Hi thanks for your amazing work, supposing I have 4 calibrated cameras, could I use a trained model from the campus dataset into a different scene, or should I rather retrain the model with different voxel space size and calibration parameters?

Thank you for the amazing work! Do you have a demo script available for qualitative testing? Thanks

I had this error in replicating your code.
Traceback (most recent call last):
File "D:\anaconda3\envs\PRGN\lib\site-packages\mmcv\utils\registry.py", line 69, in build_from_cfg
return obj_cls(**args)
File "E:\code\multiview_pose-main\multiview_pose\models\detectors\multiview_pose.py", line 13, in init
super(GraphBasedModel, self).init(*args, **kwargs)
TypeError: init() got an unexpected keyword argument 'keypoint_head'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "tools/train.py", line 206, in
main()
File "tools/train.py", line 180, in main
model = build_posenet(cfg.model)
File "D:\anaconda3\envs\PRGN\lib\site-packages\mmpose\models\builder.py", line 39, in build_posenet
return POSENETS.build(cfg)
File "D:\anaconda3\envs\PRGN\lib\site-packages\mmcv\utils\registry.py", line 237, in build
return self.build_func(*args, **kwargs, registry=self)
File "D:\anaconda3\envs\PRGN\lib\site-packages\mmcv\cnn\builder.py", line 27, in build_model_from_cfg
return build_from_cfg(cfg, registry, default_args)
File "D:\anaconda3\envs\PRGN\lib\site-packages\mmcv\utils\registry.py", line 72, in build_from_cfg
raise type(e)(f'{obj_cls.name}: {e}')
TypeError: GraphBasedModel: init() got an unexpected keyword argument 'keypoint_head'
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 9732) of binary: D:\anaconda3\envs\PRGN\python.exe
Traceback (most recent call last):
File "D:\anaconda3\envs\PRGN\lib\runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "D:\anaconda3\envs\PRGN\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\distributed\launch.py", line 193, in
main()
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\distributed\launch.py", line 189, in main
launch(args)
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\distributed\launch.py", line 174, in launch
run(args)
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\distributed\run.py", line 755, in run
)(*cmd_args)
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\distributed\launcher\api.py", line 131, in call
return launch_agent(self._config, self._entrypoint, list(args))
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\distributed\launcher\api.py", line 247, in launch_agent
failures=result.failures,
torch.distributed.elastic.multiprocessing.errors.ChildFailedError:

tools/train.py FAILED

I changed the code in the GraphBasedModel class to look like this：
@POSENETS.register_module()
class GraphBasedModel(DetectAndRegress):
def init(self, num_joints, pose_refiner, test_with_refine=True, freeze_keypoint_head=True,keypoint_head=None,
*args, **kwargs):
super(GraphBasedModel, self).init(*args, **kwargs)
self.num_joints = num_joints
if pose_refiner is not None:
self.pose_refiner = GCNS.build(pose_refiner)
else:
self.pose_refiner = None
self.test_with_refine = test_with_refine
self.freeze_keypoint_head = freeze_keypoint_head
self.keypoint_head = keypoint_head
There was this mistake again：
Traceback (most recent call last):
File "tools/train.py", line 206, in
main()
File "tools/train.py", line 202, in main
meta=meta)
File "D:\anaconda3\envs\PRGN\lib\site-packages\mmpose\apis\train.py", line 213, in train_model
runner.run(data_loaders, cfg.workflow, cfg.total_epochs)
File "D:\anaconda3\envs\PRGN\lib\site-packages\mmcv\runner\epoch_based_runner.py", line 136, in run
epoch_runner(data_loaders[i], **kwargs)
File "D:\anaconda3\envs\PRGN\lib\site-packages\mmcv\runner\epoch_based_runner.py", line 53, in train
self.run_iter(data_batch, train_mode=True, **kwargs)
File "D:\anaconda3\envs\PRGN\lib\site-packages\mmcv\runner\epoch_based_runner.py", line 32, in run_iter
**kwargs)
File "D:\anaconda3\envs\PRGN\lib\site-packages\mmcv\parallel\data_parallel.py", line 77, in train_step
return self.module.train_step(*inputs[0], **kwargs[0])
File "D:\anaconda3\envs\PRGN\lib\site-packages\mmpose\models\detectors\multiview_pose.py", line 273, in train_step
losses = self.forward(**data_batch)
File "E:\code\multiview_pose-main\multiview_pose\models\detectors\multiview_pose.py", line 58, in forward
targets_3d, input_heatmaps, **kwargs)
File "E:\code\multiview_pose-main\multiview_pose\models\detectors\multiview_pose.py", line 79, in forward_train
feature_maps.append(self.predict_heatmap(img_)[0])
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\nn\modules\module.py", line 1208, in getattr
type(self).name, name))
AttributeError: 'GraphBasedModel' object has no attribute 'predict_heatmap'
ERROR:torch.distributed.elastic.multiprocessing.api:failed (exitcode: 1) local_rank: 0 (pid: 19796) of binary: D:\anaconda3\envs\PRGN\python.exe
Traceback (most recent call last):
File "D:\anaconda3\envs\PRGN\lib\runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "D:\anaconda3\envs\PRGN\lib\runpy.py", line 85, in _run_code
exec(code, run_globals)
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\distributed\launch.py", line 193, in
main()
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\distributed\launch.py", line 189, in main
launch(args)
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\distributed\launch.py", line 174, in launch
run(args)
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\distributed\run.py", line 755, in run
)(*cmd_args)
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\distributed\launcher\api.py", line 131, in call
return launch_agent(self._config, self._entrypoint, list(args))
File "D:\anaconda3\envs\PRGN\lib\site-packages\torch\distributed\launcher\api.py", line 247, in launch_agent
failures=result.failures,
torch.distributed.elastic.multiprocessing.errors.ChildFailedError: