3.4.1

Bugfixes

• Fix serialization of ListConfig in checkpoint state dictionary by @BloodAxe in #1534
• Ensure that checkpoint_num_classes is propagated from YAML to model by @BloodAxe in #1533
• Fixed a bug in YoloNASPose.export() that prevented to export model for BS>1 by @BloodAxe in #1530
• Check class_id validity in DetectionDataset by @Louis-Dupont in #1536
• Fix training_params deprecation by @Louis-Dupont in #1542
• Fixing typos and adding extra info to CONTRIBUTING by @hakuryuu96 in #1546
• Remove np.bool which is not supported in latest np versions by @Louis-Dupont in #1558
• Fix CSPDarknet53.foward by @Louis-Dupont in #1564
• Bugfix of model.export() to work correct with bs>1 by @BloodAxe in #1551
• Mixed precision automatically changed with warning by @Louis-Dupont in #1567
• Updated data-gradients requirement by @shaydeci in #1572
• Fixed issue with torch 1.12 where _scale_fn_ref is missing in CyclicLR by @BloodAxe in #1575
• Fixed issue with torch 1.12 issue with arange not supporting fp16 for CPU device. by @BloodAxe in #1574
• Reorder operators to ensure Neg operator is not used by @BloodAxe in #1584
• Updated "What are Recipes and How To Use Them" notebook by @BloodAxe in #1586
• Update link for "Open in Colab" by @BloodAxe in #1588
• Added metrics logging to checkpoint and separate yaml file by @hakuryuu96 in #1562
• Fixed bug in ModelWeightAveraging class that led to corrupted model when metric to watch was NaN/Inf by @BloodAxe in #1598
• Transfer learning classification notebook update by @shaydeci in #1587
• Update KD Notebook for classification by @BloodAxe in #1595
• Fixed bug in COCOPoseEstimationDataset which caused the images or reversed channel order used in predict() by @BloodAxe in #1609
• Fixed supervisely .get which uses dataset: inside the .yaml file by @shaydeci in #1603
• Fixed bug in _pad_image that did not support pad_value=(R,B,G) input by @BloodAxe in #1599
• Fixed ListConfig in pose estimation dataset classes by @BloodAxe in #1602
• Enforced check of that all notebooks has matching SG version installed by @BloodAxe in #1607
• Update README by @BloodAxe in #1615
• Way to fix bug with validation frequency by @hakuryuu96 in #1601
• Changed key for SegKDLoss by @hakuryuu96 in #1620
• Bump onnx-simplifier version require at least 0.4.3 by @BloodAxe in #1631

Enhancement:

• Add class_names to model.predict for detection by @Louis-Dupont in #1529
• Argument max_batches support to training log and tqdm progress bar. by @hakuryuu96 in #1554
• Add explanations on experiment management by @Louis-Dupont in #1559
• Added recipe unifying script by @shaydeci in #1560
• Added packages to pth checkpoint by @hakuryuu96 in #1581
• Added sequential assignment capability to PPYoloELoss by @BloodAxe in #1582
• Add replace in channels by @Louis-Dupont in #1557
• Add image examples by @Louis-Dupont in #1589
• Update ptq and qat training by @BloodAxe in #1618
• Added convert_from_recipe script, that converts yaml train_from_config, "recipe style" training script to a "python dictionaries" standalone training script. by @BloodAxe in #1568

New Contributors

• @hakuryuu96 made their first contribution in #1546
• @aler9 made their first contribution in #1548