Skip to content

Commit

Permalink
Merge pull request #27 from Project-MONAI/swin_unetr_btcv
Browse files Browse the repository at this point in the history 
add swin_unetr bundle
  • Loading branch information
@Nic-Ma
Nic-Ma authored Jun 2, 2022
2 parents dfb14bd + 8c5ca0d commit 0ded5a4
Show file tree
Hide file tree
Showing 10 changed files with 790 additions and 0 deletions.
77 changes: 77 additions & 0 deletions models/swin_unetr_btcv_segmentation/configs/evaluate.json
View file
Original file line number Diff line number Diff line change
@@ -0,0 +1,77 @@
{
"validate#postprocessing": {
"_target_": "Compose",
"transforms": [
{
"_target_": "Activationsd",
"keys": "pred",
"softmax": true
},
{
"_target_": "Invertd",
"keys": [
"pred",
"label"
],
"transform": "@validate#preprocessing",
"orig_keys": "image",
"meta_key_postfix": "meta_dict",
"nearest_interp": [
false,
true
],
"to_tensor": true
},
{
"_target_": "AsDiscreted",
"keys": [
"pred",
"label"
],
"argmax": [
true,
false
],
"to_onehot": 14
},
{
"_target_": "SaveImaged",
"keys": "pred",
"meta_keys": "pred_meta_dict",
"output_dir": "@output_dir",
"resample": false,
"squeeze_end_dims": true
}
]
},
"validate#handlers": [
{
"_target_": "CheckpointLoader",
"load_path": "$@ckpt_dir + '/model.pt'",
"load_dict": {
"model": "@network"
}
},
{
"_target_": "StatsHandler",
"iteration_log": false
},
{
"_target_": "MetricsSaver",
"save_dir": "@output_dir",
"metrics": [
"val_mean_dice",
"val_acc"
],
"metric_details": [
"val_mean_dice"
],
"batch_transform": "$monai.handlers.from_engine(['image_meta_dict'])",
"summary_ops": "*"
}
],
"evaluating": [
"$setattr(torch.backends.cudnn, 'benchmark', True)",
"$@validate#evaluator.run()"
]
}
141 changes: 141 additions & 0 deletions models/swin_unetr_btcv_segmentation/configs/inference.json
View file
Original file line number Diff line number Diff line change
@@ -0,0 +1,141 @@
{
"imports": [
"$import glob",
"$import os"
],
"bundle_root": "/workspace/MONAI_Bundle/swin_unetr_btcv_segmentation/",
"output_dir": "$@bundle_root + '/eval'",
"dataset_dir": "/dataset/dataset0",
"datalist": "$list(sorted(glob.glob(@dataset_dir + '/imagesTs/*.nii.gz')))",
"device": "$torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')",
"network_def": {
"_target_": "SwinUNETR",
"spatial_dims": 3,
"img_size": 96,
"in_channels": 1,
"out_channels": 14,
"feature_size": 48,
"use_checkpoint": true
},
"network": "$@network_def.to(@device)",
"preprocessing": {
"_target_": "Compose",
"transforms": [
{
"_target_": "LoadImaged",
"keys": "image"
},
{
"_target_": "EnsureChannelFirstd",
"keys": "image"
},
{
"_target_": "Orientationd",
"keys": "image",
"axcodes": "RAS"
},
{
"_target_": "Spacingd",
"keys": "image",
"pixdim": [
1.5,
1.5,
2.0
],
"mode": "bilinear"
},
{
"_target_": "ScaleIntensityRanged",
"keys": "image",
"a_min": -175,
"a_max": 250,
"b_min": 0.0,
"b_max": 1.0,
"clip": true
},
{
"_target_": "EnsureTyped",
"keys": "image"
}
]
},
"dataset": {
"_target_": "Dataset",
"data": "$[{'image': i} for i in @datalist]",
"transform": "@preprocessing"
},
"dataloader": {
"_target_": "DataLoader",
"dataset": "@dataset",
"batch_size": 1,
"shuffle": false,
"num_workers": 4
},
"inferer": {
"_target_": "SlidingWindowInferer",
"roi_size": [
96,
96,
96
],
"sw_batch_size": 4,
"overlap": 0.5
},
"postprocessing": {
"_target_": "Compose",
"transforms": [
{
"_target_": "Activationsd",
"keys": "pred",
"softmax": true
},
{
"_target_": "Invertd",
"keys": "pred",
"transform": "@preprocessing",
"orig_keys": "image",
"meta_key_postfix": "meta_dict",
"nearest_interp": false,
"to_tensor": true
},
{
"_target_": "AsDiscreted",
"keys": "pred",
"argmax": true
},
{
"_target_": "SaveImaged",
"keys": "pred",
"meta_keys": "pred_meta_dict",
"output_dir": "@output_dir"
}
]
},
"handlers": [
{
"_target_": "CheckpointLoader",
"load_path": "$@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)",
"[email protected]()"
]
}
21 changes: 21 additions & 0 deletions models/swin_unetr_btcv_segmentation/configs/logging.conf
View file
Original file line number Diff line number Diff line change
@@ -0,0 +1,21 @@
[loggers]
keys=root

[handlers]
keys=consoleHandler

[formatters]
keys=fullFormatter

[logger_root]
level=INFO
handlers=consoleHandler

[handler_consoleHandler]
class=StreamHandler
level=INFO
formatter=fullFormatter
args=(sys.stdout,)

[formatter_fullFormatter]
format=%(asctime)s - %(name)s - %(levelname)s - %(message)s
89 changes: 89 additions & 0 deletions models/swin_unetr_btcv_segmentation/configs/metadata.json
View file
Original file line number Diff line number Diff line change
@@ -0,0 +1,89 @@
{
"schema": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/meta_schema_20220324.json",
"version": "0.1.0",
"changelog": {
"0.1.0": "complete the model package",
"0.0.1": "initialize the model package structure"
},
"monai_version": "0.9.0rc1+19.g61a0dc35",
"pytorch_version": "1.10.0",
"numpy_version": "1.21.2",
"optional_packages_version": {
"nibabel": "3.2.1"
},
"task": "BTCV multi-organ segmentation",
"description": "A pre-trained model for volumetric (3D) multi-organ segmentation from CT image",
"authors": "MONAI team",
"copyright": "Copyright (c) MONAI Consortium",
"data_source": "RawData.zip from https://www.synapse.org/#!Synapse:syn3193805/wiki/217752/",
"data_type": "nibabel",
"image_classes": "single channel data, intensity scaled to [0, 1]",
"label_classes": "multi-channel data,0:background,1:spleen, 2:Right Kidney, 3:Left Kideny, 4:Gallbladder, 5:Esophagus, 6:Liver, 7:Stomach, 8:Aorta, 9:IVC, 10:Portal and Splenic Veins, 11:Pancreas, 12:Right adrenal gland, 13:Left adrenal gland",
"pred_classes": "14 channels OneHot data, 0:background,1:spleen, 2:Right Kidney, 3:Left Kideny, 4:Gallbladder, 5:Esophagus, 6:Liver, 7:Stomach, 8:Aorta, 9:IVC, 10:Portal and Splenic Veins, 11:Pancreas, 12:Right adrenal gland, 13:Left adrenal gland",
"eval_metrics": {
"mean_dice": 0.8283
},
"intended_use": "This is an example, not to be used for diagnostic purposes",
"references": [
"Hatamizadeh, Ali, et al. 'Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors in MRI Images. arXiv preprint arXiv:2201.01266 (2022). https://arxiv.org/abs/2201.01266.",
"Tang, Yucheng, et al. 'Self-supervised pre-training of swin transformers for 3d medical image analysis. arXiv preprint arXiv:2111.14791 (2021). https://arxiv.org/abs/2111.14791."
],
"network_data_format": {
"inputs": {
"image": {
"type": "image",
"format": "hounsfield",
"modality": "CT",
"num_channels": 1,
"spatial_shape": [
96,
96,
96
],
"dtype": "float32",
"value_range": [
0,
1
],
"is_patch_data": true,
"channel_def": {
"0": "image"
}
}
},
"outputs": {
"pred": {
"type": "image",
"format": "segmentation",
"num_channels": 14,
"spatial_shape": [
96,
96,
96
],
"dtype": "float32",
"value_range": [
0,
1
],
"is_patch_data": true,
"channel_def": {
"0": "background",
"1": "spleen",
"2": "Right Kidney",
"3": "Left Kideny",
"4": "Gallbladder",
"5": "Esophagus",
"6": "Liver",
"7": "Stomach",
"8": "Aorta",
"9": "IVC",
"10": "Portal and Splenic Veins",
"11": "Pancreas",
"12": "Right adrenal gland",
"13": "Left adrenal gland"
}
}
}
}
}
36 changes: 36 additions & 0 deletions models/swin_unetr_btcv_segmentation/configs/multi_gpu_train.json
View file
Original file line number Diff line number Diff line change
@@ -0,0 +1,36 @@
{
"device": "$torch.device(f'cuda:{dist.get_rank()}')",
"network": {
"_target_": "torch.nn.parallel.DistributedDataParallel",
"module": "$@network_def.to(@device)",
"device_ids": [
"@device"
]
},
"train#sampler": {
"_target_": "DistributedSampler",
"dataset": "@train#dataset",
"even_divisible": true,
"shuffle": true
},
"train#dataloader#sampler": "@train#sampler",
"train#dataloader#shuffle": false,
"train#trainer#train_handlers": "$@train#handlers[: -2 if dist.get_rank() > 0 else None]",
"validate#sampler": {
"_target_": "DistributedSampler",
"dataset": "@validate#dataset",
"even_divisible": false,
"shuffle": false
},
"validate#dataloader#sampler": "@validate#sampler",
"validate#evaluator#val_handlers": "$None if dist.get_rank() > 0 else @validate#handlers",
"training": [
"$import torch.distributed as dist",
"$dist.init_process_group(backend='nccl')",
"$torch.cuda.set_device(@device)",
"$monai.utils.set_determinism(seed=123)",
"$setattr(torch.backends.cudnn, 'benchmark', True)",
"$@train#trainer.run()",
"$dist.destroy_process_group()"
]
}
Loading

0 comments on commit 0ded5a4

Please sign in to comment.