Release v1.5.0
New features
- Enable configurable confidence threshold for otx eval and export (#2388)
- Add YOLOX variants as new object detector models (#2402)
- Enable FeatureVectorHook to support action tasks (#2408)
- Add ONNX metadata to detection, instance segmantation, and segmentation models (#2418)
- Add a new feature to configure input size (#2420)
- Introduce the OTXSampler and AdaptiveRepeatDataHook to achieve faster training at the small data regime (#2428)
- Add a new object detector Lite-DINO (#2457)
- Add Semi-SL Mean Teacher algorithm for Instance Segmentation task (#2444)
- Official supports for YOLOX-X, YOLOX-L, YOLOX-S, ResNeXt101-ATSS (#2485)
- Add new argument to track resource usage in train command (#2500)
- Add Self-SL for semantic segmentation of SegNext families (#2215)
- Adapt input size automatically based on dataset statistics (#2499)
Enhancements
- Refine input data in-memory caching (#2416)
- Adapt timeout value of initialization for distributed training (#2422)
- Optimize data loading by merging load & resize operations w/ caching support for cls/det/iseg/sseg (#2438, #2453, #2460)
- Support torch==2.0.1 (#2465)
- Set "Auto" as default input size mode (#2515)
Bug fixes
- Fix F1 auto-threshold to choose best largest confidence (#2371)
- Fix a performance drop while training EfficientNetV2 with multi-GPU (#2398)
- Fix bug that auto adaptive batch size raises an error if CUDA isn't available (#2410)
- Fix sampler degradation issue (#2482)
- Fix a bug that
fp16
key error is raised when training without GPU (#2501) - Fix bug that auto batch size doesn't consider distributed training (#2533)
- Fix auto input size mismatch in eval & export (#2530)
- Fix the CustomNonLinearClsHead when the batch_size is set to 1 (#2571)
- Fix IBLoss enablement with DeiT-Tiny when class incremental training (#2594)
- Fix XAI algorithm for Detection (#2617)
Full Changelog: 1.4.4...1.5.0