fns, kwargs = determine_postprocessing(merged_output_folder, labelstr, plans_manager.plans, dataset_json, 8, keep_postprocessed_files=True) save_pickle((fns, kwargs), join(trained_model_folder, 'postprocessing.pkl')) fns, kwargs = load_pickle(join(trained_model_folder, 'postprocessing.pkl...
This is the regular nnUNet but with three new features: 1 - Training with cyclic learning rate, producing checkpoints from different convergent minima. 2 - an ensemble of the different checkpoints is used to determine uncertainty of each fold. 3 - On inference prediction is made using the lo...
find_best_configuration_entry_point" nnUNetv2_determine_postprocessing = "nnunetv2.postprocessing.remove_connected_components:entry_point_determine_postprocessing_folder" nnUNetv2_apply_postprocessing = "nnunetv2.postprocessing.remove_connected_components:entry_point_apply_postprocessing" nnUNetv2_...
nnU-Net trains all U-Net configurations in a 5-fold cross-validation. This enables nnU-Net to determine the postprocessing and ensembling (see next step) on the training dataset. Per default, all U-Net configurations need to be run on a given dataset. There are, however situations in whic...
nnU-Net trains all U-Net configurations in a 5-fold cross-validation. This enables nnU-Net to determine the postprocessing and ensembling (see next step) on the training dataset. Per default, all U-Net configurations need to be run on a given dataset. There are, however situations in whic...
MicroPhion: 1、后处理最主要是计算最大联通区域 2、apply_postprocessing这个里面是调用后处理算法的代码 3、determine_postprocessing将后处理算法和对应的参数放在pp_fns和pp_fn_kwargs中 4、apply_postprocessing_to_folder采用多… 赞同 2 添加评论 ...
(configuration_name) #2.0利用plans_manager构建网络network,restore network num_input_channels = determine_num_input_channels(plans_manager, configuration_manager, dataset_json) trainer_class = recursive_find_python_class(join(nnunetv2.__path__[0], "training", "nnUNetTrainer"), trainer_name, '...
This enables nnU-Net to determine the postprocessing and ensembling (see next step) on the training dataset. Per default, all U-Net configurations need to be run on a given dataset. There are, however situations in which only some configurations (and maybe even without running the cross-...
nnU-Net trains all U-Net configurations in a 5-fold cross-validation. This enables nnU-Net to determine the postprocessing and ensembling (see next step) on the training dataset. Per default, all U-Net configurations need to be run on a given dataset. There are, however situations in whic...
= nnunet.inference.pretrained_models.download_pretrained_model:download_by_url','nnUNet_determine_postprocessing = nnunet.postprocessing.consolidate_postprocessing_simple:main','nnUNet_export_model_to_zip = nnunet.inference.pretrained_models.collect_pretrained_models:export_entry_point','nnUNet_install...