1.5.2

## 🚀 Added

- **Peak GPU memory in progress bars.** Training and evaluation tqdm bars now display `max_mem` (in MB) when running on CUDA, making it easy to track hardware utilisation without a separate profiling tool. The metric is device-aware and is omitted on CPU and MPS runs. (#773)

## 🔧 Fixed

- Fixed `aug_config` being silently ignored when training on YOLO-format datasets — `build_roboflow_from_yolo` never forwarded the value, so transforms always fell back to the default `AUG_CONFIG` regardless of what was configured. (#774)
- Fixed segmentation evaluation metrics not being written to `results_mask.json` during the validation phase. The file now has the same structure as `results.json` and is updated after both validation and test runs. (#772)
- Fixed `AttributeError` crash in `update_drop_path` when the DinoV2 backbone layer structure does not match any known pattern. `_get_backbone_encoder_layers` now returns `None` for unrecognised architectures and `update_drop_path` exits early instead of raising. (#762)
- Fixed `drop_path_rate` not being forwarded to the DinoV2 model configuration, meaning stochastic depth was never actually applied even when explicitly set. A warning is now emitted when `drop_path_rate > 0.0` is used with a non-windowed backbone where it has no effect. (#762)
- Fixed incorrect COCO hierarchy filtering logic that caused parent categories to be excluded from the class list when they should have been retained. (#759)
- Fixed evaluation metric corruption on 1-indexed Roboflow datasets caused by a flawed contiguity check in `_should_use_raw_category_ids` — the old heuristic inspected per-batch labels and could pick the wrong resolution path depending on which labels happened to appear first. (#755)

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## 🏆 Contributors

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

* **Samuel Lima** (@samuellimabraz) – *Fix drop path in DinoV2 backbone*
* **youthfrost** (@youthfrost) – *Fix segmentation results_mask.json saving*
* **Jelle R. Dalenberg** (@jrdalenberg) ([LinkedIn](https://www.linkedin.com/in/jelledalenberg)) – *Fix COCO hierarchy filtering*
* **Abdul Mukit** (@Abdul-Mukit) ([LinkedIn](https://www.linkedin.com/in/abdul-mukit-in)) – *Fix category contiguity and evaluation metric corruption on 1-indexed datasets*
* **Jirka Borovec** (@Borda) ([LinkedIn](https://www.linkedin.com/in/jirka-borovec/)) – *Fix aug_config in YOLO dataset builder, max_mem telemetry, CI/testing infrastructure*

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**Full Changelog**: https://github.com/roboflow/rf-detr/compare/1.5.1...1.5.2