Release v1.5.1: Nested transforms · roboflow/rf-detr

🚀 Added

Nested Albumentations transforms. OneOf and Sequential containers now work correctly inside the augmentation pipeline. Probability settings on container transforms are ignored — they always fire, keeping composition predictable. Inference pipelines can also pass None targets so the same transform object works for both training and inference. (#752)
```
from rfdetr import RFDETRSmall

model = RFDETRSmall()
model.train(
    dataset_dir="...",
    aug_config={
        "OneOf": [
            {"RandomBrightnessContrast": {"p": 0.5}},
            {"HueSaturationValue": {"p": 0.5}},
        ],
        "HorizontalFlip": {"p": 0.5},
    },
)
```

Dataset transform pipeline now uses torchvision-native Compose, ToImage, and ToDtype instead of custom implementations. Normalize defaults to ImageNet mean/std. (#745)

Fixed RFDETRMedium missing from the public API — __all__ contained a duplicate RFDETRSmall entry instead. (#748)
Fixed AR50_90 reporting an incorrect value in MetricsMLFlowSink due to a wrong COCO evaluation index. (#735)
Fixed supercategory filtering in _load_classes for COCO datasets with flat or mixed supercategory structures. (#744)
Fixed a crash in geometric transforms (flip, crop, etc.) when a sample contains zero-area / empty masks. (#727)
Fixed segmentation training on Colab — DepthwiseConvBlock now disables cuDNN for depthwise separable convolutions. (#728)
Locked onnxsim to <0.6.0 to prevent pip install from hanging indefinitely. (#749)

A special welcome to our new contributors and a big thank you to everyone who helped with this release:

tillfri (@tillfri) – Fix AR50_90 metric index in MLflow sink
justin-alt-account (@justin-alt-account) – Fix RFDETRMedium missing from __all__
Jirka Borovec (@Borda) (LinkedIn) – Nested Albumentations support, transform pipeline refactor, mask fix, supercategory fix, onnxsim pin, CI/testing infrastructure

Full Changelog: 1.5.0...1.5.1