1.3.1
版本发布时间: 2024-05-21 16:24:42
Project-MONAI/MONAI最新发布版本:1.4.0(2024-10-17 08:54:28)
Added
- Support for
by_measure
argument inRemoveSmallObjects
(#7137) - Support for
pretrained
flag inResNet
(#7095) - Support for uploading and downloading bundles to and from the Hugging Face Hub (#6454)
- Added weight parameter in DiceLoss to apply weight to voxels of each class (#7158)
- Support for returning dice for each class in
DiceMetric
(#7163) - Introduced
ComponentStore
for storage purposes (#7159) - Added utilities used in MONAI Generative (#7134)
- Enabled Python 3.11 support for
convert_to_torchscript
andconvert_to_onnx
(#7182) - Support for MLflow in
AutoRunner
(#7176) -
fname_regex
option in PydicomReader (#7181) - Allowed setting AutoRunner parameters from config (#7175)
-
VoxelMorphUNet
andVoxelMorph
(#7178) - Enabled
cache
option inGridPatchDataset
(#7180) - Introduced
class_labels
option inwrite_metrics_reports
for improved readability (#7249) -
DiffusionLoss
for image registration task (#7272) - Supported specifying
filename
inSaveimage
(#7318) - Compile support in
SupervisedTrainer
andSupervisedEvaluator
(#7375) -
mlflow_experiment_name
support inAuto3DSeg
(#7442) - Arm support (#7500)
-
BarlowTwinsLoss
for representation learning (#7530) -
SURELoss
andConjugateGradient
for diffusion models (#7308) - Support for
CutMix
,CutOut
, andMixUp
augmentation techniques (#7198) -
meta_file
andlogging_file
options toBundleWorkflow
(#7549) -
properties_path
option toBundleWorkflow
for customized properties (#7542) - Support for both soft and hard clipping in
ClipIntensityPercentiles
(#7535) - Support for not saving artifacts in
MLFlowHandler
(#7604) - Support for multi-channel images in
PerceptualLoss
(#7568) - Added ResNet backbone for
FlexibleUNet
(#7571) - Introduced
dim_head
option inSABlock
to set dimensions for each head (#7664) - Direct links to github source code to docs (#7738, #7779)
misc.
- Refactored
list_data_collate
andcollate_meta_tensor
to utilize the latest PyTorch API (#7165) - Added str method in
Metric
base class (#7487) - Made enhancements for testing files (#7662, #7670, #7663, #7671, #7672)
- Improved documentation for bundles (#7116)
Fixed
transforms
- Addressed issue where lazy mode was ignored in
SpatialPadd
(#7316) - Tracked applied operations in
ImageFilter
(#7395) - Warnings are now given only if missing class is not set to 0 in
generate_label_classes_crop_centers
(#7602) - Input is now always converted to C-order in
distance_transform_edt
to ensure consistent behavior (#7675)
data
- Modified .npz file behavior to use keys in
NumpyReader
(#7148) - Handled corrupted cached files in
PersistentDataset
(#7244) - Corrected affine update in
NrrdReader
(#7415)
metrics and losses
- Addressed precision issue in
get_confusion_matrix
(#7187) - Harmonized and clarified documentation and tests for dice losses variants (#7587)
networks
- Removed hard-coded
spatial_dims
inSwinTransformer
(#7302) - Fixed learnable
position_embeddings
inPatchEmbeddingBlock
(#7564, #7605) - Removed
memory_pool_limit
in TRT config (#7647) - Propagated
kernel_size
toConvBlocks
withinAttentionUnet
(#7734) - Addressed hard-coded activation layer in
ResNet
(#7749)
bundle
- Resolved bundle download issue (#7280)
- Updated
bundle_root
directory forNNIGen
(#7586) - Checked for
num_fold
and failed early if incorrect (#7634) - Enhanced logging logic in
ConfigWorkflow
(#7745)
misc.
- Enabled chaining in
Auto3DSeg
CLI (#7168) - Addressed useless error message in
nnUNetV2Runner
(#7217) - Resolved typing and deprecation issues in Mypy (#7231)
- Quoted
$PY_EXE
variable to handle Python path that contains spaces in Bash (#7268) - Improved documentation, code examples, and warning messages in various modules (#7234, #7213, #7271, #7326, #7569, #7584)
- Fixed typos in various modules (#7321, #7322, #7458, #7595, #7612)
- Enhanced docstrings in various modules (#7245, #7381, #7746)
- Handled error when data is on CPU in
DataAnalyzer
(#7310) - Updated version requirements for third-party packages (#7343, #7344, #7384, #7448, #7659, #7704, #7744, #7742, #7780)
- Addressed incorrect slice compute in
ImageStats
(#7374) - Avoided editing a loop's mutable iterable to address B308 (#7397)
- Fixed issue with
CUDA_VISIBLE_DEVICES
setting being ignored (#7408, #7581) - Avoided changing Python version in CICD (#7424)
- Renamed partial to callable in instantiate mode (#7413)
- Imported AttributeError for Python 3.12 compatibility (#7482)
- Updated
nnUNetV2Runner
to support nnunetv2 2.2 (#7483) - Used uint8 instead of int8 in
LabelStats
(#7489) - Utilized subprocess for nnUNet training (#7576)
- Addressed deprecated warning in ruff (#7625)
- Fixed downloading failure on FIPS machine (#7698)
- Updated
torch_tensorrt
compile parameters to avoid warning (#7714) - Restrict
Auto3DSeg
fold input based on datalist (#7778)
Changed
- Base Docker image upgraded to
nvcr.io/nvidia/pytorch:24.03-py3
fromnvcr.io/nvidia/pytorch:23.08-py3
Removed
- Removed unrecommended star-arg unpacking after a keyword argument, addressed B026 (#7262)
- Skipped old PyTorch version test for
SwinUNETR
(#7266) - Dropped docker build workflow and migrated to Nvidia Blossom system (#7450)
- Dropped Python 3.8 test on quick-py3 workflow (#7719)