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Processing: 0 : ./data_obj_parent_directory\013FHA7K\013FHA7K_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 "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\predict_utils.py", line 97, in predict
pred_result = self.chl_pipeline(scan_path)
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\inference_pipelines\inference_pipeline_tgn.py", line 46, in call
first_results = self.get_first_module_results(input_cuda_feats, self.first_module)
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\inference_pipelines\inference_pipeline_tgn.py", line 170, in get_first_module_results
output = base_model([points])
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\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 "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\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:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\sklearn\base.py", line 1151, in wrapper
return fit_method(estimator, *args, **kwargs)
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\sklearn\cluster_dbscan.py", line 370, in fit
X = self._validate_data(X, accept_sparse="csr")
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\sklearn\base.py", line 604, in _validate_data
out = check_array(X, input_name="X", **check_params)
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\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.
Traceback (most recent call last):
File "start_inference.py", line 39, in
pred_obj.process(stl_path_ls[i], os.path.join(args.save_path, os.path.basename(stl_path_ls[i]).replace(".obj", ".json")))
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\predict_utils.py", line 136, in process
labels, instances, jaw = self.predict([input_path])
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\predict_utils.py", line 97, in predict
pred_result = self.chl_pipeline(scan_path)
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\inference_pipelines\inference_pipeline_tgn.py", line 46, in call
first_results = self.get_first_module_results(input_cuda_feats, self.first_module)
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\inference_pipelines\inference_pipeline_tgn.py", line 170, in get_first_module_results
output = base_model([points])
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\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 "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\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:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\sklearn\base.py", line 1151, in wrapper
return fit_method(estimator, *args, **kwargs)
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\sklearn\cluster_dbscan.py", line 370, in fit
X = self._validate_data(X, accept_sparse="csr")
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\sklearn\base.py", line 604, in _validate_data
out = check_array(X, input_name="X", **check_params)
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\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
I have followed all the steps but may be I'm missing something. Anyone could help me?
The text was updated successfully, but these errors were encountered:
Hello! I'm using the following command to obtain inference results:
but I'm getting the following error:
Processing: 0 : ./data_obj_parent_directory\013FHA7K\013FHA7K_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 "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\predict_utils.py", line 97, in predict
pred_result = self.chl_pipeline(scan_path)
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\inference_pipelines\inference_pipeline_tgn.py", line 46, in call
first_results = self.get_first_module_results(input_cuda_feats, self.first_module)
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\inference_pipelines\inference_pipeline_tgn.py", line 170, in get_first_module_results
output = base_model([points])
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\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 "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\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:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\sklearn\base.py", line 1151, in wrapper
return fit_method(estimator, *args, **kwargs)
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\sklearn\cluster_dbscan.py", line 370, in fit
X = self._validate_data(X, accept_sparse="csr")
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\sklearn\base.py", line 604, in _validate_data
out = check_array(X, input_name="X", **check_params)
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\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.
Traceback (most recent call last):
File "start_inference.py", line 39, in
pred_obj.process(stl_path_ls[i], os.path.join(args.save_path, os.path.basename(stl_path_ls[i]).replace(".obj", ".json")))
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\predict_utils.py", line 136, in process
labels, instances, jaw = self.predict([input_path])
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\predict_utils.py", line 97, in predict
pred_result = self.chl_pipeline(scan_path)
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\inference_pipelines\inference_pipeline_tgn.py", line 46, in call
first_results = self.get_first_module_results(input_cuda_feats, self.first_module)
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\inference_pipelines\inference_pipeline_tgn.py", line 170, in get_first_module_results
output = base_model([points])
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\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 "C:\Users\mrcabello\Documents\Research\code\ToothGroupNetwork\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:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\sklearn\base.py", line 1151, in wrapper
return fit_method(estimator, *args, **kwargs)
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\sklearn\cluster_dbscan.py", line 370, in fit
X = self._validate_data(X, accept_sparse="csr")
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\lib\site-packages\sklearn\base.py", line 604, in _validate_data
out = check_array(X, input_name="X", **check_params)
File "C:\Users\mrcabello\Miniconda3\envs\tooth_seg\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
I have followed all the steps but may be I'm missing something. Anyone could help me?
The text was updated successfully, but these errors were encountered: