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args.input_dir_path= H:\teeth\3DTeethSeg\ToothGroupNetwork-main\in_obj
args.split_txt_path= test_id.txt
stl_path_ls= ['H:\teeth\3DTeethSeg\ToothGroupNetwork-main\in_obj\00OMSZGW\00OMSZGW_lower.obj', 'H:\teeth\3DTeethSeg\ToothGroupNetwork-main\in_obj\00OMSZGW\00OMSZGW_upper.obj']
Processing: 0 : H:\teeth\3DTeethSeg\ToothGroupNetwork-main\in_obj\00OMSZGW\00OMSZGW_lower.obj
Found array with 0 sample(s) (shape=(0, 3)) while a minimum of 1 is required by DBSCAN.
Traceback (most recent call last):
File "h:\teeth\3DTeethSeg\ToothGroupNetwork-main\predict_utils.py", line 97, in predict
pred_result = self.chl_pipeline(scan_path)
File "h:\teeth\3DTeethSeg\ToothGroupNetwork-main\inference_pipelines\inference_pipeline_tgn.py", line 46, in call
first_results = self.get_first_module_results(input_cuda_feats, self.first_module)
File "h:\teeth\3DTeethSeg\ToothGroupNetwork-main\inference_pipelines\inference_pipeline_tgn.py", line 170, in get_first_module_results
output = base_model([points])
File "C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "h:\teeth\3DTeethSeg\ToothGroupNetwork-main\models\modules\grouping_network_module.py", line 65, in forward
fg_points_labels_ls = ou.get_clustering_labels(b_moved_points, whole_cls_1)
File "h:\teeth\3DTeethSeg\ToothGroupNetwork-main\ops_utils.py", line 98, in get_clustering_labels
clustering = DBSCAN(eps=0.03, min_samples=30).fit(moved_points[super_point_cond, :], 3)
File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\base.py", line 1151, in wrapper
return fit_method(estimator, *args, **kwargs)
File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\cluster_dbscan.py", line 370, in fit
X = self._validate_data(X, accept_sparse="csr")
File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\base.py", line 604, in _validate_data
out = check_array(X, input_name="X", **check_params)
File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\validation.py", line 969, in check_array
raise ValueError(
ValueError: Found array with 0 sample(s) (shape=(0, 3)) while a minimum of 1 is required by DBSCAN.
The text was updated successfully, but these errors were encountered:
更换一下库的版本就好了
在 2024-07-15 16:57:24,"hongpengxu779" ***@***.***> 写道:
我遇到了同样的问题,调整 eps min_samples不起作用!
您好,你们解决这个问题了吗?
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You are receiving this because you commented.Message ID: ***@***.***>
args.input_dir_path= H:\teeth\3DTeethSeg\ToothGroupNetwork-main\in_obj
args.split_txt_path= test_id.txt
stl_path_ls= ['H:\teeth\3DTeethSeg\ToothGroupNetwork-main\in_obj\00OMSZGW\00OMSZGW_lower.obj', 'H:\teeth\3DTeethSeg\ToothGroupNetwork-main\in_obj\00OMSZGW\00OMSZGW_upper.obj']
Processing: 0 : H:\teeth\3DTeethSeg\ToothGroupNetwork-main\in_obj\00OMSZGW\00OMSZGW_lower.obj
Found array with 0 sample(s) (shape=(0, 3)) while a minimum of 1 is required by DBSCAN.
Traceback (most recent call last):
File "h:\teeth\3DTeethSeg\ToothGroupNetwork-main\predict_utils.py", line 97, in predict
pred_result = self.chl_pipeline(scan_path)
File "h:\teeth\3DTeethSeg\ToothGroupNetwork-main\inference_pipelines\inference_pipeline_tgn.py", line 46, in call
first_results = self.get_first_module_results(input_cuda_feats, self.first_module)
File "h:\teeth\3DTeethSeg\ToothGroupNetwork-main\inference_pipelines\inference_pipeline_tgn.py", line 170, in get_first_module_results
output = base_model([points])
File "C:\ProgramData\Anaconda3\lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "h:\teeth\3DTeethSeg\ToothGroupNetwork-main\models\modules\grouping_network_module.py", line 65, in forward
fg_points_labels_ls = ou.get_clustering_labels(b_moved_points, whole_cls_1)
File "h:\teeth\3DTeethSeg\ToothGroupNetwork-main\ops_utils.py", line 98, in get_clustering_labels
clustering = DBSCAN(eps=0.03, min_samples=30).fit(moved_points[super_point_cond, :], 3)
File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\base.py", line 1151, in wrapper
return fit_method(estimator, *args, **kwargs)
File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\cluster_dbscan.py", line 370, in fit
X = self._validate_data(X, accept_sparse="csr")
File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\base.py", line 604, in _validate_data
out = check_array(X, input_name="X", **check_params)
File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\validation.py", line 969, in check_array
raise ValueError(
ValueError: Found array with 0 sample(s) (shape=(0, 3)) while a minimum of 1 is required by DBSCAN.
The text was updated successfully, but these errors were encountered: