v0.2.1

New Features:

• Add dataset validation step and refactoring data modules by @illian01 in PR 417, PR 419
• Add various dataset examples including automatic open dataset format converter by @illian01 in PR 430
• Allow using text file path for the id_mapping field by @illian01 in PR 432, PR 435

Bug Fixes:

• Fix test directory check line by @illian01 in PR 428
• Fix Dockerfile installation commandline @cbpark-nota in PR 434

Breaking Changes:

No changes to highlight.

Other Changes:

• Save training summary at every end of epochs by @illian01 in PR 420
• Refacotring: rename postprocessors/register.py to registry.py by @aychun in PR 424
• Add example configuration set by @illian01 in PR 438
• Documentation: fix simple use config file path by @cbpark-nota in PR 437

v0.2.0

New Features:

• Add activation and dropout layer in FC by @illian01 in PR 325, PR 327
• Add function to Resize: Match longer side with input size and keep ratio by @illian01 in PR 329
• Add transforms: MosaicDetection by @illian01 in PR 331, PR 337, PR 397
• Add transform: HSVJitter by @illian01 in PR 336, PR 413
• Add transforms: RandomResize by @illian01 in PR 341, PR 344, PR 398
• Add model EMA (Exponential Moving Average) by @illian01 in PR 348
• Add entry point for evaluation and inference by @illian01 in PR 374, PR 379, PR 381, PR 383
• Add classification visulizer by @illian01 in PR 384
• Add dataset caching feature by @illian01 in PR 391
• Add mixed precision training by @illian01 in PR 392
• Add YOLOX l1 loss activation option by @illian01 in PR 396
• Add NetsPresso Trainer YOLOX pretrained weights by @illian01 in PR 406

Bug Fixes:

• Fix output_root_dir from fixed string to config value by @illian01 in PR 323
• Gather predicted results before compute metric and fix additional distributed evaluation inaccurate error by @illian01 in PR 346, PR 356
• Fix detection score return by @illian01 in PR 373
• Fix memory leak from onnx export by @illian01 in PR 386, PR 394
• Refactoring metric modules and fix inaccurate metric bug by @illian01 in PR 402

Breaking Changes:

• Simplify augmentation configuration hierarchy by @illian01 in PR 322
• Add pose estimation task and RTMPose model by @illian01 in PR 357, PR 366
• Remove pythonic config and move training initialization functions to trainer_main.py by @illian01 in PR 371
• Unify gradio demo in one page by @deepkyu in PR 408

Other Changes:

• Refactoring: Move custom transforms to each python module by @illian01 in PR 332
• Update Pad transform to receive target size of image by @illian01 in PR 334
• Rafactoring: Fix to make transform object in init by @illian01 in PR 339
• Add before_epoch step which does update modules like dataloader before epoch training by @illian01 in PR 340
• Revert PR 340 and add multiprocessing.Value to handle MosaicDetection and RandomResize by @illian01 in PR 345
• Enable adjust max epoch of scheduler by illian01 in PR 350
• Remove github action about hugging face space demo by @illian01 in PR 351
• Update docs by @illian01 in PR 355, PR 410
• Backbone task compatibility checking refactoring by @illian01 in PR 361, PR 364
• Fix postprocessor return type as numpy.ndarray by @illian01 in PR 365
• Update default asignees of issue template by @illian01 in PR 375
• Refactoring: Remove CSV logger, change logger module input format by @illian01 in PR 377
• Change ClassficationDataSampler logic by @illian01 in PR 382
• Add YOLOX weights initialization step by @illian01 in PR 393
• Minor update: detection postprocessor, dataset, and padding strategy by @illian01 in PR 395
• Specify input size for onnx export and remove augmentation.img_size by @illian01 in PR 399
• Update issue and pr template by @illian01 in PR 401
• Add documentation auto deploy action by @illian01 in PR 405

v0.1.2

v0.1.2

Bug Fixes:

• Remove union of int and list by @illian01 in PR 317

v0.1.1

v0.1.1

New Features:

• Enable customizing inference transform by @illian01 in PR 304
• Add transform function: CenterCrop by @illian01 in PR 308

Bug Fixes:

• Fix automatic PIDNet weights download bug by @illian01 in PR 306
• Resize default value to list by @illian01 in PR 315

Breaking Changes:

No changes to highlight.

Other Changes:

• Update model caching directory and checkpoint configuration by @deepkyu in PR 299, PR 312
• Minor docs update by @illian01 in PR 300
• Update software development stage by @illian01 in PR 301
• Fix size param of Resize to receive int or list by @illian01 in PR 310
• Modify PIDNet conv bias, add head_list property on models by @illian01 in PR 311

Contributors

• @deepkyu
• @illian01

v0.1.0

v0.1.0

New Features:

• Construct head by config file by @illian01 in PR 237
• Construct neck by config file by @illian01 in PR 249
• Add model: RetinaNet by @illian01 in PR 257
• Select gpus with environment configuration by @deepkyu in PR 269
• Return logging directory path and fix training interfaces by @deepkyu in PR 271
• Add transform: AutoAugment by @illian01 in PR 281

Bug Fixes:

• Fix attribute error on fc by @illian01 in PR 252
• Restore file export for stream log by @deepkyu in PR 255
• Fix CSV logging, configuration error, and misused loggings by @deepkyu in PR 259
• Fix minor bug in train.py by @illian01 in PR 277
• Fix local classification dataset loader error by @illian01 in PR 279
• Fix safetensors file overwriting bug by @illian01 in PR 289
• Fix error on full model load by @illian01 in PR 295

Breaking Changes:

• Provide pytorch state dict with .safetensors and training summary with .json for a better utilization by @deepkyu in PR 262

Other Changes:

• Refactoring for detection models by @illian01 in PR 260
• Equalize logging format with PyNetsPresso by @deepkyu in PR 263
• Refactoring for clean docs by @illian01 in PR 265, PR 266, PR 272, PR 273, PR 274, PR 284
• Update docs up-to-date by @illian01 in PR 278
• Refactoring model building code and move TASK_MODEL_DICT by @illian01 in PR 282
• Add eps param on RMSprop by @illian01 in PR 285
• Fix weights loading logic by @illian01 in PR 287, PR 290
• Change pretrained checkpoint name convention and update weight path and url by @illian01 in PR 291
• Move seed field to environment config by @illian01 in PR 292
• Move ResNet and Fc implementation code to core directory by @illian01 in PR 294

Contributors

• @deepkyu
• @illian01

v0.0.10

v0.0.10

New Features:

• Add a gpu option in train_with_config (only single-GPU supported) by @deepkyu in PR 219
• Support augmentation for classification task: cutmix, mixup by @illian01 in PR 221
• Add model: MixNet by @illian01 in PR 229
• Add model.name to get the exact nickname of the model by @deepkyu in PR 243
• Add transforms: RandomErasing and TrivialAugmentationWide by @illian01 in PR 246

Bug Fixes:

• Fix PIDNet model dataclass task field by @illian01 in PR 220
• Fix default criterion value of classification @illian01 in PR 238
• Fix model access of 2-stage detection pipeline to compat with distributed environment by @illian in PR 239

Breaking Changes:

• Enable dataset augmentation customizing by @illian01 in PR 201
• Add postprocessor module by @illian01 in PR 223
• Equalize the model backbone configuration format by @illian01 in PR 228
• Separate FPN and PAFPN as neck module by @illian01 in PR 234
• Auto-download pretrained checkpoint from AWS S3 by @deepkyu in PR 244

Other Changes:

• Update ruff rule (W) by @deepkyu in PR 218
• Integrate classification loss modules by @illian01 in PR 226

v0.0.9

v0.0.9

New Features:

• Add YOLOX model by @illian01 in PR 195, PR 212
• Fix Faster R-CNN detection head to compat with PyNP compressor by @illian01 in PR 184, PR 194, PR 204
• Support multi-GPU training with netspresso-train entrypoint by @deepkyu, @illian01 and @Only-bottle in PR 213

Bug Fixes:

• Remove fx training flag in entry point by @illian01 in PR 188
• Fix bounding box coordinates computing error on random flip augmentation by @illian01 in PR 211

Breaking Changes:

• Release NetsPresso Trainer colab tutorial @illian01 in PR 191
• Support training with python-level config by @deepkyu in PR 205

Other Changes:

• Refactoring models/op module by @illian01 in PR 189, PR 190
• Parameterize activation function of BasicBlock and Bottleneck by @illian01 in PR193
• Modify MobileNetV3 to stage format and remove forward hook by @illian01 in PR 199
• Substitute MACs counter with fvcore library to sync with NetsPresso by @deepkyu and @Only-bottle in PR 202
• Enable to compute metric with all training samples by @illian01 in PR 210

v0.0.9.b0: checkpointing release for integrating PyNetsPresso

Release note would be included in v0.0.9.

v0.0.8

v0.0.8

New Features:

• Add MobileNetV3 by @illian01 in PR 173
• Handling for fp16 fx model by @illian01 in PR 175
• Deploy Gradio simulators to Hugging Face Space by @deepkyu in PR 181

Bug Fixes:

No changes to highlight.

Breaking Changes:

No changes to highlight.

Other Changes:

• Removed model_name check in create_transform_segmentation function by @illian01 in PR 176
• Combine entry point to train.py by @illian01 in PR 180

v0.0.7

v0.0.7

Bug Fixes:

• ⚠️ Fix pypi package import by @deepkyu in PR 169