3.6.0
版本发布时间: 2024-01-25 22:25:20
Deci-AI/super-gradients最新发布版本:3.7.1(2024-04-09 00:50:10)
Hey @channel We're pleased to announce the release of Super-Gradients 3.6.0 :slightly_smiling_face: . This update includes several important changes and improvements: Changes and Enhancements
- Added segmentation samples and support for albumentation transforms for segmentation, contributed by @shaydeci.
- Implemented distance-based detection matching in
DetectionMetrics
as an enhancement by @DimaBir. - New training hyperparameter - finetune, and multiple LR assignment by @shaydeci, read about it here
- Enhanced
ImagePermute
processing inclusion, by @BloodAxe. - Improved dataset plotting and plot functionality, by @Louis Dupont .
- Updated prediction notebooks and documentation, thanks to @Louis Dupont .
- Supported depth estimation dataset and added depth estimation metrics support, by @shaydeci.
- Proposed an API for checking model input compatibility, by @BloodAxe.
- Extended
predict()
support for segmentation models, by @BloodAxe. - Removed deprecated features from version 3.6.0, by @shaydeci.
- Updated pre-trained models badge URL, contributed by @gasparitiago.
- Made changes to
PPYoloELoss
, removing the requirement for areg_max
parameter, by @BloodAxe. - Switched to using
onnxsim
instead ofonnx-simplifier
for consistency in naming, thanks to @BloodAxe. Bugfixes - Resolved a bug in
OhemLoss
thanks to @danielafrimi. - Updated conditions to ensure functionality only on rank 0 where
[context.sg](http://context.sg/)_logger
is available, by @shaydeci. - Modified the default
set_device
value to prevent unintentional launch of DDP, updated by @Louis Dupont . - Addressed a bug where
multigpu=None
withdevice=cpu
wasn't functioning as expected, thanks to @Louis Dupont . - Adjusted bounding box thickness and text size relative to bbox size, for object detection model's predict() by @Louis Dupont .
- Addressed a bug in
DetectionMixup
that affectedYoloXTrainingStageSwitchCallback
, by @BloodAxe. - Corrected a typo in an exception message variable name, by @BloodAxe.
- Reintegrated tests and refined CI/CD workflows, thanks to @shaydeci and @Yonatan-Kaplounov.
- Fixed import issues and improved model flexibility and metrics handling, mainly by @BloodAxe.
- Ensured class names in
DetectionDataset
are contained within a trivial container, by @BloodAxe. - Fixed
ExtremeBatchDetectionVisualizationCallback
for multiscale collate function, by @BloodAxe. - Several bug fixes and improvements in
DistanceBasedDetectionMetrics
andDetectionMetrics
, by @BloodAxe. And various other fixes and improvements across the board to enhance functionality and user experience. For a detailed list of changes, refer to the full changelog. New Contributors - Welcome to the contributors' team, @DimaBir, @gasparitiago, and @Yonatan-Kaplounov, for making their first contributions.Hey @channel We're pleased to announce the release of Super-Gradients 3.6.0 :slightly_smiling_face: . This update includes several important changes and improvements: Changes and Enhancements
- Added segmentation samples and support for albumentation transforms for segmentation, contributed by @shaydeci.
- Implemented distance-based detection matching in
DetectionMetrics
as an enhancement by @DimaBir. - New training hyperparameter - finetune, and multiple LR assignment by @shaydeci, read about it here
- Enhanced
ImagePermute
processing inclusion, by @BloodAxe. - Improved dataset plotting and plot functionality, by @Louis Dupont .
- Updated prediction notebooks and documentation, thanks to @Louis Dupont .
- Supported depth estimation dataset and added depth estimation metrics support, by @shaydeci.
- Proposed an API for checking model input compatibility, by @BloodAxe.
- Extended
predict()
support for segmentation models, by @BloodAxe. - Removed deprecated features from version 3.6.0, by @shaydeci.
- Updated pre-trained models badge URL, contributed by @gasparitiago.
- Made changes to
PPYoloELoss
, removing the requirement for areg_max
parameter, by @BloodAxe. - Switched to using
onnxsim
instead ofonnx-simplifier
for consistency in naming, thanks to @BloodAxe. Bugfixes - Resolved a bug in
OhemLoss
thanks to @danielafrimi. - Updated conditions to ensure functionality only on rank 0 where
[context.sg](http://context.sg/)_logger
is available, by @shaydeci. - Modified the default
set_device
value to prevent unintentional launch of DDP, updated by @Louis Dupont . - Addressed a bug where
multigpu=None
withdevice=cpu
wasn't functioning as expected, thanks to @Louis Dupont . - Adjusted bounding box thickness and text size relative to bbox size, for object detection model's predict() by @Louis Dupont .
- Addressed a bug in
DetectionMixup
that affectedYoloXTrainingStageSwitchCallback
, by @BloodAxe. - Corrected a typo in an exception message variable name, by @BloodAxe.
- Reintegrated tests and refined CI/CD workflows, thanks to @shaydeci and @Yonatan-Kaplounov.
- Fixed import issues and improved model flexibility and metrics handling, mainly by @BloodAxe.
- Ensured class names in
DetectionDataset
are contained within a trivial container, by @BloodAxe. - Fixed
ExtremeBatchDetectionVisualizationCallback
for multiscale collate function, by @BloodAxe. - Several bug fixes and improvements in
DistanceBasedDetectionMetrics
andDetectionMetrics
, by @BloodAxe. And various other fixes and improvements across the board to enhance functionality and user experience. For a detailed list of changes, refer to the full changelog. New Contributors - Welcome to the contributors' team, @DimaBir, @gasparitiago, and @Yonatan-Kaplounov, for making their first contributions..