Auto Segmentation error in 'brats_segmentation_v0.3.3' model

[ulphypro]

Describe the bug
[2022-11-22 10:24:37,281] [19036] [MainThread] [ERROR] (uvicorn.error:119) - Traceback (most recent call last):
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\site-packages\starlette\routing.py", line 635, in lifespan
async with self.lifespan_context(app):
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\site-packages\starlette\routing.py", line 530, in aenter
await self.router.startup()
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\site-packages\starlette\routing.py", line 612, in startup
await handler()
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\site-packages\monailabel\app.py", line 106, in startup_event
instance = app_instance()
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\site-packages\monailabel\interfaces\utils\app.py", line 51, in app_instance
app = c(app_dir=app_dir, studies=studies, conf=conf)
File "C:\Users\AA\apps\monaibundle\main.py", line 90, in init
super().init(
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\site-packages\monailabel\interfaces\app.py", line 96, in init
self.trainers = self.init_trainers() if settings.MONAI_LABEL_TASKS_TRAIN else {}
File "C:\Users\AA\apps\monaibundle\main.py", line 116, in init_trainers
t = BundleTrainTask(b, self.conf)
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\site-packages\monailabel\tasks\train\bundle.py", line 83, in init
self.bundle_config.read_config(self.bundle_config_path)
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\site-packages\monai\bundle\config_parser.py", line 300, in read_config
content.update(self.load_config_files(f, **kwargs))
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\site-packages\monai\bundle\config_parser.py", line 403, in load_config_files
for k, v in (cls.load_config_file(i, **kwargs)).items():
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\site-packages\monai\bundle\config_parser.py", line 382, in load_config_file
return json.load(f, **kwargs)
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\json_init.py", line 293, in load
return loads(fp.read(),
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\json_init.py", line 346, in loads
return _default_decoder.decode(s)
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\json\decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
File "C:\Users\AA\AppData\Local\Programs\Python\Python39\lib\json\decoder.py", line 353, in raw_decode
obj, end = self.scan_once(s, idx)
json.decoder.JSONDecodeError: Expecting ',' delimiter: line 63 column 43 (char 1947)

[2022-11-22 10:24:37,282] [19036] [MainThread] [ERROR] (uvicorn.error:56) - Application startup failed. Exiting.

To Reproduce
Steps to reproduce the behavior:

1. 'in_channel' value edited 4 into 1 and added 'ensure_channel_first": ture in inference.json

   • edited inference.json code
     "target": "SegResNet",
     "blocks_down": [
     1,
     2,
     2,
     4
     ],
     "blocks_up": [
     1,
     1,
     1
     ],
     "init_filters": 16,
     "in_channels": 1,
     "out_channels": 3,
     "dropout_prob": 0.2
     },
     "network": "$@network_def.to(@device)",
     "preprocessing": {
     "target": "Compose",
     "transforms": [
     {
     "target": "LoadImaged",
     "keys": "image",
     "ensure_channel_first": true
     },

2. 'in_channel' value edited 4 into 1 and added 'ensure_channel_first": ture in train.json

   • edited train.json code
     "target": "SegResNet",
     "blocks_down": [
     1,
     2,
     2,
     4
     ],
     "blocks_up": [
     1,
     1,
     1
     ],
     "init_filters": 16,
     "in_channels": 1,
     "out_channels": 3,
     "dropout_prob": 0.2
     },
     .
     .
     .
     "train": {
     "preprocessing_transforms": [
     {
     "target": "LoadImaged",
     "keys": [
     "image",
     "label",
     "ensure_channel_first": true
     ]
     },

3. '("inputs" :) num_channel' value edits 4 into 1 train.json

   • edited metadata.json code
     "intended_use": "This is an example, not to be used for diagnostic purposes",
     "references": [
     "Myronenko, Andriy. '3D MRI brain tumor segmentation using autoencoder regularization.' International MICCAI Brainlesion Workshop. Springer, Cham, 2018. https://arxiv.org/abs/1810.11654"
     ],
     "network_data_format": {
     "inputs": {
     "image": {
     "type": "image",
     "format": "magnitude",
     "modality": "MR",
     "num_channels": 1,
     "spatial_shape": [
     "8n",
     "8n",
     "8*n"
     ],

Expected behavior
I can expect result when I press 'run' button in Auto Segmentation option, after I edited and added inference.json, train.josn and metadata.json.

Screenshots
But I can't extract brain tumor as following figure.

Environment

Printing MONAI config...

MONAI version: 1.0.1
Numpy version: 1.23.4
Pytorch version: 1.12.1+cu113
MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False
MONAI rev id: 8271a193229fe4437026185e218d5b06f7c8ce69
MONAI file: C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monai_init_.py

Optional dependencies:
Pytorch Ignite version: 0.4.10
Nibabel version: 4.0.2
scikit-image version: 0.19.3
Pillow version: 9.3.0
Tensorboard version: 2.10.1
gdown version: 4.5.3
TorchVision version: 0.13.1+cu113
tqdm version: 4.64.1
lmdb version: 1.3.0
psutil version: 5.9.4
pandas version: 1.5.1
einops version: 0.6.0
transformers version: 4.24.0
mlflow version: 2.0.1
pynrrd version: 0.4.3

For details about installing the optional dependencies, please visit:
https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies

================================
Printing system config...

System: Windows
Win32 version: ('10', '10.0.22000', 'SP0', 'Multiprocessor Free')
Win32 edition: Core
Platform: Windows-10-10.0.22000-SP0
Processor: AMD64 Family 25 Model 80 Stepping 0, AuthenticAMD
Machine: AMD64
Python version: 3.9.13
Process name: python.exe
Command: ['C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\python.exe', '-c', 'import monai; monai.config.print_debug_info()']
Open files: [popenfile(path='C:\Program Files\WindowsApps\Microsoft.LanguageExperiencePackko-KR_22000.29.134.0_neutral__8wekyb3d8bbwe\Windows\System32\ko-KR\39386f74d1967f5c37a5b4171f81c8f3\kernel32.dll.mui', fd=-1), popenfile(path='C:\Program Files\WindowsApps\Microsoft.LanguageExperiencePackko-KR_22000.29.134.0_neutral__8wekyb3d8bbwe\Windows\System32\ko-KR\fe441ef3ed396a241e46f9f354057863\tzres.dll.mui', fd=-1), popenfile(path='C:\Program Files\WindowsApps\Microsoft.LanguageExperiencePackko-KR_22000.29.134.0_neutral__8wekyb3d8bbwe\Windows\System32\ko-KR\a7c1941e6709c10ab525083b61805316\KernelBase.dll.mui', fd=-1)]
Num physical CPUs: 8
Num logical CPUs: 16
Num usable CPUs: 16
CPU usage (%): [10.3, 9.4, 6.9, 3.8, 4.4, 0.6, 1.9, 2.2, 6.6, 15.2, 7.8, 3.2, 2.2, 0.9, 6.0, 41.1]
CPU freq. (MHz): 3301
Load avg. in last 1, 5, 15 mins (%): [0.0, 0.0, 0.0]
Disk usage (%): 60.3
Avg. sensor temp. (Celsius): UNKNOWN for given OS
Total physical memory (GB): 15.4
Available memory (GB): 7.1
Used memory (GB): 8.3

================================
Printing GPU config...

Num GPUs: 1
Has CUDA: True
CUDA version: 11.3
cuDNN enabled: True
cuDNN version: 8302
Current device: 0
Library compiled for CUDA architectures: ['sm_37', 'sm_50', 'sm_60', 'sm_61', 'sm_70', 'sm_75', 'sm_80', 'sm_86', 'compute_37']
GPU 0 Name: NVIDIA GeForce RTX 3070 Laptop GPU
GPU 0 Is integrated: False
GPU 0 Is multi GPU board: False
GPU 0 Multi processor count: 40
GPU 0 Total memory (GB): 8.0
GPU 0 CUDA capability (maj.min): 8.6

[yiheng-wang-nv]

Hi, the error is json.decoder.JSONDecodeError: Expecting ',' delimiter: line 63 column 43 (char 1947), could you please double check if line 63 misses a comma?

[ulphypro]

Hello, @yiheng-wang-nv
Thank you for answering my question

There is no problem regarding 63 line in decorder.py that error showed.

Is it correct to modify it as follows??
In inference.json code
"in_channels": 1 ---->edit
"ensure_channel_first: true" ------------->add

In train.json code
In inference.json code
"in_channels": 1 ---->edit
"ensure_channel_first: true" ------------->add

In metadata.json
"num_channels": 1 ------>edit

[yiheng-wang-nv]

Hi @ulphypro , I suspect here "line 63" is for the json file that produced the error, not for decoder.py. I cannot find an error in the code you attached, but may need to see the whole json files to double check it.

[ulphypro]

Thank you. @yiheng-wang-nv

I edited total 3 files: inference.json, train.json and metadata.json included in 'brats_mri_segmentation_v0.3.3'.

There is no problem in corresponding codes.

I don't know why it occurs the error that is '[2022-11-22 15:37:19,967] [5628] [MainThread] [ERROR] (uvicorn.error:56) - Application startup failed. Exiting.'.

Corresponding codes are as following : edited inference.json, train.json and metadata.json.

[ulphypro]

Edited inference.json code included in brats_mri_segmentation_v0.3.3
{
"imports": [
"$import glob",
"$import os"
],
"bundle_root": "/workspace/brats_mri_segmentation",
"ckpt_dir": "$@bundle_root + '/models'",
"output_dir": "$@bundle_root + '/eval'",
"data_list_file_path": "$@bundle_root + '/configs/datalist.json'",
"data_file_base_dir": "/workspace/data/medical/brats2018challenge",
"test_datalist": "$monai.data.load_decathlon_datalist(@data_list_file_path, data_list_key='testing', base_dir=@data_file_base_dir)",
"device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')",
"amp": true,
"network_def": {
"target": "SegResNet",
"blocks_down": [
1,
2,
2,
4
],
"blocks_up": [
1,
1,
1
],
"init_filters": 16,
"in_channels": 1,
"out_channels": 3,
"dropout_prob": 0.2
},
"network": "$@network_def.to(@device)",
"preprocessing": {
"target": "Compose",
"transforms": [
{
"target": "LoadImaged",
"keys": "image",
"ensure_channel_first": true
},
{
"target": "NormalizeIntensityd",
"keys": "image",
"nonzero": true,
"channel_wise": true
}
]
},
"dataset": {
"target": "Dataset",
"data": "@test_datalist",
"transform": "@preprocessing"
},
"dataloader": {
"target": "DataLoader",
"dataset": "@dataset",
"batch_size": 1,
"shuffle": true,
"num_workers": 4
},
"inferer": {
"target": "SlidingWindowInferer",
"roi_size": [
240,
240,
160
],
"sw_batch_size": 1,
"overlap": 0.5
},
"postprocessing": {
"target": "Compose",
"transforms": [
{
"target": "Activationsd",
"keys": "pred",
"sigmoid": true
},
{
"target": "Invertd",
"keys": "pred",
"transform": "@preprocessing",
"orig_keys": "image",
"meta_keys": "pred_meta_dict",
"nearest_interp": false,
"to_tensor": true
},
{
"target": "AsDiscreted",
"keys": "pred",
"threshold": 0.5
},
{
"target": "SaveImaged",
"keys": "pred",
"meta_keys": "pred_meta_dict",
"output_dir": "@output_dir"
}
]
},
"handlers": [
{
"target": "CheckpointLoader",
"load_path": "$@bundle_root + '/models/model.pt'",
"load_dict": {
"model": "@network"
}
},
{
"target": "StatsHandler",
"iteration_log": false
}
],
"evaluator": {
"target": "SupervisedEvaluator",
"device": "@device",
"val_data_loader": "@dataloader",
"network": "@network",
"inferer": "@inferer",
"postprocessing": "@Postprocessing",
"val_handlers": "@handlers",
"amp": true
},
"evaluating": [
"$setattr(torch.backends.cudnn, 'benchmark', True)",
"$@evaluator.run()"
]
}

[ulphypro]

Edited train.json code included in brats_mri_segmentation_v0.3.3

{
"imports": [
"$import glob",
"$import os"
],
"bundle_root": "/workspace/brats_mri_segmentation",
"ckpt_dir": "$@bundle_root + '/models'",
"output_dir": "$@bundle_root + '/eval'",
"data_list_file_path": "$@bundle_root + '/configs/datalist.json'",
"data_file_base_dir": "/workspace/data/medical/brats2018challenge",
"train_datalist": "$monai.data.load_decathlon_datalist(@data_list_file_path, data_list_key='training', base_dir=@data_file_base_dir)",
"val_datalist": "$monai.data.load_decathlon_datalist(@data_list_file_path, data_list_key='validation', base_dir=@data_file_base_dir)",
"device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')",
"epochs": 300,
"val_interval": 1,
"learning_rate": 0.0001,
"amp": true,
"network_def": {
"target": "SegResNet",
"blocks_down": [
1,
2,
2,
4
],
"blocks_up": [
1,
1,
1
],
"init_filters": 16,
"in_channels": 1,
"out_channels": 3,
"dropout_prob": 0.2
},
"network": "$@network_def.to(@device)",
"loss": {
"target": "DiceLoss",
"smooth_nr": 0,
"smooth_dr": 1e-05,
"squared_pred": true,
"to_onehot_y": false,
"sigmoid": true
},
"optimizer": {
"target": "torch.optim.Adam",
"params": "$@network.parameters()",
"lr": "@learning_rate",
"weight_decay": 1e-05
},
"lr_scheduler": {
"target": "torch.optim.lr_scheduler.CosineAnnealingLR",
"optimizer": "@optimizer",
"T_max": "@epochs"
},
"train": {
"preprocessing_transforms": [
{
"target": "LoadImaged",
"keys": [
"image",
"label",
"ensure_channel_first": true
]
},
{
"target": "ConvertToMultiChannelBasedOnBratsClassesd",
"keys": "label"
},
{
"target": "NormalizeIntensityd",
"keys": "image",
"nonzero": true,
"channel_wise": true
}
],
"random_transforms": [
{
"target": "RandSpatialCropd",
"keys": [
"image",
"label"
],
"roi_size": [
224,
224,
144
],
"random_size": false
},
{
"target": "RandFlipd",
"keys": [
"image",
"label"
],
"prob": 0.5,
"spatial_axis": 0
},
{
"target": "RandFlipd",
"keys": [
"image",
"label"
],
"prob": 0.5,
"spatial_axis": 1
},
{
"target": "RandFlipd",
"keys": [
"image",
"label"
],
"prob": 0.5,
"spatial_axis": 2
},
{
"target": "RandScaleIntensityd",
"keys": "image",
"factors": 0.1,
"prob": 1.0
},
{
"target": "RandShiftIntensityd",
"keys": "image",
"offsets": 0.1,
"prob": 1.0
}
],
"preprocessing": {
"target": "Compose",
"transforms": "$@train#preprocessing_transforms + @train#random_transforms"
},
"dataset": {
"target": "Dataset",
"data": "@train_datalist",
"transform": "@train#preprocessing"
},
"dataloader": {
"target": "DataLoader",
"dataset": "@train#dataset",
"batch_size": 1,
"shuffle": true,
"num_workers": 4
},
"inferer": {
"target": "SimpleInferer"
},
"postprocessing": {
"target": "Compose",
"transforms": [
{
"target": "Activationsd",
"keys": "pred",
"sigmoid": true
},
{
"target": "AsDiscreted",
"keys": "pred",
"threshold": 0.5
}
]
},
"handlers": [
{
"target": "LrScheduleHandler",
"lr_scheduler": "@lr_scheduler",
"print_lr": true
},
{
"target": "ValidationHandler",
"validator": "@Validate#evaluator",
"epoch_level": true,
"interval": "@val_interval"
},
{
"target": "StatsHandler",
"tag_name": "train_loss",
"output_transform": "$monai.handlers.from_engine(['loss'], first=True)"
},
{
"target": "TensorBoardStatsHandler",
"log_dir": "@output_dir",
"tag_name": "train_loss",
"output_transform": "$monai.handlers.from_engine(['loss'], first=True)"
}
],
"key_metric": {
"train_mean_dice": {
"target": "MeanDice",
"include_background": true,
"output_transform": "$monai.handlers.from_engine(['pred', 'label'])"
}
},
"trainer": {
"target": "SupervisedTrainer",
"max_epochs": "@epochs",
"device": "@device",
"train_data_loader": "@train#dataloader",
"network": "@network",
"loss_function": "@loss",
"optimizer": "@optimizer",
"inferer": "@train#inferer",
"postprocessing": "@train#postprocessing",
"key_train_metric": "@train#key_metric",
"train_handlers": "@train#handlers",
"amp": "@amp"
}
},
"validate": {
"preprocessing": {
"target": "Compose",
"transforms": "$@train#preprocessing_transforms"
},
"dataset": {
"target": "Dataset",
"data": "@val_datalist",
"transform": "@Validate#preprocessing"
},
"dataloader": {
"target": "DataLoader",
"dataset": "@Validate#dataset",
"batch_size": 1,
"shuffle": false,
"num_workers": 4
},
"inferer": {
"target": "SlidingWindowInferer",
"roi_size": [
240,
240,
160
],
"sw_batch_size": 1,
"overlap": 0.5
},
"postprocessing": {
"target": "Compose",
"transforms": [
{
"target": "Activationsd",
"keys": "pred",
"sigmoid": true
},
{
"target": "AsDiscreted",
"keys": "pred",
"threshold": 0.5
},
{
"target": "SplitDimd",
"keys": [
"pred",
"label"
],
"output_postfixes": [
"tc",
"wt",
"et"
]
}
]
},
"handlers": [
{
"target": "StatsHandler",
"iteration_log": false
},
{
"target": "TensorBoardStatsHandler",
"log_dir": "@output_dir",
"iteration_log": false
},
{
"target": "CheckpointSaver",
"save_dir": "@ckpt_dir",
"save_dict": {
"model": "@network"
},
"save_key_metric": true,
"key_metric_filename": "model.pt"
}
],
"key_metric": {
"val_mean_dice": {
"target": "MeanDice",
"include_background": true,
"output_transform": "$monai.handlers.from_engine(['pred', 'label'])"
}
},
"additional_metrics": {
"val_mean_dice_tc": {
"target": "MeanDice",
"include_background": true,
"output_transform": "$monai.handlers.from_engine(['pred_tc', 'label_tc'])"
},
"val_mean_dice_wt": {
"target": "MeanDice",
"include_background": true,
"output_transform": "$monai.handlers.from_engine(['pred_wt', 'label_wt'])"
},
"val_mean_dice_et": {
"target": "MeanDice",
"include_background": true,
"output_transform": "$monai.handlers.from_engine(['pred_et', 'label_et'])"
}
},
"evaluator": {
"target": "SupervisedEvaluator",
"device": "@device",
"val_data_loader": "@Validate#dataloader",
"network": "@network",
"inferer": "@Validate#inferer",
"postprocessing": "@Validate#postprocessing",
"key_val_metric": "@Validate#key_metric",
"additional_metrics": "@Validate#additional_metrics",
"val_handlers": "@Validate#handlers",
"amp": "@amp"
}
},
"training": [
"$monai.utils.set_determinism(seed=123)",
"$setattr(torch.backends.cudnn, 'benchmark', True)",
"$@train#trainer.run()"
]
}

[ulphypro]

Edited train.json code included in brats_mri_segmentation_v0.3.3

{
"schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
"version": "0.3.3",
"changelog": {
"0.3.3": "update to use monai 1.0.1",
"0.3.2": "enhance readme on commands example",
"0.3.1": "fix license Copyright error",
"0.3.0": "update license files",
"0.2.1": "fix network_data_format error",
"0.2.0": "unify naming",
"0.1.1": "update for MetaTensor",
"0.1.0": "complete the model package"
},
"monai_version": "1.0.1",
"pytorch_version": "1.13.0",
"numpy_version": "1.22.4",
"optional_packages_version": {
"nibabel": "4.0.1",
"pytorch-ignite": "0.4.9",
"scikit-learn": "1.1.3",
"tensorboard": "2.10.1"
},
"task": "Multimodal Brain Tumor segmentation",
"description": "A pre-trained model for volumetric (3D) segmentation of brain tumor subregions from multimodal MRIs based on BraTS 2018 data",
"authors": "MONAI team",
"copyright": "Copyright (c) MONAI Consortium",
"data_source": "https://www.med.upenn.edu/sbia/brats2018/data.html",
"data_type": "nibabel",
"image_classes": "4 channel data, T1c, T1, T2, FLAIR at 1x1x1 mm",
"label_classes": "3 channel data, channel 0 for Tumor core, channel 1 for Whole tumor, channel 2 for Enhancing tumor",
"pred_classes": "3 channels data, same as label_classes",
"eval_metrics": {
"val_mean_dice": 0.8518,
"val_mean_dice_tc": 0.8559,
"val_mean_dice_wt": 0.9026,
"val_mean_dice_et": 0.7905
},
"intended_use": "This is an example, not to be used for diagnostic purposes",
"references": [
"Myronenko, Andriy. '3D MRI brain tumor segmentation using autoencoder regularization.' International MICCAI Brainlesion Workshop. Springer, Cham, 2018. https://arxiv.org/abs/1810.11654"
],
"network_data_format": {
"inputs": {
"image": {
"type": "image",
"format": "magnitude",
"modality": "MR",
"num_channels": 1,
"spatial_shape": [
"8n",
"8n",
"8n"
],
"dtype": "float32",
"value_range": [],
"is_patch_data": true,
"channel_def": {
"0": "T1c",
"1": "T1",
"2": "T2",
"3": "FLAIR"
}
}
},
"outputs": {
"pred": {
"type": "image",
"format": "segmentation",
"num_channels": 3,
"spatial_shape": [
"8n",
"8n",
"8n"
],
"dtype": "float32",
"value_range": [
0,
1
],
"is_patch_data": true,
"channel_def": {
"0": "Tumor core",
"1": "Whole tumor",
"2": "Enhancing tumor"
}
}
}
}
}

[ulphypro]

@yiheng-wang-nv I edited only total 6 lines.
nference.json
-"in_channels" : 1
-ensure_channel_first" : true

train.json
-"in_channels" : 1
-ensure_channel_first" : true

metadata.json
-In "inputs" section, "num_channels": 1

[yiheng-wang-nv]

this place is wrong:

"keys": [
"image",
"label",
"ensure_channel_first": true
]

"ensure_channel_first" should not be inside the list of "keys", it is another arg.

[ulphypro]

@yiheng-wang-nv

Someone uploaded as demo video how to edit json files .

Project-MONAI/MONAILabel#1051
https://user-images.githubusercontent.com/11991079/194732741-6d55c171-0eb6-4661-97fc-8fa0004897be.mp4

The person input "ensure_channel_first" inside "keys".

Then, where should I put "ensure_channel_first"?

[yiheng-wang-nv]

            {
                "_target_": "LoadImaged",
                "keys": [
                    "image",
                    "label"
                ],
                "ensure_channel_first": true
            },

[ulphypro]

Thank you for helping me @yiheng-wang-nv

I edited inference.json and train.json code as you let me know.

1. Edited inference.json code
   "preprocessing": {
   "target": "Compose",
   "transforms": [
   {
   "target": "LoadImaged",
   "keys": [
   "image",
   ],
   "ensure_channel_first":true
   },
   {
   "target": "NormalizeIntensityd",
   "keys": "image",
   "nonzero": true,
   "channel_wise": true
   }
   ]
   },

2. Edited train.json code
   "preprocessing_transforms": [
   {
   "target": "LoadImaged",
   "keys": [
   "image",
   "label"
   ],
   "ensure_channel_firts": true
   },
   When I input as following, it occurs bottom error.

[2022-11-22 16:24:42,505] [12688] [MainThread] [ERROR] (uvicorn.error:119) - Traceback (most recent call last):
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\starlette\routing.py", line 635, in lifespan
async with self.lifespan_context(app):
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\starlette\routing.py", line 530, in aenter
await self.router.startup()
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\starlette\routing.py", line 612, in startup
await handler()
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monailabel\app.py", line 106, in startup_event
instance = app_instance()
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monailabel\interfaces\utils\app.py", line 51, in app_instance
app = c(app_dir=app_dir, studies=studies, conf=conf)
File "C:\Users\TRL 3D\apps\monaibundle\main.py", line 90, in init
super().init(
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monailabel\interfaces\app.py", line 95, in init
self.infers = self.init_infers()
File "C:\Users\TRL 3D\apps\monaibundle\main.py", line 105, in init_infers
i = BundleInferTask(b, self.conf)
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monailabel\tasks\infer\bundle.py", line 95, in init
self.bundle_config.read_config(os.path.join(path, "configs", config_paths[0]))
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monai\bundle\config_parser.py", line 300, in read_config
content.update(self.load_config_files(f, **kwargs))
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monai\bundle\config_parser.py", line 403, in load_config_files
for k, v in (cls.load_config_file(i, **kwargs)).items():
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monai\bundle\config_parser.py", line 382, in load_config_file
return json.load(f, **kwargs)
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\json_init.py", line 293, in load
return loads(fp.read(),
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\json_init.py", line 346, in loads
return _default_decoder.decode(s)
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\json\decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\json\decoder.py", line 355, in raw_decode
raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 40 column 16 (char 1182)

[2022-11-22 16:24:42,506] [12688] [MainThread] [ERROR] (uvicorn.error:56) - Application startup failed. Exiting.

[ulphypro]

Dear @yiheng-wang-nv
Sorry for bothering you, but let me know how to perfectly run 'Auto Segmentation' using 'brats_mri_segmentation_v0.3.3'.

[yiheng-wang-nv]

This place in inference config is wrong:

"preprocessing": {
"target": "Compose",
"transforms": [
{
"target": "LoadImaged",
"keys": [
"image",
],
"ensure_channel_first":true
},

the comma after "image" will raise the error, and actually only one key named "image" is used, there is no need to put it into a list.
You can do:

"keys": "image",

or

"keys": ["image"],

[ulphypro]

@yiheng-wang-nv

1. edited inference.json code
   "preprocessing": {
   "target": "Compose",
   "transforms": [
   {
   "target": "LoadImaged",
   "keys": ["image"],
   "ensure_channel_first": true
   },

2. edited train.json code
   "train": {
   "preprocessing_transforms": [
   {
   "target": "LoadImaged",
   "keys": [
   "image",
   "label"
   ],
   "ensure_channel_firt": true
   },

I'm sorry.

The result also occurs same error although I edited json files. :

[2022-11-22 17:52:02,288] [956] [MainThread] [ERROR] (uvicorn.error:119) - Traceback (most recent call last):
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\starlette\routing.py", line 635, in lifespan
async with self.lifespan_context(app):
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\starlette\routing.py", line 530, in aenter
await self.router.startup()
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\starlette\routing.py", line 612, in startup
await handler()
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monailabel\app.py", line 106, in startup_event
instance = app_instance()
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monailabel\interfaces\utils\app.py", line 51, in app_instance
app = c(app_dir=app_dir, studies=studies, conf=conf)
File "C:\Users\TRL 3D\apps\monaibundle\main.py", line 90, in init
super().init(
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monailabel\interfaces\app.py", line 95, in init
self.infers = self.init_infers()
File "C:\Users\TRL 3D\apps\monaibundle\main.py", line 105, in init_infers
i = BundleInferTask(b, self.conf)
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monailabel\tasks\infer\bundle.py", line 95, in init
self.bundle_config.read_config(os.path.join(path, "configs", config_paths[0]))
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monai\bundle\config_parser.py", line 300, in read_config
content.update(self.load_config_files(f, **kwargs))
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monai\bundle\config_parser.py", line 403, in load_config_files
for k, v in (cls.load_config_file(i, **kwargs)).items():
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\site-packages\monai\bundle\config_parser.py", line 382, in load_config_file
return json.load(f, **kwargs)
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\json_init.py", line 293, in load
return loads(fp.read(),
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\json_init.py", line 346, in loads
return _default_decoder.decode(s)
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\json\decoder.py", line 337, in decode
obj, end = self.raw_decode(s, idx=_w(s, 0).end())
File "C:\Users\TRL 3D\AppData\Local\Programs\Python\Python39\lib\json\decoder.py", line 355, in raw_decode
raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 40 column 16 (char 1182)

[2022-11-22 17:52:02,288] [956] [MainThread] [ERROR] (uvicorn.error:56) - Application startup failed. Exiting.