File "/home/multiperson/mmdetection/tools/demo.py", line 190, in
main()
File "/home/multiperson/mmdetection/tools/demo.py", line 186, in main
cv2.imwrite(f'{file_name.replace(folder_name, output_folder)}.output.jpg', img_viz[:, :, ::-1])
TypeError: 'NoneType' object is not subscriptable
startswith first arg must be bytes or a tuple of bytes, not str
I commented the try-except part (demo.py line 89-94) to get a more detailed error message. The problem seems to occur in renderer.py line 88:
Traceback (most recent call last):
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/OpenGL/latebind.py", line 41, in call
return self._finalCall( *args, **named )
TypeError: 'NoneType' object is not callable
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/nora/multiperson/mmdetection/tools/demo.py", line 185, in main
img_viz = prepare_dump(pred_results, img, render, bbox_results, FOCAL_LENGTH)
File "/home/nora/multiperson/mmdetection/tools/demo.py", line 90, in prepare_dump
fv_rendered = render([img_th.clone()], [pred_verts], translation=[pred_trans])[0]
File "/home/nora/multiperson/mmdetection/mmdet/models/utils/smpl/renderer.py", line 88, in call
color, rend_depth = self.renderer.render(scene, flags=pyrender.RenderFlags.RGBA)
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/pyrender/offscreen.py", line 99, in render
return self._renderer.render(scene, flags)
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/pyrender/renderer.py", line 121, in render
self._update_context(scene, flags)
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/pyrender/renderer.py", line 709, in _update_context
p._add_to_context()
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/pyrender/primitive.py", line 324, in _add_to_context
self._vaid = glGenVertexArrays(1)
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/OpenGL/latebind.py", line 45, in call
return self._finalCall( *args, **named )
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/OpenGL/wrapper.py", line 657, in wrapperCall
result = wrappedOperation( *cArguments )
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/OpenGL/platform/baseplatform.py", line 401, in call
if self.load():
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/OpenGL/platform/baseplatform.py", line 390, in load
error_checker = self.error_checker,
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/OpenGL/platform/baseplatform.py", line 148, in constructFunction
if (not is_core) and not self.checkExtension( extension ):
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/OpenGL/platform/baseplatform.py", line 270, in checkExtension
result = extensions.ExtensionQuerier.hasExtension( name )
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/OpenGL/extensions.py", line 98, in hasExtension
result = registered( specifier )
File "/home/nora/anaconda2/envs/multiperson/lib/python3.7/site-packages/OpenGL/extensions.py", line 105, in call
if not specifier.startswith( self.prefix ):
TypeError: startswith first arg must be bytes or a tuple of bytes, not str
Hi, thanks for wonderful project!
Currently, I have carried out the project with the SMPL(SMPL_NEUTRAL.pkl) model, and I plan to proceed with the SMPLX(SMPLX_NEUTRAL) model. An error occurs when using the model SMPLX. Is there a way to use the model?
unexpected key in source state_dict: fc.weight, fc.bias
missing keys in source state_dict: layer2.2.bn2.num_batches_tracked, layer3.4.bn2.num_batches_tracked, layer3.3.bn1.num_batches_tracked, layer4.0.bn3.num_batches_tracked, layer4.1.bn2.num_batches_tracked, layer1.1.bn2.num_batches_tracked, layer1.2.bn2.num_batches_tracked, layer2.1.bn1.num_batches_tracked, layer1.2.bn3.num_batches_tracked, layer4.0.downsample.1.num_batches_tracked, layer3.1.bn2.num_batches_tracked, layer3.4.bn3.num_batches_tracked, layer1.0.bn1.num_batches_tracked, layer3.3.bn3.num_batches_tracked, layer4.2.bn3.num_batches_tracked, layer1.1.bn1.num_batches_tracked, bn1.num_batches_tracked, layer2.1.bn2.num_batches_tracked, layer3.2.bn1.num_batches_tracked, layer3.0.bn3.num_batches_tracked, layer2.2.bn3.num_batches_tracked, layer3.5.bn3.num_batches_tracked, layer2.0.bn3.num_batches_tracked, layer4.0.bn2.num_batches_tracked, layer2.3.bn1.num_batches_tracked, layer3.1.bn1.num_batches_tracked, layer2.1.bn3.num_batches_tracked, layer1.0.downsample.1.num_batches_tracked, layer4.2.bn2.num_batches_tracked, layer3.5.bn1.num_batches_tracked, layer1.0.bn2.num_batches_tracked, layer4.1.bn3.num_batches_tracked, layer3.0.downsample.1.num_batches_tracked, layer4.0.bn1.num_batches_tracked, layer3.4.bn1.num_batches_tracked, layer2.3.bn3.num_batches_tracked, layer2.0.downsample.1.num_batches_tracked, layer2.0.bn2.num_batches_tracked, layer1.0.bn3.num_batches_tracked, layer3.2.bn3.num_batches_tracked, layer3.0.bn1.num_batches_tracked, layer3.3.bn2.num_batches_tracked, layer2.2.bn1.num_batches_tracked, layer4.1.bn1.num_batches_tracked, layer3.5.bn2.num_batches_tracked, layer2.0.bn1.num_batches_tracked, layer2.3.bn2.num_batches_tracked, layer3.0.bn2.num_batches_tracked, layer1.1.bn3.num_batches_tracked, layer4.2.bn1.num_batches_tracked, layer3.1.bn3.num_batches_tracked, layer1.2.bn1.num_batches_tracked, layer3.2.bn2.num_batches_tracked
2021-08-12 18:09:38,964 - INFO - load checkpoint from data/checkpoint.pt
Traceback (most recent call last):
File "/home/neosungsin/anaconda3/envs/multi/lib/python3.7/site-packages/mmcv-0.2.10-py3.7-linux-x86_64.egg/mmcv/runner/checkpoint.py", line 87, in load_state_dict
own_state[name].copy_(param)
RuntimeError: The size of tensor a (20908) must match the size of tensor b (13776) at non-singleton dimension 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "tools/demo.py", line 190, in <module>
main()
File "tools/demo.py", line 149, in main
runner.resume(cfg.resume_from)
File "/home/neosungsin/anaconda3/envs/multi/lib/python3.7/site-packages/mmcv-0.2.10-py3.7-linux-x86_64.egg/mmcv/runner/runner.py", line 330, in resume
map_location=lambda storage, loc: storage.cuda(device_id))
File "/home/neosungsin/anaconda3/envs/multi/lib/python3.7/site-packages/mmcv-0.2.10-py3.7-linux-x86_64.egg/mmcv/runner/runner.py", line 239, in load_checkpoint
self.logger)
File "/home/neosungsin/anaconda3/envs/multi/lib/python3.7/site-packages/mmcv-0.2.10-py3.7-linux-x86_64.egg/mmcv/runner/checkpoint.py", line 180, in load_checkpoint
load_state_dict(model.module, state_dict, strict, logger)
File "/home/neosungsin/anaconda3/envs/multi/lib/python3.7/site-packages/mmcv-0.2.10-py3.7-linux-x86_64.egg/mmcv/runner/checkpoint.py", line 93, in load_state_dict
name, own_state[name].size(), param.size()))
RuntimeError: While copying the parameter named smpl_head.loss.sdf_loss.faces, whose dimensions in the model are torch.Size([20908, 3]) and whose dimensions in the checkpoint are torch.Size([13776, 3]).
Also, if the SMPL model is used, the above error occurs, but the output result is generated.
unexpected key in source state_dict: fc.weight, fc.bias
missing keys in source state_dict: layer3.2.bn2.num_batches_tracked, layer1.0.bn3.num_batches_tracked, layer3.4.bn3.num_batches_tracked, layer3.0.downsample.1.num_batches_tracked, layer3.5.bn3.num_batches_tracked, layer3.0.bn1.num_batches_tracked, layer3.2.bn3.num_batches_tracked, layer3.4.bn2.num_batches_tracked, layer3.1.bn2.num_batches_tracked, layer2.3.bn1.num_batches_tracked, layer3.3.bn3.num_batches_tracked, layer2.2.bn1.num_batches_tracked, layer3.5.bn2.num_batches_tracked, layer2.1.bn3.num_batches_tracked, layer3.4.bn1.num_batches_tracked, layer4.0.bn1.num_batches_tracked, bn1.num_batches_tracked, layer3.3.bn1.num_batches_tracked, layer2.1.bn1.num_batches_tracked, layer1.1.bn3.num_batches_tracked, layer4.2.bn2.num_batches_tracked, layer4.2.bn3.num_batches_tracked, layer3.2.bn1.num_batches_tracked, layer1.1.bn1.num_batches_tracked, layer3.3.bn2.num_batches_tracked, layer2.3.bn2.num_batches_tracked, layer2.3.bn3.num_batches_tracked, layer2.2.bn2.num_batches_tracked, layer4.1.bn3.num_batches_tracked, layer4.0.bn2.num_batches_tracked, layer4.2.bn1.num_batches_tracked, layer2.0.bn2.num_batches_tracked, layer4.1.bn2.num_batches_tracked, layer3.0.bn2.num_batches_tracked, layer2.1.bn2.num_batches_tracked, layer2.0.bn3.num_batches_tracked, layer2.0.bn1.num_batches_tracked, layer4.1.bn1.num_batches_tracked, layer4.0.downsample.1.num_batches_tracked, layer3.0.bn3.num_batches_tracked, layer1.0.downsample.1.num_batches_tracked, layer1.2.bn3.num_batches_tracked, layer1.2.bn2.num_batches_tracked, layer1.0.bn2.num_batches_tracked, layer2.0.downsample.1.num_batches_tracked, layer3.1.bn1.num_batches_tracked, layer1.2.bn1.num_batches_tracked, layer2.2.bn3.num_batches_tracked, layer1.1.bn2.num_batches_tracked, layer1.0.bn1.num_batches_tracked, layer3.1.bn3.num_batches_tracked, layer4.0.bn3.num_batches_tracked, layer3.5.bn1.num_batches_tracked
2021-08-12 17:54:32,318 - INFO - load checkpoint from data/checkpoint.pt
2021-08-12 17:54:32,574 - WARNING - missing keys in source state_dict: smpl_head.loss.smpl.shapedirs, smpl_head.loss.smpl.vertex_joint_selector.extra_joints_idxs, smpl_head.loss.smpl.parents, smpl_head.smpl.lbs_weights, smpl_head.smpl.faces_tensor, smpl_head.loss.smpl.faces_tensor, smpl_head.smpl.shapedirs, smpl_head.smpl.parents, smpl_head.smpl.J_regressor_extra, smpl_head.smpl.J_regressor, smpl_head.smpl.v_template, smpl_head.loss.smpl.posedirs, smpl_head.smpl.posedirs, smpl_head.loss.smpl.J_regressor_extra, smpl_head.loss.smpl.v_template, smpl_head.smpl.vertex_joint_selector.extra_joints_idxs, smpl_head.loss.smpl.J_regressor, smpl_head.loss.smpl.lbs_weights
2021-08-12 17:54:32,593 - INFO - resumed epoch 27, iter 90901
/home/multi/mmdetection/mmdet/core/bbox/transforms.py:56: UserWarning: This overload of addcmul is deprecated:
addcmul(Tensor input, Number value, Tensor tensor1, Tensor tensor2, *, Tensor out)
Consider using one of the following signatures instead:
addcmul(Tensor input, Tensor tensor1, Tensor tensor2, *, Number value, Tensor out) (Triggered internally at /pytorch/torch/csrc/utils/python_arg_parser.cpp:882.)
gx = torch.addcmul(px, 1, pw, dx) # gx = px + pw * dx
Hi, I am trying to use your SDF loss function implementation for my project. I am facing an issue described below
#CODE SNIPPET
import sdf
sdf_loss = sdf.sdf_loss.SDFLoss(np.array(human_parameters['faces'].detach().cpu()))
translations = torch.ones((num_people,3), device = 'cuda:0')
vertices = params['pred_vertices']
sdf_loss(vertices,translations)
There are people in the image and I have generated the vertices and faces of those people. I want to calculate the sdf loss function value when all have identical translations ( that is same tx, ty, and tz) and this loss is coming out to be zero I don't understand why because if all the people have the same translation values there is overlap and that implies there are collisions but why is the sdf loss value zero?
Thank you!
Hi could you please either share the teapot.obj or the link to download to reproduce example1.py?
mona@goku:~/research/code/multiperson/neural_renderer$ python ./examples/example1.py
Traceback (most recent call last):
File "./examples/example1.py", line 55, in <module>
main()
File "./examples/example1.py", line 31, in main
vertices, faces = nr.load_obj(args.filename_input)
File "/home/mona/venv/nmr/lib/python3.8/site-packages/neural_renderer/load_obj.py", line 117, in load_obj
with open(filename_obj) as f:
FileNotFoundError: [Errno 2] No such file or directory: '/home/mona/research/code/multiperson/neural_renderer/examples/data/teapot.obj'
Could you give a brief explanation about L171 to L176? It's an approximation that depth d = 2 * focal_length / (s * max(box_w, box_h)), right? Because generally small person means larger depth.
Hi,
How can I get the percentage of correctly estimated ordinal depth relations in Table 5
Is it reasonable for the losses to oscillate?
Hi, thank you for sharing this great work. It seems that the "tools" folder is missing in this repository. Could you please reupload these files?
hello, I use panoptic.py to get test dataset, But I get an error bellow. I don't kown what the cmu keypoints the code have used.
Connected to pydev debugger (build 201.8743.11)
0%| | 0/1200 [00:00<?, ?it/s]Traceback (most recent call last):
File "/home/icvhpc1/.pycharm_helpers/pydev/pydevd.py", line 1438, in _exec
pydev_imports.execfile(file, globals, locals) # execute the script
File "/home/icvhpc1/.pycharm_helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile
exec(compile(contents+"\n", file, 'exec'), glob, loc)
File "/home/icvhpc1/bluce/code/mhmr-v1.1/experiments/release_version/multiperson/misc/preprocess_datasets/full/panoptic.py", line 166, in
process_panoptic(args.panoptic_path, args.dataset_name, args.sequence_idx)
File "/home/icvhpc1/bluce/code/mhmr-v1.1/experiments/release_version/multiperson/misc/preprocess_datasets/full/panoptic.py", line 120, in process_panoptic
kpts3d_J24[J24_to_J15] = skel.T
ValueError: shape mismatch: value array of shape (19,4) could not be broadcast to indexing result of shape (15,4)
Hi, thanks for sharing your code. I run the demo
python3 tools/demo.py --config=configs/smpl/tune.py --image_folder=demo_images/ --output_folder=results/ --ckpt data/checkpoint.pt
However, I get this info:
unexpected key in source state_dict: fc.weight, fc.bias
missing keys in source state_dict: layer2.1.bn3.num_batches_tracked, layer3.2.bn2.num_batches_tracked, layer2.2.bn2.num_batches_tracked, layer1.0.bn1.num_batches_tracked, layer4.1.bn3.num_batches_tracked, layer1.2.bn2.num_batches_tracked, layer4.0.bn1.num_batches_tracked, layer1.1.bn1.num_batches_tracked, layer1.2.bn1.num_batches_tracked, layer1.1.bn3.num_batches_tracked, layer4.2.bn3.num_batches_tracked, layer4.1.bn2.num_batches_tracked, layer4.0.bn3.num_batches_tracked, layer2.3.bn1.num_batches_tracked, layer3.5.bn3.num_batches_tracked, layer3.3.bn2.num_batches_tracked, layer4.0.downsample.1.num_batches_tracked, layer4.2.bn2.num_batches_tracked, layer2.0.bn1.num_batches_tracked, layer3.4.bn1.num_batches_tracked, layer3.1.bn3.num_batches_tracked, layer3.2.bn1.num_batches_tracked, layer3.3.bn1.num_batches_tracked, layer2.3.bn2.num_batches_tracked, layer3.5.bn2.num_batches_tracked, layer4.2.bn1.num_batches_tracked, layer3.1.bn1.num_batches_tracked, layer1.2.bn3.num_batches_tracked, layer4.1.bn1.num_batches_tracked, layer3.0.bn1.num_batches_tracked, layer2.0.bn3.num_batches_tracked, layer2.1.bn1.num_batches_tracked, layer2.0.bn2.num_batches_tracked, layer2.3.bn3.num_batches_tracked, layer1.0.bn3.num_batches_tracked, layer3.0.downsample.1.num_batches_tracked, layer3.0.bn2.num_batches_tracked, layer3.2.bn3.num_batches_tracked, layer3.4.bn2.num_batches_tracked, layer2.2.bn1.num_batches_tracked, layer3.0.bn3.num_batches_tracked, layer1.0.bn2.num_batches_tracked, layer3.5.bn1.num_batches_tracked, layer1.0.downsample.1.num_batches_tracked, layer2.2.bn3.num_batches_tracked, layer3.1.bn2.num_batches_tracked, layer4.0.bn2.num_batches_tracked, layer2.0.downsample.1.num_batches_tracked, layer3.3.bn3.num_batches_tracked, layer1.1.bn2.num_batches_tracked, bn1.num_batches_tracked, layer2.1.bn2.num_batches_tracked, layer3.4.bn3.num_batches_tracked
2022-08-19 12:51:02,959 - INFO - load checkpoint from data/checkpoint.pt
2022-08-19 12:51:03,424 - WARNING - missing keys in source state_dict: smpl_head.loss.smpl.J_regressor_extra, smpl_head.smpl.v_template, smpl_head.loss.smpl.faces_tensor, smpl_head.loss.smpl.posedirs, smpl_head.smpl.J_regressor_extra, smpl_head.smpl.parents, smpl_head.loss.smpl.lbs_weights, smpl_head.loss.smpl.parents, smpl_head.smpl.shapedirs, smpl_head.smpl.vertex_joint_selector.extra_joints_idxs, smpl_head.smpl.faces_tensor, smpl_head.smpl.posedirs, smpl_head.smpl.lbs_weights, smpl_head.smpl.J_regressor, smpl_head.loss.smpl.vertex_joint_selector.extra_joints_idxs, smpl_head.loss.smpl.v_template, smpl_head.loss.smpl.shapedirs, smpl_head.loss.smpl.J_regressor
2022-08-19 12:51:03,450 - INFO - resumed epoch 27, iter 90901
I suppose there are many missing keys so the demo will fail. However, I got a reasonable result.
I tried as #1 . But I still get the same info.
I am trying to install multiperson repo for PyTorch 1.6 and I get the following error. How can I make it work for PyTorch 1.6?
(base) mona@mona:~/research$ cd phosa/
(base) mona@mona:~/research/phosa$ mkdir -p external
(base) mona@mona:~/research/phosa$ git clone https://github.com/JiangWenPL/multiperson.git external/multiperson
Cloning into 'external/multiperson'...
remote: Enumerating objects: 752, done.
remote: Counting objects: 100% (752/752), done.
remote: Compressing objects: 100% (566/566), done.
remote: Total 752 (delta 189), reused 723 (delta 173), pack-reused 0
Receiving objects: 100% (752/752), 48.29 MiB | 46.26 MiB/s, done.
Resolving deltas: 100% (189/189), done.
(base) mona@mona:~/research/phosa$ pip install external/multiperson/neural_renderer
Processing ./external/multiperson/neural_renderer
Building wheels for collected packages: neural-renderer-pytorch
Building wheel for neural-renderer-pytorch (setup.py) ... error
ERROR: Command errored out with exit status 1:
command: /home/mona/anaconda3/bin/python3.7 -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-req-build-ma51z6r7/setup.py'"'"'; __file__='"'"'/tmp/pip-req-build-ma51z6r7/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' bdist_wheel -d /tmp/pip-wheel-nl9m5bw0
cwd: /tmp/pip-req-build-ma51z6r7/
Complete output (210 lines):
running bdist_wheel
running build
running build_py
creating build
creating build/lib.linux-x86_64-3.7
creating build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/load_obj.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/perspective.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/vertices_to_faces.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/visibility.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/get_points_from_angles.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/look.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/projection.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/rasterize.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/save_obj.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/look_at.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/__init__.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/lighting.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/mesh.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/renderer.py -> build/lib.linux-x86_64-3.7/neural_renderer
creating build/lib.linux-x86_64-3.7/neural_renderer/cuda
copying neural_renderer/cuda/__init__.py -> build/lib.linux-x86_64-3.7/neural_renderer/cuda
running build_ext
building 'neural_renderer.cuda.load_textures' extension
creating /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7
creating /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer
creating /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda
Emitting ninja build file /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/build.ninja...
Compiling objects...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
[1/2] /usr/bin/nvcc -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/TH -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/THC -I/home/mona/anaconda3/include/python3.7m -c -c /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda_kernel.cu -o /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda/load_textures_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=load_textures -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14
[2/2] c++ -MMD -MF /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda/load_textures_cuda.o.d -pthread -B /home/mona/anaconda3/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/TH -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/THC -I/home/mona/anaconda3/include/python3.7m -c -c /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp -o /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda/load_textures_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=load_textures -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
FAILED: /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda/load_textures_cuda.o
c++ -MMD -MF /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda/load_textures_cuda.o.d -pthread -B /home/mona/anaconda3/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/TH -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/THC -I/home/mona/anaconda3/include/python3.7m -c -c /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp -o /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda/load_textures_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=load_textures -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
In file included from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Parallel.h:149,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/utils.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:5,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/nn.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:1:
/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/ParallelOpenMP.h:84: warning: ignoring #pragma omp parallel [-Wunknown-pragmas]
84 | #pragma omp parallel for if ((end - begin) >= grain_size)
|
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp: In function ‘at::Tensor load_textures(at::Tensor, at::Tensor, at::Tensor, at::Tensor, int, int)’:
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:15:39: warning: ‘at::DeprecatedTypeProperties& at::Tensor::type() const’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [-Wdeprecated-declarations]
15 | #define CHECK_CUDA(x) AT_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:17:24: note: in expansion of macro ‘CHECK_CUDA’
17 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:28:5: note: in expansion of macro ‘CHECK_INPUT’
28 | CHECK_INPUT(image);
| ^~~~~~~~~~~
In file included from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Tensor.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Context.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:5,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:1:
/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/core/TensorBody.h:268:30: note: declared here
268 | DeprecatedTypeProperties & type() const {
| ^~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:15:23: error: ‘AT_CHECK’ was not declared in this scope; did you mean ‘DCHECK’?
15 | #define CHECK_CUDA(x) AT_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:17:24: note: in expansion of macro ‘CHECK_CUDA’
17 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:28:5: note: in expansion of macro ‘CHECK_INPUT’
28 | CHECK_INPUT(image);
| ^~~~~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:15:39: warning: ‘at::DeprecatedTypeProperties& at::Tensor::type() const’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [-Wdeprecated-declarations]
15 | #define CHECK_CUDA(x) AT_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:17:24: note: in expansion of macro ‘CHECK_CUDA’
17 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:29:5: note: in expansion of macro ‘CHECK_INPUT’
29 | CHECK_INPUT(faces);
| ^~~~~~~~~~~
In file included from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Tensor.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Context.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:5,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:1:
/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/core/TensorBody.h:268:30: note: declared here
268 | DeprecatedTypeProperties & type() const {
| ^~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:15:39: warning: ‘at::DeprecatedTypeProperties& at::Tensor::type() const’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [-Wdeprecated-declarations]
15 | #define CHECK_CUDA(x) AT_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:17:24: note: in expansion of macro ‘CHECK_CUDA’
17 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:30:5: note: in expansion of macro ‘CHECK_INPUT’
30 | CHECK_INPUT(is_update);
| ^~~~~~~~~~~
In file included from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Tensor.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Context.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:5,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:1:
/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/core/TensorBody.h:268:30: note: declared here
268 | DeprecatedTypeProperties & type() const {
| ^~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:15:39: warning: ‘at::DeprecatedTypeProperties& at::Tensor::type() const’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [-Wdeprecated-declarations]
15 | #define CHECK_CUDA(x) AT_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:17:24: note: in expansion of macro ‘CHECK_CUDA’
17 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:31:5: note: in expansion of macro ‘CHECK_INPUT’
31 | CHECK_INPUT(textures);
| ^~~~~~~~~~~
In file included from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Tensor.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Context.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:5,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:1:
/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/core/TensorBody.h:268:30: note: declared here
268 | DeprecatedTypeProperties & type() const {
| ^~~~
ninja: build stopped: subcommand failed.
Traceback (most recent call last):
File "/home/mona/anaconda3/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1515, in _run_ninja_build
env=env)
File "/home/mona/anaconda3/lib/python3.7/subprocess.py", line 512, in run
output=stdout, stderr=stderr)
subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 1.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/tmp/pip-req-build-ma51z6r7/setup.py", line 40, in <module>
cmdclass = {'build_ext': BuildExtension}
File "/home/mona/anaconda3/lib/python3.7/site-packages/setuptools/__init__.py", line 163, in setup
return distutils.core.setup(**attrs)
File "/home/mona/anaconda3/lib/python3.7/distutils/core.py", line 148, in setup
dist.run_commands()
File "/home/mona/anaconda3/lib/python3.7/distutils/dist.py", line 966, in run_commands
self.run_command(cmd)
File "/home/mona/anaconda3/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "/home/mona/anaconda3/lib/python3.7/site-packages/wheel/bdist_wheel.py", line 290, in run
self.run_command('build')
File "/home/mona/anaconda3/lib/python3.7/distutils/cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "/home/mona/anaconda3/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "/home/mona/anaconda3/lib/python3.7/distutils/command/build.py", line 135, in run
self.run_command(cmd_name)
File "/home/mona/anaconda3/lib/python3.7/distutils/cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "/home/mona/anaconda3/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "/home/mona/anaconda3/lib/python3.7/site-packages/setuptools/command/build_ext.py", line 87, in run
_build_ext.run(self)
File "/home/mona/anaconda3/lib/python3.7/site-packages/Cython/Distutils/old_build_ext.py", line 186, in run
_build_ext.build_ext.run(self)
File "/home/mona/anaconda3/lib/python3.7/distutils/command/build_ext.py", line 340, in run
self.build_extensions()
File "/home/mona/anaconda3/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 649, in build_extensions
build_ext.build_extensions(self)
File "/home/mona/anaconda3/lib/python3.7/site-packages/Cython/Distutils/old_build_ext.py", line 195, in build_extensions
_build_ext.build_ext.build_extensions(self)
File "/home/mona/anaconda3/lib/python3.7/distutils/command/build_ext.py", line 449, in build_extensions
self._build_extensions_serial()
File "/home/mona/anaconda3/lib/python3.7/distutils/command/build_ext.py", line 474, in _build_extensions_serial
self.build_extension(ext)
File "/home/mona/anaconda3/lib/python3.7/site-packages/setuptools/command/build_ext.py", line 208, in build_extension
_build_ext.build_extension(self, ext)
File "/home/mona/anaconda3/lib/python3.7/distutils/command/build_ext.py", line 534, in build_extension
depends=ext.depends)
File "/home/mona/anaconda3/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 478, in unix_wrap_ninja_compile
with_cuda=with_cuda)
File "/home/mona/anaconda3/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1233, in _write_ninja_file_and_compile_objects
error_prefix='Error compiling objects for extension')
File "/home/mona/anaconda3/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1529, in _run_ninja_build
raise RuntimeError(message)
RuntimeError: Error compiling objects for extension
----------------------------------------
ERROR: Failed building wheel for neural-renderer-pytorch
Running setup.py clean for neural-renderer-pytorch
Failed to build neural-renderer-pytorch
Installing collected packages: neural-renderer-pytorch
Attempting uninstall: neural-renderer-pytorch
Found existing installation: neural-renderer-pytorch 1.1.3
Uninstalling neural-renderer-pytorch-1.1.3:
Successfully uninstalled neural-renderer-pytorch-1.1.3
Running setup.py install for neural-renderer-pytorch ... error
ERROR: Command errored out with exit status 1:
command: /home/mona/anaconda3/bin/python3.7 -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-req-build-ma51z6r7/setup.py'"'"'; __file__='"'"'/tmp/pip-req-build-ma51z6r7/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /tmp/pip-record-ul8nk1jn/install-record.txt --single-version-externally-managed --compile --install-headers /home/mona/anaconda3/include/python3.7m/neural-renderer-pytorch
cwd: /tmp/pip-req-build-ma51z6r7/
Complete output (212 lines):
running install
running build
running build_py
creating build
creating build/lib.linux-x86_64-3.7
creating build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/load_obj.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/perspective.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/vertices_to_faces.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/visibility.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/get_points_from_angles.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/look.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/projection.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/rasterize.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/save_obj.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/look_at.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/__init__.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/lighting.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/mesh.py -> build/lib.linux-x86_64-3.7/neural_renderer
copying neural_renderer/renderer.py -> build/lib.linux-x86_64-3.7/neural_renderer
creating build/lib.linux-x86_64-3.7/neural_renderer/cuda
copying neural_renderer/cuda/__init__.py -> build/lib.linux-x86_64-3.7/neural_renderer/cuda
running build_ext
building 'neural_renderer.cuda.load_textures' extension
creating /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7
creating /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer
creating /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda
Emitting ninja build file /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/build.ninja...
Compiling objects...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
[1/2] c++ -MMD -MF /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda/load_textures_cuda.o.d -pthread -B /home/mona/anaconda3/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/TH -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/THC -I/home/mona/anaconda3/include/python3.7m -c -c /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp -o /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda/load_textures_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=load_textures -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
FAILED: /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda/load_textures_cuda.o
c++ -MMD -MF /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda/load_textures_cuda.o.d -pthread -B /home/mona/anaconda3/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/TH -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/THC -I/home/mona/anaconda3/include/python3.7m -c -c /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp -o /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda/load_textures_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=load_textures -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
In file included from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Parallel.h:149,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/utils.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/nn/cloneable.h:5,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/nn.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:7,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:1:
/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/ParallelOpenMP.h:84: warning: ignoring #pragma omp parallel [-Wunknown-pragmas]
84 | #pragma omp parallel for if ((end - begin) >= grain_size)
|
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp: In function ‘at::Tensor load_textures(at::Tensor, at::Tensor, at::Tensor, at::Tensor, int, int)’:
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:15:39: warning: ‘at::DeprecatedTypeProperties& at::Tensor::type() const’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [-Wdeprecated-declarations]
15 | #define CHECK_CUDA(x) AT_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:17:24: note: in expansion of macro ‘CHECK_CUDA’
17 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:28:5: note: in expansion of macro ‘CHECK_INPUT’
28 | CHECK_INPUT(image);
| ^~~~~~~~~~~
In file included from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Tensor.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Context.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:5,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:1:
/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/core/TensorBody.h:268:30: note: declared here
268 | DeprecatedTypeProperties & type() const {
| ^~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:15:23: error: ‘AT_CHECK’ was not declared in this scope; did you mean ‘DCHECK’?
15 | #define CHECK_CUDA(x) AT_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:17:24: note: in expansion of macro ‘CHECK_CUDA’
17 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:28:5: note: in expansion of macro ‘CHECK_INPUT’
28 | CHECK_INPUT(image);
| ^~~~~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:15:39: warning: ‘at::DeprecatedTypeProperties& at::Tensor::type() const’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [-Wdeprecated-declarations]
15 | #define CHECK_CUDA(x) AT_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:17:24: note: in expansion of macro ‘CHECK_CUDA’
17 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:29:5: note: in expansion of macro ‘CHECK_INPUT’
29 | CHECK_INPUT(faces);
| ^~~~~~~~~~~
In file included from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Tensor.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Context.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:5,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:1:
/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/core/TensorBody.h:268:30: note: declared here
268 | DeprecatedTypeProperties & type() const {
| ^~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:15:39: warning: ‘at::DeprecatedTypeProperties& at::Tensor::type() const’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [-Wdeprecated-declarations]
15 | #define CHECK_CUDA(x) AT_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:17:24: note: in expansion of macro ‘CHECK_CUDA’
17 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:30:5: note: in expansion of macro ‘CHECK_INPUT’
30 | CHECK_INPUT(is_update);
| ^~~~~~~~~~~
In file included from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Tensor.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Context.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:5,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:1:
/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/core/TensorBody.h:268:30: note: declared here
268 | DeprecatedTypeProperties & type() const {
| ^~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:15:39: warning: ‘at::DeprecatedTypeProperties& at::Tensor::type() const’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [-Wdeprecated-declarations]
15 | #define CHECK_CUDA(x) AT_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:17:24: note: in expansion of macro ‘CHECK_CUDA’
17 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:31:5: note: in expansion of macro ‘CHECK_INPUT’
31 | CHECK_INPUT(textures);
| ^~~~~~~~~~~
In file included from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Tensor.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/Context.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:5,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:4,
from /home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda.cpp:1:
/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/ATen/core/TensorBody.h:268:30: note: declared here
268 | DeprecatedTypeProperties & type() const {
| ^~~~
[2/2] /usr/bin/nvcc -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/TH -I/home/mona/anaconda3/lib/python3.7/site-packages/torch/include/THC -I/home/mona/anaconda3/include/python3.7m -c -c /tmp/pip-req-build-ma51z6r7/neural_renderer/cuda/load_textures_cuda_kernel.cu -o /tmp/pip-req-build-ma51z6r7/build/temp.linux-x86_64-3.7/neural_renderer/cuda/load_textures_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H -DTORCH_EXTENSION_NAME=load_textures -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_75,code=sm_75 -std=c++14
ninja: build stopped: subcommand failed.
Traceback (most recent call last):
File "/home/mona/anaconda3/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1515, in _run_ninja_build
env=env)
File "/home/mona/anaconda3/lib/python3.7/subprocess.py", line 512, in run
output=stdout, stderr=stderr)
subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 1.
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/tmp/pip-req-build-ma51z6r7/setup.py", line 40, in <module>
cmdclass = {'build_ext': BuildExtension}
File "/home/mona/anaconda3/lib/python3.7/site-packages/setuptools/__init__.py", line 163, in setup
return distutils.core.setup(**attrs)
File "/home/mona/anaconda3/lib/python3.7/distutils/core.py", line 148, in setup
dist.run_commands()
File "/home/mona/anaconda3/lib/python3.7/distutils/dist.py", line 966, in run_commands
self.run_command(cmd)
File "/home/mona/anaconda3/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "/home/mona/anaconda3/lib/python3.7/site-packages/setuptools/command/install.py", line 61, in run
return orig.install.run(self)
File "/home/mona/anaconda3/lib/python3.7/distutils/command/install.py", line 545, in run
self.run_command('build')
File "/home/mona/anaconda3/lib/python3.7/distutils/cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "/home/mona/anaconda3/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "/home/mona/anaconda3/lib/python3.7/distutils/command/build.py", line 135, in run
self.run_command(cmd_name)
File "/home/mona/anaconda3/lib/python3.7/distutils/cmd.py", line 313, in run_command
self.distribution.run_command(command)
File "/home/mona/anaconda3/lib/python3.7/distutils/dist.py", line 985, in run_command
cmd_obj.run()
File "/home/mona/anaconda3/lib/python3.7/site-packages/setuptools/command/build_ext.py", line 87, in run
_build_ext.run(self)
File "/home/mona/anaconda3/lib/python3.7/site-packages/Cython/Distutils/old_build_ext.py", line 186, in run
_build_ext.build_ext.run(self)
File "/home/mona/anaconda3/lib/python3.7/distutils/command/build_ext.py", line 340, in run
self.build_extensions()
File "/home/mona/anaconda3/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 649, in build_extensions
build_ext.build_extensions(self)
File "/home/mona/anaconda3/lib/python3.7/site-packages/Cython/Distutils/old_build_ext.py", line 195, in build_extensions
_build_ext.build_ext.build_extensions(self)
File "/home/mona/anaconda3/lib/python3.7/distutils/command/build_ext.py", line 449, in build_extensions
self._build_extensions_serial()
File "/home/mona/anaconda3/lib/python3.7/distutils/command/build_ext.py", line 474, in _build_extensions_serial
self.build_extension(ext)
File "/home/mona/anaconda3/lib/python3.7/site-packages/setuptools/command/build_ext.py", line 208, in build_extension
_build_ext.build_extension(self, ext)
File "/home/mona/anaconda3/lib/python3.7/distutils/command/build_ext.py", line 534, in build_extension
depends=ext.depends)
File "/home/mona/anaconda3/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 478, in unix_wrap_ninja_compile
with_cuda=with_cuda)
File "/home/mona/anaconda3/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1233, in _write_ninja_file_and_compile_objects
error_prefix='Error compiling objects for extension')
File "/home/mona/anaconda3/lib/python3.7/site-packages/torch/utils/cpp_extension.py", line 1529, in _run_ninja_build
raise RuntimeError(message)
RuntimeError: Error compiling objects for extension
----------------------------------------
Rolling back uninstall of neural-renderer-pytorch
Moving to /home/mona/anaconda3/lib/python3.7/site-packages/neural_renderer/
from /home/mona/anaconda3/lib/python3.7/site-packages/~eural_renderer
Moving to /home/mona/anaconda3/lib/python3.7/site-packages/neural_renderer_pytorch-1.1.3.dist-info/
from /home/mona/anaconda3/lib/python3.7/site-packages/~eural_renderer_pytorch-1.1.3.dist-info
ERROR: Command errored out with exit status 1: /home/mona/anaconda3/bin/python3.7 -u -c 'import sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-req-build-ma51z6r7/setup.py'"'"'; __file__='"'"'/tmp/pip-req-build-ma51z6r7/setup.py'"'"';f=getattr(tokenize, '"'"'open'"'"', open)(__file__);code=f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, __file__, '"'"'exec'"'"'))' install --record /tmp/pip-record-ul8nk1jn/install-record.txt --single-version-externally-managed --compile --install-headers /home/mona/anaconda3/include/python3.7m/neural-renderer-pytorch Check the logs for full command output.
I have:
$ python
Python 3.7.6 (default, Jan 8 2020, 19:59:22)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import torch
>>> torch.__version__
'1.6.0'
$ lsb_release -a
LSB Version: core-11.1.0ubuntu2-noarch:security-11.1.0ubuntu2-noarch
Distributor ID: Ubuntu
Description: Ubuntu 20.04.1 LTS
Release: 20.04
Codename: focal
$ nvidia-smi
Sun Dec 6 16:36:36 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 450.80.02 Driver Version: 450.80.02 CUDA Version: 11.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 GeForce RTX 2070 Off | 00000000:01:00.0 Off | N/A |
| N/A 49C P8 21W / N/A | 1546MiB / 7982MiB | 8% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
$ nvcc --version
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2019 NVIDIA Corporation
Built on Sun_Jul_28_19:07:16_PDT_2019
Cuda compilation tools, release 10.1, V10.1.243
Hi,
Thanks for uploading your code!
I am wondering:
Cheers!
when I run full_eval, I get this error. I don't find the function of CollisionVolume.
What is the difference between the two joint regressors? From what I can tell J_regressor_extra is used to extract smpl paramters during smplifyx fitting operation for dataset generation, while J_regressor_h36m is used solely in loss calculation.
Since J_regressor_extra is used to fit SMPL keypoints to gt keypoints would it not also work for loss calculation?
When I run full_eval.py, I get this error? How to solve it.
I ran the main.py in GeForce RTX 2080, and got the results 85 images per hour. Is it the right speed?
Seemks like there are something wrong with the smplx.
Does this is caused by the version difference?
e_folder=demo_images/ --output_folder=results/ --ckpt data/checkpoint.pt
WARNING: You are using a SMPL model, with only 10 shape coefficients.
WARNING: You are using a SMPL model, with only 10 shape coefficients.
unexpected key in source state_dict: fc.weight, fc.bias
missing keys in source state_dict: layer2.0.bn1.num_batches_tracked, layer4.0.downsample.1.num_batches_tracked, layer4.2.bn3.num_batches_tracked, layer3.0.downsample.1.num_batches_tracked, layer1.1.bn3.num_batches_tracked, layer4.0.bn1.num_batches_tracked, layer4.2.bn1.num_batches_tracked, layer2.0.bn2.num_batches_tracked, layer3.1.bn2.num_batches_tracked, layer1.0.downsample.1.num_batches_tracked, layer3.3.bn2.num_batches_tracked, layer1.2.bn2.num_batches_tracked, layer4.2.bn2.num_batches_tracked, layer3.5.bn2.num_batches_tracked, layer2.3.bn3.num_batches_tracked, layer2.1.bn2.num_batches_tracked, layer3.2.bn2.num_batches_tracked, layer4.1.bn2.num_batches_tracked, layer1.0.bn1.num_batches_tracked, layer1.1.bn1.num_batches_tracked, layer2.0.bn3.num_batches_tracked, layer3.0.bn1.num_batches_tracked, layer2.3.bn1.num_batches_tracked, layer3.5.bn3.num_batches_tracked, layer3.4.bn3.num_batches_tracked, layer3.5.bn1.num_batches_tracked, layer3.4.bn2.num_batches_tracked, layer3.0.bn2.num_batches_tracked, layer2.3.bn2.num_batches_tracked, layer1.2.bn3.num_batches_tracked, layer2.2.bn3.num_batches_tracked, layer3.2.bn3.num_batches_tracked, layer4.0.bn3.num_batches_tracked, layer3.1.bn3.num_batches_tracked, layer2.2.bn1.num_batches_tracked, layer2.2.bn2.num_batches_tracked, layer1.0.bn2.num_batches_tracked, layer3.3.bn3.num_batches_tracked, layer1.2.bn1.num_batches_tracked, layer3.4.bn1.num_batches_tracked, layer2.1.bn1.num_batches_tracked, layer2.0.downsample.1.num_batches_tracked, layer3.2.bn1.num_batches_tracked, layer3.3.bn1.num_batches_tracked, layer1.0.bn3.num_batches_tracked, layer3.0.bn3.num_batches_tracked, layer2.1.bn3.num_batches_tracked, layer1.1.bn2.num_batches_tracked, layer4.1.bn1.num_batches_tracked, layer4.0.bn2.num_batches_tracked, layer4.1.bn3.num_batches_tracked, layer3.1.bn1.num_batches_tracked, bn1.num_batches_tracked
2021-02-15 16:49:01,865 - INFO - load checkpoint from data/checkpoint.pt
2021-02-15 16:49:02,106 - WARNING - missing keys in source state_dict: smpl_head.smpl.parents, smpl_head.smpl.faces_tensor, smpl_head.smpl.J_regressor_extra, smpl_head.loss.smpl.faces_tensor, smpl_head.loss.smpl.v_template, smpl_head.loss.smpl.lbs_weights, smpl_head.loss.smpl.J_regressor, smpl_head.loss.smpl.J_regressor_extra, smpl_head.loss.smpl.vertex_joint_selector.extra_joints_idxs, smpl_head.smpl.shapedirs, smpl_head.smpl.J_regressor, smpl_head.loss.smpl.parents, smpl_head.smpl.vertex_joint_selector.extra_joints_idxs, smpl_head.smpl.v_template, smpl_head.loss.smpl.shapedirs, smpl_head.smpl.posedirs, smpl_head.smpl.lbs_weights, smpl_head.loss.smpl.posedirs
2021-02-15 16:49:02,121 - INFO - resumed epoch 27, iter 90901
WARNING: You are using a SMPL model, with only 10 shape coefficients.
Traceback (most recent call last):
File "tools/demo.py", line 190, in <module>
main()
File "tools/demo.py", line 180, in main
bbox_results, pred_results = model(**data_batch, return_loss=False)
File "/media/frank/MyPassport/anaconda3/envs/multiperson/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in __call__
result = self.forward(*input, **kwargs)
File "/media/frank/MyPassport/anaconda3/envs/multiperson/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 150, in forward
return self.module(*inputs[0], **kwargs[0])
File "/media/frank/MyPassport/anaconda3/envs/multiperson/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in __call__
result = self.forward(*input, **kwargs)
File "/media/frank/MyPassport/Code/HPE/multiperson/mmdetection/mmdet/core/fp16/decorators.py", line 49, in new_func
return old_func(*args, **kwargs)
File "/media/frank/MyPassport/Code/HPE/multiperson/mmdetection/mmdet/models/detectors/base.py", line 88, in forward
return self.forward_test(img, img_meta, **kwargs)
File "/media/frank/MyPassport/Code/HPE/multiperson/mmdetection/mmdet/models/detectors/smpl_rcnn.py", line 419, in forward_test
return self.simple_test(imgs, img_metas, **kwargs)
File "/media/frank/MyPassport/Code/HPE/multiperson/mmdetection/mmdet/models/detectors/smpl_rcnn.py", line 374, in simple_test
smpl_results = self.simple_test_smpl(x, img_meta, det_bboxes, img.shape, rescale=rescale)
File "/media/frank/MyPassport/Code/HPE/multiperson/mmdetection/mmdet/models/detectors/test_mixins.py", line 189, in simple_test_smpl
smpl_pred = self.smpl_head(smpl_feats)
File "/media/frank/MyPassport/anaconda3/envs/multiperson/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in __call__
result = self.forward(*input, **kwargs)
File "/media/frank/MyPassport/Code/HPE/multiperson/mmdetection/mmdet/models/smpl_heads/smpl_head.py", line 132, in forward
global_orient=pred_rotmat[:, 0].unsqueeze(1), pose2rot=False)
File "/media/frank/MyPassport/anaconda3/envs/multiperson/lib/python3.7/site-packages/torch/nn/modules/module.py", line 493, in __call__
result = self.forward(*input, **kwargs)
File "/media/frank/MyPassport/Code/HPE/multiperson/mmdetection/mmdet/models/utils/smpl/smpl.py", line 64, in forward
output = ModelOutput(vertices=smpl_output.vertices,
NameError: name 'ModelOutput' is not defined
ENVs:
I tried to install the pkg strictly following the instructions.
Ubuntu 16.04
CUDA: 10.1
Package Version Location
----------------------- ------------- --------------------------------------------------------
addict 2.2.1
argon2-cffi 20.1.0
asn1crypto 1.2.0
async-generator 1.10
attrs 20.3.0
backcall 0.1.0
bleach 3.3.0
certifi 2019.11.28
cffi 1.13.0
chardet 3.0.4
chumpy 0.69
conda 4.8.2
conda-package-handling 1.6.0
ConfigArgParse 1.3
cryptography 2.8
cycler 0.10.0
Cython 0.29.15
decorator 4.4.2
defusedxml 0.6.0
entrypoints 0.3
filelock 3.0.12
freetype-py 2.1.0.post1
future 0.18.2
gdown 3.12.2
h5py 2.10.0
idna 2.8
imageio 2.8.0
importlib-metadata 3.4.0
install 1.3.4
ipdb 0.13.2
ipykernel 5.4.3
ipython 7.13.0
ipython-genutils 0.2.0
ipywidgets 7.6.3
jedi 0.16.0
Jinja2 2.11.3
jsonschema 3.2.0
jupyter-client 6.1.11
jupyter-core 4.7.1
jupyterlab-pygments 0.1.2
jupyterlab-widgets 1.0.0
kiwisolver 1.1.0
MarkupSafe 1.1.1
matplotlib 3.2.0rc3
mistune 0.8.4
mkl-fft 1.0.15
mkl-random 1.1.0
mkl-service 2.3.0
mmcv 0.2.10
mmdet 0.6.0+unknown /media/frank/MyPassport/Code/HPE/multiperson/mmdetection
mpmath 1.2.1
nbclient 0.5.2
nbconvert 6.0.7
nbformat 5.1.2
nest-asyncio 1.5.1
networkx 2.4
neural-renderer-pytorch 1.1.3
notebook 6.2.0
numpy 1.18.1
olefile 0.46
open3d-python 0.7.0.0
opencv-python 4.2.0.32
packaging 20.9
pandas 1.0.1
pandocfilters 1.4.3
parso 0.6.2
pexpect 4.8.0
pickleshare 0.7.5
Pillow 6.1.0
pip 19.3.1
prometheus-client 0.9.0
prompt-toolkit 3.0.4
protobuf 3.11.3
ptyprocess 0.6.0
pycocotools 2.0.0
pycosat 0.6.3
pycparser 2.19
pyglet 1.5.0
Pygments 2.6.1
PyMCubes 0.1.2
PyOpenGL 3.1.0
pyOpenSSL 19.0.0
pyparsing 2.4.6
pypng 0.0.20
pyrender 0.1.36
pyrsistent 0.17.3
PySocks 1.7.1
python-dateutil 2.8.1
pytz 2019.3
PyWavelets 1.1.1
PyYAML 5.4.1
pyzmq 22.0.3
requests 2.22.0
ruamel-yaml 0.15.46
scikit-image 0.16.2
scipy 1.4.1
sdf-pytorch 0.0.1
seaborn 0.10.0
Send2Trash 1.5.0
setuptools 41.4.0
Shapely 1.7.1
six 1.12.0
smpl 0.0.66
smplx 0.1.21
sympy 1.7.1
tensorboardX 2.0
terminado 0.9.2
terminaltables 3.1.0
testpath 0.4.4
torch 1.1.0
torchgeometry 0.1.2
torchvision 0.3.0
tornado 6.1
tqdm 4.36.1
traitlets 4.3.3
trimesh 3.5.25
typing-extensions 3.7.4.3
uncertainties 3.1.5
urllib3 1.24.2
wcwidth 0.1.9
webencodings 0.5.1
wheel 0.33.6
widgetsnbextension 3.5.1
zipp 3.4.0
Thanks for your great work!
I want to use the sdf package in my own project and the installation process is finished. But when I am trying to run my code, I get the following error. How can I solve the problem?
Traceback (most recent call last):
File "test.py", line 20, in
fai = get_sdf(test_faces, test_vertics)
File "/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/sdf.py", line 25, in forward
phi = SDFFunction.apply(phi, faces, vertices)
File "/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/sdf.py", line 15, in forward
return _C.sdf(phi, faces, vertices)
AttributeError: module 'sdf.csrc' has no attribute 'sdf'
The installation process:
`running install
running bdist_egg
running egg_info
creating sdf_pytorch.egg-info
writing sdf_pytorch.egg-info/PKG-INFO
writing dependency_links to sdf_pytorch.egg-info/dependency_links.txt
writing top-level names to sdf_pytorch.egg-info/top_level.txt
writing manifest file 'sdf_pytorch.egg-info/SOURCES.txt'
package init file 'sdf/csrc/init.py' not found (or not a regular file)
reading manifest file 'sdf_pytorch.egg-info/SOURCES.txt'
writing manifest file 'sdf_pytorch.egg-info/SOURCES.txt'
installing library code to build/bdist.linux-x86_64/egg
running install_lib
running build_py
creating build
creating build/lib.linux-x86_64-3.7
creating build/lib.linux-x86_64-3.7/sdf
copying sdf/sdf.py -> build/lib.linux-x86_64-3.7/sdf
copying sdf/sdf_loss.py -> build/lib.linux-x86_64-3.7/sdf
copying sdf/init.py -> build/lib.linux-x86_64-3.7/sdf
running build_ext
building 'sdf.csrc' extension
creating /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/build/temp.linux-x86_64-3.7
creating /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/build/temp.linux-x86_64-3.7/sdf
creating /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/build/temp.linux-x86_64-3.7/sdf/csrc
Emitting ninja build file /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/build/temp.linux-x86_64-3.7/build.ninja...
Compiling objects...
Allowing ninja to set a default number of workers... (overridable by setting the environment variable MAX_JOBS=N)
[1/2] /usr/local/cuda/bin/nvcc -I/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include -I/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/TH -I/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/mnt/data3/HOME/zjx/miniconda3/include/python3.7m -c -c /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda_kernel.cu -o /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/build/temp.linux-x86_64-3.7/sdf/csrc/sdf_cuda_kernel.o -D__CUDA_NO_HALF_OPERATORS__ -D__CUDA_NO_HALF_CONVERSIONS__ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr --compiler-options ''"'"'-fPIC'"'"'' -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=csrc -D_GLIBCXX_USE_CXX11_ABI=0 -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_86,code=sm_86 -std=c++14
[2/2] c++ -MMD -MF /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/build/temp.linux-x86_64-3.7/sdf/csrc/sdf_cuda.o.d -pthread -B /mnt/data3/HOME/zjx/miniconda3/compiler_compat -Wl,--sysroot=/ -Wsign-compare -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC -I/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include -I/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include -I/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/TH -I/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/THC -I/usr/local/cuda/include -I/mnt/data3/HOME/zjx/miniconda3/include/python3.7m -c -c /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp -o /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/build/temp.linux-x86_64-3.7/sdf/csrc/sdf_cuda.o -DTORCH_API_INCLUDE_EXTENSION_H '-DPYBIND11_COMPILER_TYPE="_gcc"' '-DPYBIND11_STDLIB="_libstdcpp"' '-DPYBIND11_BUILD_ABI="_cxxabi1011"' -DTORCH_EXTENSION_NAME=csrc -D_GLIBCXX_USE_CXX11_ABI=0 -std=c++14
cc1plus: warning: command line option ‘-Wstrict-prototypes’ is valid for C/ObjC but not for C++
In file included from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/core/DeviceType.h:8,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/core/Device.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/core/Allocator.h:6,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:7,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:8,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:1:
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp: In function ‘at::Tensor sdf(at::Tensor, at::Tensor, at::Tensor)’:
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:3:42: warning: ‘at::DeprecatedTypeProperties& at::Tensor::type() const’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [-Wdeprecated-declarations]
3 | #define CHECK_CUDA(x) TORCH_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^
/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/macros/Macros.h:197:64: note: in definition of macro ‘C10_UNLIKELY’
197 | #define C10_UNLIKELY(expr) (__builtin_expect(static_cast(expr), 0))
| ^~~~
/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/util/Exception.h:441:7: note: in expansion of macro ‘C10_UNLIKELY_OR_CONST’
441 | if (C10_UNLIKELY_OR_CONST(!(cond))) {
| ^~~~~~~~~~~~~~~~~~~~~
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:3:23: note: in expansion of macro ‘TORCH_CHECK’
3 | #define CHECK_CUDA(x) TORCH_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^~~~~~~~~~~
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:5:24: note: in expansion of macro ‘CHECK_CUDA’
5 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:19:2: note: in expansion of macro ‘CHECK_INPUT’
19 | CHECK_INPUT(phi);
| ^~~~~~~~~~~
In file included from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/Tensor.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/Context.h:4,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:9,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:8,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:1:
/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/core/TensorBody.h:194:30: note: declared here
194 | DeprecatedTypeProperties & type() const {
| ^~~~
In file included from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/core/DeviceType.h:8,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/core/Device.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/core/Allocator.h:6,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:7,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:8,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:1:
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:3:42: warning: ‘at::DeprecatedTypeProperties& at::Tensor::type() const’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [-Wdeprecated-declarations]
3 | #define CHECK_CUDA(x) TORCH_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^
/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/macros/Macros.h:197:64: note: in definition of macro ‘C10_UNLIKELY’
197 | #define C10_UNLIKELY(expr) (__builtin_expect(static_cast(expr), 0))
| ^~~~
/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/util/Exception.h:441:7: note: in expansion of macro ‘C10_UNLIKELY_OR_CONST’
441 | if (C10_UNLIKELY_OR_CONST(!(cond))) {
| ^~~~~~~~~~~~~~~~~~~~~
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:3:23: note: in expansion of macro ‘TORCH_CHECK’
3 | #define CHECK_CUDA(x) TORCH_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^~~~~~~~~~~
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:5:24: note: in expansion of macro ‘CHECK_CUDA’
5 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:20:2: note: in expansion of macro ‘CHECK_INPUT’
20 | CHECK_INPUT(faces);
| ^~~~~~~~~~~
In file included from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/Tensor.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/Context.h:4,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:9,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:8,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:1:
/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/core/TensorBody.h:194:30: note: declared here
194 | DeprecatedTypeProperties & type() const {
| ^~~~
In file included from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/core/DeviceType.h:8,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/core/Device.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/core/Allocator.h:6,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:7,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:8,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:1:
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:3:42: warning: ‘at::DeprecatedTypeProperties& at::Tensor::type() const’ is deprecated: Tensor.type() is deprecated. Instead use Tensor.options(), which in many cases (e.g. in a constructor) is a drop-in replacement. If you were using data from type(), that is now available from Tensor itself, so instead of tensor.type().scalar_type(), use tensor.scalar_type() instead and instead of tensor.type().backend() use tensor.device(). [-Wdeprecated-declarations]
3 | #define CHECK_CUDA(x) TORCH_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^
/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/macros/Macros.h:197:64: note: in definition of macro ‘C10_UNLIKELY’
197 | #define C10_UNLIKELY(expr) (__builtin_expect(static_cast(expr), 0))
| ^~~~
/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/c10/util/Exception.h:441:7: note: in expansion of macro ‘C10_UNLIKELY_OR_CONST’
441 | if (C10_UNLIKELY_OR_CONST(!(cond))) {
| ^~~~~~~~~~~~~~~~~~~~~
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:3:23: note: in expansion of macro ‘TORCH_CHECK’
3 | #define CHECK_CUDA(x) TORCH_CHECK(x.type().is_cuda(), #x " must be a CUDA tensor")
| ^~~~~~~~~~~
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:5:24: note: in expansion of macro ‘CHECK_CUDA’
5 | #define CHECK_INPUT(x) CHECK_CUDA(x); CHECK_CONTIGUOUS(x)
| ^~~~~~~~~~
/mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:21:2: note: in expansion of macro ‘CHECK_INPUT’
21 | CHECK_INPUT(vertices);
| ^~~~~~~~~~~
In file included from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/Tensor.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/Context.h:4,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/ATen.h:9,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/types.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader_options.h:4,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/base.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader/stateful.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data/dataloader.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/data.h:3,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/all.h:8,
from /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/torch/csrc/api/include/torch/torch.h:3,
from /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/sdf/csrc/sdf_cuda.cpp:1:
/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/include/ATen/core/TensorBody.h:194:30: note: declared here
194 | DeprecatedTypeProperties & type() const {
| ^~~~
g++ -pthread -shared -B /mnt/data3/HOME/zjx/miniconda3/compiler_compat -L/mnt/data3/HOME/zjx/miniconda3/lib -Wl,-rpath=/mnt/data3/HOME/zjx/miniconda3/lib -Wl,--no-as-needed -Wl,--sysroot=/ /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/build/temp.linux-x86_64-3.7/sdf/csrc/sdf_cuda.o /mnt/data3/HOME/zjx/code/PMnet_pytorch/outside-code/sdf/build/temp.linux-x86_64-3.7/sdf/csrc/sdf_cuda_kernel.o -L/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/torch/lib -L/usr/local/cuda/lib64 -lc10 -ltorch -ltorch_cpu -ltorch_python -lcudart -lc10_cuda -ltorch_cuda_cu -ltorch_cuda_cpp -o build/lib.linux-x86_64-3.7/sdf/csrc.cpython-37m-x86_64-linux-gnu.so
creating build/bdist.linux-x86_64
creating build/bdist.linux-x86_64/egg
creating build/bdist.linux-x86_64/egg/sdf
copying build/lib.linux-x86_64-3.7/sdf/csrc.cpython-37m-x86_64-linux-gnu.so -> build/bdist.linux-x86_64/egg/sdf
copying build/lib.linux-x86_64-3.7/sdf/sdf.py -> build/bdist.linux-x86_64/egg/sdf
copying build/lib.linux-x86_64-3.7/sdf/sdf_loss.py -> build/bdist.linux-x86_64/egg/sdf
copying build/lib.linux-x86_64-3.7/sdf/init.py -> build/bdist.linux-x86_64/egg/sdf
byte-compiling build/bdist.linux-x86_64/egg/sdf/sdf.py to sdf.cpython-37.pyc
byte-compiling build/bdist.linux-x86_64/egg/sdf/sdf_loss.py to sdf_loss.cpython-37.pyc
byte-compiling build/bdist.linux-x86_64/egg/sdf/init.py to init.cpython-37.pyc
creating stub loader for sdf/csrc.cpython-37m-x86_64-linux-gnu.so
byte-compiling build/bdist.linux-x86_64/egg/sdf/csrc.py to csrc.cpython-37.pyc
creating build/bdist.linux-x86_64/egg/EGG-INFO
copying sdf_pytorch.egg-info/PKG-INFO -> build/bdist.linux-x86_64/egg/EGG-INFO
copying sdf_pytorch.egg-info/SOURCES.txt -> build/bdist.linux-x86_64/egg/EGG-INFO
copying sdf_pytorch.egg-info/dependency_links.txt -> build/bdist.linux-x86_64/egg/EGG-INFO
copying sdf_pytorch.egg-info/top_level.txt -> build/bdist.linux-x86_64/egg/EGG-INFO
writing build/bdist.linux-x86_64/egg/EGG-INFO/native_libs.txt
zip_safe flag not set; analyzing archive contents...
sdf.pycache.csrc.cpython-37: module references file
creating dist
creating 'dist/sdf_pytorch-0.0.1-py3.7-linux-x86_64.egg' and adding 'build/bdist.linux-x86_64/egg' to it
removing 'build/bdist.linux-x86_64/egg' (and everything under it)
Processing sdf_pytorch-0.0.1-py3.7-linux-x86_64.egg
removing '/mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/sdf_pytorch-0.0.1-py3.7-linux-x86_64.egg' (and everything under it)
creating /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/sdf_pytorch-0.0.1-py3.7-linux-x86_64.egg
Extracting sdf_pytorch-0.0.1-py3.7-linux-x86_64.egg to /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages
sdf-pytorch 0.0.1 is already the active version in easy-install.pth
Installed /mnt/data3/HOME/zjx/miniconda3/lib/python3.7/site-packages/sdf_pytorch-0.0.1-py3.7-linux-x86_64.egg
Processing dependencies for sdf-pytorch==0.0.1
Finished processing dependencies for sdf-pytorch==0.0.1`
Traceback (most recent call last):
File "tools/demo.py", line 190, in
main()
File "tools/demo.py", line 131, in main
cfg.model, train_cfg=cfg.train_cfg, test_cfg=cfg.test_cfg)
File "/root/picasso/xhzhang/multiperson/mmdetection/mmdet/models/builder.py", line 60, in build_detector
return build(cfg, DETECTORS, dict(train_cfg=train_cfg, test_cfg=test_cfg))
File "/root/picasso/xhzhang/multiperson/mmdetection/mmdet/models/builder.py", line 32, in build
return _build_module(cfg, registry, default_args)
File "/root/picasso/xhzhang/multiperson/mmdetection/mmdet/models/builder.py", line 24, in _build_module
return obj_type(**args)
File "/root/picasso/xhzhang/multiperson/mmdetection/mmdet/models/detectors/smpl_rcnn.py", line 65, in init
self.smpl_head = builder.build_head(smpl_head)
File "/root/picasso/xhzhang/multiperson/mmdetection/mmdet/models/builder.py", line 52, in build_head
return build(cfg, HEADS)
File "/root/picasso/xhzhang/multiperson/mmdetection/mmdet/models/builder.py", line 32, in build
return _build_module(cfg, registry, default_args)
File "/root/picasso/xhzhang/multiperson/mmdetection/mmdet/models/builder.py", line 24, in _build_module
return obj_type(**args)
File "/root/picasso/xhzhang/multiperson/mmdetection/mmdet/models/smpl_heads/smpl_head.py", line 74, in init
self.loss = build_loss(loss_cfg)
File "/root/picasso/xhzhang/multiperson/mmdetection/mmdet/models/builder.py", line 56, in build_loss
return build(cfg, LOSSES)
File "/root/picasso/xhzhang/multiperson/mmdetection/mmdet/models/builder.py", line 32, in build
return _build_module(cfg, registry, default_args)
File "/root/picasso/xhzhang/multiperson/mmdetection/mmdet/models/builder.py", line 24, in _build_module
return obj_type(**args)
File "/root/picasso/xhzhang/multiperson/mmdetection/mmdet/models/losses/smpl_loss.py", line 107, in init
anti_aliasing=False)
File "/root/anaconda3/envs/multiperson/lib/python3.7/site-packages/neural_renderer_pytorch-1.1.3-py3.7-linux-x86_64.egg/neural_renderer/renderer.py", line 41, in init
self.dist_coeffs = torch.cuda.FloatTensor([[0., 0., 0., 0., 0.]])
RuntimeError: CUDA error: unknown error
hi
when i see the keypoints of 160422_mafia2 dataset , some of gt keypoints is not correct.
how to get keypoints from mafia2_dataset??
HI! Awesome work!
This is an error with evaluation code.
Traceback (most recent call last):
File "tools/full_eval.py", line 35, in
from mmdetection.mmdet.core.utils.eval_utils import H36MEvalHandler, EvalHandler, PanopticEvalHandler,
File "/home/seonghyun/CRMH_venv/multiperson-master/mmdetection/mmdet/core/utils/eval_utils.py", line 7, in
from mmdetection.mmdet.models.utils.camera import PerspectiveCamera
ModuleNotFoundError: No module named 'mmdetection.mmdet.models.utils.camera'
and
Traceback (most recent call last):
File "tools/full_eval.py", line 35, in
from mmdetection.mmdet.core.utils.eval_utils import H36MEvalHandler, EvalHandler, PanopticEvalHandler,
File "/home/seonghyun/CRMH_venv/multiperson-master/mmdetection/mmdet/core/utils/eval_utils.py", line 5, in
from mmdetection.mmdet.models.utils.pose_utils import reconstruction_error, vectorize_distance
ImportError: cannot import name 'vectorize_distance' from 'mmdetection.mmdet.models.utils.pose_utils' (/home/seonghyun/CRMH_venv/multiperson-master/mmdetection/mmdet/models/utils/pose_utils.py)
Where can I find these modules?
Not all code has been released yet?
Hi, Kudos for such great work I was wondering under which folder should I place the mean SMPL parameters file and the neutral model pkl file.
Thank you.
Hello, I can't understand why we need this operation. Can we get unique SMPL parameters from 3D key points?
How to prepare the dataset?
Hi, I want to use ordinary calibration camera parameters in the differentiable render, but I find it is non-trival to direct use K, R, t which are obtained from calibration camera parameters.
Hi,
I have a question regarding MuPots annotations. I know you did not create the dataset. However, I see that annotations for some people in the images are missing. For example, for TS1/img_0000001.jpg, the image has 3 people, but annotations for 2d and 3d_kpts come only for 2 people.
Have you came with this problem while evaluating your method?
Thanks
When I run the demo with the default version of smpl-x, I encountered an error - 'no model named ModelOutput'. So I rolled back the version to 0.1.15. The demo.py then ran smoothly. But I found a slight difference between the output of the demo picture and the output of the first picture in the paper. I don't know why it is different.
After a 3D shape is reconstructed, how can I get its 2D bounding box?
Hi,
I was wondering, which data do you use for adversarial pre-training SMPL head?
Is it the same as in Kanazawa paper? or do you use different data.
Thank you
Hi, kudos for the great work! Thank you for sharing the code.
When trying to run demo.py with the command
python3 tools/demo.py --config=configs/smpl/tune.py --image_folder=demo_images/ --output_folder=results/ --ckpt data/checkpoint.pt
I get the following error:
FIle "/miniconda3/envs/multiperson/lib/python3.7/site-packages/mmcv/runner/runner.py", line 313, in resume
self.optimizer.load_state_dict(checkpoint['optimizer'])
File "/miniconda3/envs/multiperson/lib/python3.7/site-packages/torch/optim/optimizer.py", line 115, in load_state_dict
raise ValueError("loaded state dict contains a parameter group "
ValueError: loaded state dict contains a parameter group that doesn't match the size of optimizer's group
It seems to be triggered by something with the checkpoint and the model architecture. I also get the following message:
unexpected key in source state_dict: fc.weight, fc.bias
missing keys in source state_dict: layer3.0.bn2.num_batches_tracked, layer1.2.bn1.num_batches_tracked, layer2.0.bn2.num_batches_tracked, layer2.1.bn1.num_batches_tracked, layer3.0.bn3.num_batches_tracked, layer3.2.bn2.num_batches_tracked, layer1.2.bn2.num_batches_tracked, layer4.2.bn3.num_batches_tracked, layer4.2.bn2.num_batches_tracked, layer3.3.bn1.num_batches_tracked, layer2.1.bn2.num_batches_tracked, layer3.2.bn1.num_batches_tracked, layer2.3.bn2.num_batches_tracked, layer3.0.downsample.1.num_batches_tracked, layer3.3.bn2.num_batches_tracked, layer3.4.bn3.num_batches_tracked, layer1.0.bn2.num_batches_tracked, layer3.5.bn1.num_batches_tracked, layer1.1.bn3.num_batches_tracked, layer3.5.bn3.num_batches_tracked, layer4.0.downsample.1.num_batches_tracked, layer4.1.bn3.num_batches_tracked, layer2.3.bn1.num_batches_tracked, layer3.4.bn1.num_batches_tracked, layer2.2.bn2.num_batches_tracked, layer4.0.bn1.num_batches_tracked, layer2.1.bn3.num_batches_tracked, layer1.1.bn1.num_batches_tracked, layer3.0.bn1.num_batches_tracked, layer2.2.bn1.num_batches_tracked, layer1.0.downsample.1.num_batches_tracked, layer2.0.bn3.num_batches_tracked, layer1.1.bn2.num_batches_tracked, layer4.2.bn1.num_batches_tracked, layer3.2.bn3.num_batches_tracked, layer4.1.bn1.num_batches_tracked, layer2.0.downsample.1.num_batches_tracked, layer1.2.bn3.num_batches_tracked, layer3.1.bn2.num_batches_tracked, layer4.0.bn2.num_batches_tracked, layer3.3.bn3.num_batches_tracked, layer2.0.bn1.num_batches_tracked, layer2.3.bn3.num_batches_tracked, layer4.0.bn3.num_batches_tracked, bn1.num_batches_tracked, layer3.4.bn2.num_batches_tracked, layer4.1.bn2.num_batches_tracked, layer3.1.bn3.num_batches_tracked, layer1.0.bn1.num_batches_tracked, layer2.2.bn3.num_batches_tracked, layer3.1.bn1.num_batches_tracked, layer1.0.bn3.num_batches_tracked, layer3.5.bn2.num_batches_tracked
Hi, I found the above file is lost, where can I get it?
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