v0.14.2

[0.14.2] - 2026-02-24

New Classification Support: You can now train image classification models with LightlyTrain! See the classification documentation for more information.

Added

• Add
  classification support
• Add support for frozen backbone training in LTDETR and Picodet object detection
  models. Set model_args={"backbone_freeze": True} in train_object_detection to
  freeze the backbone and reduce VRAM usage.
• Add LTDETR support for DINOv3 ViT-B/L and DINOv2 ViT-L/B/G models. Pretrained weights
  are not yet available for these models.
• Add support for fine-tuning DINOv2 models for instance segmentation with the
  train_instance_segmentation command. See the
  instance segmentation documentation
  for more information.

Fixed

• Filter invalid bounding boxes in instance segmentation
• Fix incorrect logging of training times.

What's Changed

• Update UV by @guarin in #606
• Relax tests by @guarin in #607
• Add Image Classification Implementation by @guarin in #608
• Implement functions for reading YOLO OBB labels. by @gabrielfruet in #609
• Filter invalid bounding boxes in instance segmentation by @guarin in #610
• Add dinov2 eomt instance segmentation by @guarin in #611
• Add more ltdetr configs by @guarin in #612
• Add image classification multihead by @guarin in #613
• Add semantic segmentation multihead by @guarin in #614
• Fix pywinpty CI error by @guarin in #621
• Update GPU/Data time logging by @guarin in #617
• Document classification by @guarin in #620
• Raise error if backbone weights file doesn't exist by @guarin in #622
• Update license logs by @guarin in #623
• Object Detection backbone freezing option by @gabrielfruet in #618
• Fix timer tests by @guarin in #625
• Release 0.14.2 by @guarin in #626

New Contributors

• @gabrielfruet made their first contribution in #609

Full Changelog: v0.14.1...v0.14.2

v0.14.1

Added

• Add Python 3.13 support.
• Add random rotation transforms for all fine-tuning tasks.
• Add DistillationV3 preview tailored for ViT models.
• Skip weight decay for bias/norm/token/etc. layers.
• Add automatic fine-tuning learning rate scaling based on batch size for all tasks.
• Log fine-tuning training time breakdown.

Changed

• Missing object detection and instance segmentation label files are now treated as
  images without objects instead of being skipped. This can be configured by setting the
  skip_if_label_file_missing flag in the data argument of the
  train_object_detection and train_instance_segmentation functions respectively.
• DINO now updates the teacher temperature and last layer freezing based on the number
  of training steps instead of epochs.

Fixed

• Fix missing libxcb1 dependency in Dockerfile causing cv2 import errors.
• Fix issue when fine-tuning panoptic segmentation models with a different number of
  classes than the pretrained model.

What's Changed

• Add random rotation fine-tune transforms by @guarin in #577
• Thomas trn 1752 classification dataset by @stegmuel in #571
• fix: ensure boolean mask dtype in YOLOObjectDetectionDataset by @ucsk in #580
• Document training settings by @guarin in #581
• Add distillationv3 by @stegmuel in #582
• Update contributing guide by @guarin in #592
• Document pretrain settings by @guarin in #586
• DINO: Use by step schedules by default by @guarin in #588
• Fix docker build by @guarin in #595
• Add LTDETR predict docstring by @guarin in #594
• Add python 3.13 support by @guarin in #593
• Scale fine-tune lr by batch size by @guarin in #589
• Handle missing detection/segmentation label files by @guarin in #587
• No weight decay for bias/norm/token/etc. by @guarin in #597
• No weight decay for norm/bias/tokens/etc. for LTDETR by @guarin in #598
• CI: Remove python 3.12 by @guarin in #603
• Cleanup state dict hooks by @guarin in #600
• LTDETR keep weights hook by @guarin in #602
• Fine-tune log training times by @guarin in #604
• Handle panoptic fine-tune with different num classes by @guarin in #601
• Release 0.14.1 by @guarin in #605

New Contributors

• @ucsk made their first contribution in #580

Full Changelog: v0.14.0...v0.14.1

v0.14.0

New PicoDet Models
We release a preview of PicoDet object detection models for low-power embedded devices!

New Tiny Models
We release tiny DINOv3 based models for instance segmentation, panoptic segmentation, and semantic segmentation!

New ONNX and TensorRT FP16 Export
You can now export all supported models to ONNX and TensorRT in FP16 precision for faster inference! Object detection, instance segmentation, panoptic segmentation, and semantic segmentation are supported!

Added

• Add PicoDet family of object detection models for low-power embedded devices.
• Add tiny semantic segmentation models.
• Add tiny instance segmentation models.
• Add tiny panoptic segmentation models.
• Add FP16/FP32 ONNX and TensorRT export for object detection models.
• Add FP16/FP32 ONNX and TensorRT export for instance segmentation models.
• Add FP16/FP32 ONNX and TensorRT export for panoptic segmentation models.
• Add FP16/FP32 ONNX and TensorRT export for semantic segmentation models.
• Add example jupyter notebooks for ONNX and TensorRT export.
• Add Slicing Aided Hyper Inference (SAHI) for object detection to improve small objects
  recall at inference.
• Add pretraining support for Ultralytics RT-DETR models.
• Add support for different patch size in EoMT and semantic segmentation.
• Add classwise metrics support for object detection models.
• Add ignore_classes support for object detection models.

Changed

• Change default DINOv3 EoMT semantic segmentation image size from 518x518 to 512x512.
• New checkpoints for the COCO pretrained DINOv3 EoMT semantic segmentation models.

Fixed

• Fix numerical stability issues in LTDETR's matcher.
• Fix issue when resuming from interrupted runs with custom model args.

What's Changed

• Auto-wrap markdown by @guarin in #525
• Improve teacher loading logging by @guarin in #527
• Thomas trn 1715 ltdetr tensorrt export by @stegmuel in #522
• Object detection - SAHI by @stegmuel in #508
• Set dinov3 eomt semseg default image size to 512 by @guarin in #533
• Add pretrain to API docs by @guarin in #534
• Tiny eomt semseg models by @stegmuel in #536
• Move semantic segmentation onnx export to model by @guarin in #528
• Update EoMT coco semseg models by @guarin in #537
• Fix potential NaNs in matchs by @stegmuel in #538
• Update coco sem. seg. results by @stegmuel in #539
• Add semantic segmentation tensorrt export by @guarin in #535
• Enable RTDETR by @XevenQC in #529
• Add instance segmentation onnx export by @guarin in #540
• Support ultralytics models from local path by @guarin in #543
• Add instance segmentation tensorrt export by @guarin in #541
• Add panoptic segmentation onnx/tensorrt export by @guarin in #542
• Thomas trn 1744 eomt tiny by @stegmuel in #532
• Handle zero ema warmup steps by @guarin in #550
• Thomas trn 1745 tiny eomt inst models by @stegmuel in #552
• fix best model export by @stegmuel in #554
• Add task images by @guarin in #556
• Update LTDETR train arg names by @guarin in #545
• fix broken instance seg. table by @stegmuel in #559
• make vit tiny available for pan. seg. by @stegmuel in #557
• Add FP16 support for EoMT models by @guarin in #561
• change type before transforms by @stegmuel in #563
• Fix validation aliases by @guarin in #568
• Fix LTDETR ONNX FP16 export by @guarin in #562
• Add LTDETR classwise metrics and ignore classes by @guarin in #569
• Add picodet model by @IgorSusmelj in #531
• Add picodet docs by @IgorSusmelj in #574
• get model_init_args from checkpoint by @stegmuel in #575
• Prepeare 0.14.0 release by @guarin in #572

New Contributors

• @XevenQC made their first contribution in #529

Full Changelog: v0.13.2...v0.14.0

v0.13.2

Added

• Support for pretraining RF-DETR 1.3 models.

Changed

• Export only EMA weights for object detection models. This reduces the exported model
  size by 2x.

Fixed

• Fix pretrained ViT-small panoptic segmentation model checkpoint.

What's Changed

• Support new RF-DETR 1.3 models (Small, Nano, Medium, SegPreview) by @masakljun in #503
• Update DINOv3 ViT-S Panoptic COCO Checkpoint by @guarin in #519
• Update events for predictions by @IgorSusmelj in #521
• Export only EMA model by @guarin in #516
• Add DINOv3 fine-tuning tests by @guarin in #517
• Release 0.13.2 by @guarin in #524

Full Changelog: v0.13.1...v0.13.2

v0.13.1

Fixed

• Fix bug in ONNX export for object detection models.

What's Changed

• Add argument for number of channels and better inference. by @stegmuel in #512
• Release v0.13.1 by @guarin in #515

Full Changelog: v0.13.0...v0.13.1

v0.13.0

New DINOv3 Tiny Object Detection Models: We release tiny DINOv3 models pretrained on
COCO for object detection!

New DINOv3 Panoptic Segmentation: You can now run inference and fine-tune DINOv3 models
for panoptic segmentation!

Added

• New COCO pretrained tiny LTDETR models vitt16 and vitt16plus.
• Support for DINOv3 panoptic segmentation inference and fine-tuning.
• Quick start guide for object detection.
• Possibility to load backbone weights in LTDETR.
• ONNX export for LTDETR.
• Add Weights & Biases logging support for all fine-tuning tasks.
• Log best validation metrics at the end of training.

Changed

• Rename lightly_train.train() to lightly_train.pretrain(). The old name is still
  available as an alias for backward compatibility but will be removed in a future release.
• Restructured the documentation to better reflect the different workflows supported
  by LightlyTrain.

Fixed

• Fix bug in model.predict() for object detection models.
• Fix bug in object detection transforms when using images with dtype float32.
• Fix bug when running pretraining on an MPS device.
• Fix bug when resuming training with a recent PyTorch version.
• Fix bug when resuming a crashed run that was initialized from a pretrained COCO model.

What's Changed

• add log of best result by @masakljun in #475
• Thomas trn 1628 small od models by @stegmuel in #430
• Object detection support backbone weights by @stegmuel in #483
• Fix resuming from coco init by @stegmuel in #485
• Add panoptic segmentation by @guarin in #488
• Load teacher on correct device by @guarin in #490
• Thomas trn 1653 ltdetr onnx export by @stegmuel in #487
• Remove RSNA/Neurips banner by @stegmuel in #494
• Fix resuming error with recent torch versions by @guarin in #492
• Fix learning rate monitor float64 MPS issue by @guarin in #496
• Remove teacher eval mode warning by @guarin in #495
• Masa trn 1695 load ema weights only by @masakljun in #484
• Use latency everywhere by @stegmuel in #498
• Add links to vit tiny checkpoints by @stegmuel in #497
• Fix pytest out of disk space by @guarin in #502
• Cleanup transforms dtypes and asserts by @guarin in #499
• Revert docs CSS changes by @guarin in #504
• Restructure docs by @guarin in #489
• Update distillation quickstart by @guarin in #506
• Release v0.13.0 by @guarin in #507

New Contributors

• @masakljun made their first contribution in #475

Full Changelog: v0.12.4...v0.13.0

v0.12.4

Fixed

• Fix bug in model.predict() for object detection models.

What's Changed

• Fix bug in object detection model.predict by @guarin in #473
• Release v0.12.4 by @guarin in #474

Full Changelog: v0.12.3...v0.12.4

v0.12.3

Added

• Add support for specifying data configs in YAML format.

Changed

• Improve the layout of the object detection training logs.

Deprecated

• Deprecate reuse_class_head argument in train command. The model will now
  automatically reuse the classification head only when the number of classes in the
  data config matches that in the checkpoint. Otherwise, the classification head will
  be re-initialized.

Fixed

• Fix image_size not tuple when training from pretrained model.
• Fix a bug when fine-tuning a model with resume_interrupted=True.
• Fix num_classes not updated when loading an object detection checkpoint with
  different number of classes.

What's Changed

• Fix and speed up unit tests by @guarin in #450
• Add events for training detection and segmentation models by @IgorSusmelj in #447
• Fix dist training issues by @yutong-xiang-97 in #446
• Fix resume interrupted for fine-tuning by @guarin in #448
• Support yaml data config by @yutong-xiang-97 in #455
• Improve Metrics Logging by @yutong-xiang-97 in #458
• Internal class id mapping in Object Detection dataset by @yutong-xiang-97 in #462
• Update docs/readme by @guarin in #454
• Fix url of SAT493m url by @stegmuel in #465
• Deprecate reuse class head and use hooks for segmentation by @yutong-xiang-97 in #466
• Add RSNA/NeurIPS README banner by @liopeer in #468
• Fix README title by @liopeer in #469
• Fix OD num_classes issue. by @yutong-xiang-97 in #467
• Release v0.12.3 by @guarin in #472

Full Changelog: v0.12.2...v0.12.3

v0.12.2

Fixed

• Fix image_size not tuple when training from pretrained model.

What's Changed

• Fix object detection image size from checkpoint by @guarin in #444
• Release v0.12.2 by @guarin in #445

Full Changelog: v0.12.1...v0.12.2

v0.12.1

Added

• Add support for DINOv3 instance segmentation
  inference and fine-tuning.
• Add support for loading DICOM images
  as input data for training and inference.
• Add event tracking, disable with LIGHTLY_TRAIN_EVENTS_DISABLED=1
• Add support for fine-tuning object detection models with custom image resolutions.

What's Changed

• Add object detection colab by @guarin in #418
• Add SAT493m models to distillation docs by @liopeer in #421
• Add DICOM image loading support by @yutong-xiang-97 in #416
• Thomas trn 1628 small vit by @stegmuel in #417
• Save object detection prediction results in COCO format by @yutong-xiang-97 in #422
• Add event tracking by @IgorSusmelj in #406
• Instance segmentation improvements by @guarin in #423
• Add init_weights to DINOv3 ViT to fix the flaky tests by @yutong-xiang-97 in #427
• Add eomt instance segmentation docs by @guarin in #426
• Update detection image by @guarin in #429
• Freeze teacher parameters in Distillation and DistillationV2 by @OshriFatkiev in #434
• Document Non-RGB & DICOM loading support by @yutong-xiang-97 in #432
• Disable unit test tracker by @guarin in #438
• Add object detection custom image resolution fine-tuning by @guarin in #437
• Release v0.12.1 by @guarin in #440

New Contributors

• @IgorSusmelj made their first contribution in #406
• @OshriFatkiev made their first contribution in #434

Full Changelog: v0.12.0...v0.12.1