Release v1.5.0rc1

What's Changed

• POT->PTQ renaming in tests by @sovrasov in #2319
• Update the version of the openvino badge by @sungmanc in #2329
• Tiling doc for develop by @eugene123tw in #2334
• Relax reference saliency values check by @negvet in #2338
• Call otx.cli before the TaskType is imported by @harimkang in #2342
• added fix-cpu numbers option by @yunchu in #2340
• Fix tiling unittest and random max select logic by @eugene123tw in #2336
• Update incorrect license header by @yunchu in #2352
• Fixing XAI tests by @negvet in #2357
• Change IR scale factor to 1.0 if tile size is too big by @eugene123tw in #2337
• Add model category attributes to model template by @goodsong81 in #2362
• Fix F1 auto-threshold to choose best largest confidence by @goodsong81 in #2371
• Add model type to deit ptq config by @sovrasov in #2379
• Add description & remove unused configurable parameters by @goodsong81 in #2382
• Add onnx metadata to classification models by @sovrasov in #2378
• Update exportable code README (to develop) by @GalyaZalesskaya in #2389
• Rename SAMImageClassifier -> CustomImageClassifier by @goodsong81 in #2384
• Merge back 1.4.0 to develop by @yunchu in #2387
• Update version string of the OTX by @yunchu in #2393
• [develop] XAI: Return saliency maps for Mask RCNN IR async infer by @GalyaZalesskaya in #2391
• Enable deterministic for anomalib and visual prompting by @sungchul2 in #2361
• Fix a performance drop while training EfficientNetV2 with multi-GPU by @eunwoosh in #2398
• Change POT to PTQ in test code by @eunwoosh in #2401
• Enable configurable confidence threshold for ov export and inference by @jaegukhyun in #2388
• Fix e2e by @jaegukhyun in #2404
• Add YOLOX variants to OTX by @jaegukhyun in #2402
• Enable FeatureVectorHook for action tasks by @jaegukhyun in #2408
• Update Anomaly OpenVINO export for ModelAPI by @ashwinvaidya17 in #2400
• Fix bug that auto adaptive batch size raises an error if CUDA isn't available by @eunwoosh in #2410
• Check sal maps for async infer for M-RCNN by @negvet in #2396
• Remove data cfg in detection training recipe by @jaegukhyun in #2409
• Switch to MAPI in classification and detection inference tasks by @sovrasov in #2390
• Mergeback 1.4.1 to develop by @yunchu in #2413
• Enable ViTReciproCAM for VisionTransformer backbone (cls task) by @negvet in #2403
• Add onnx meta for sseg, iseg, and detection models by @sovrasov in #2418
• Reduce amount of SSeg PTQ e2e tests by @sovrasov in #2414
• Refactor instance segmentation and tiling inference by @sovrasov in #2415
• Refine input data in-memory caching by @goodsong81 in #2416
• Configurable input size by @eunwoosh in #2420
• Adpat timeout value of torch.dist.init_process_group depending on elapsed time by @eunwoosh in #2422
• Refactor semantic segmentation inference to use MAPI by @sovrasov in #2421
• Update FQ refs for iseg models by @sovrasov in #2426
• Limit range of PTQ parameters by @sovrasov in #2425
• Refactor configurer - Phase1 by @jaegukhyun in #2424
• Upgrade ModelAPI by @sovrasov in #2429
• Move SegNext models from experimental to custom models by @kprokofi in #2312
• Refactor configurer - Phase 2 by @jaegukhyun in #2430
• Introduce AdaptiveRepeatDataHook for the classification by @sungmanc in #2428
• Write a docs and cover additional case about configurable input size by @eunwoosh in #2433
• Fix E2E, Regression test failures and edit the inproper log message by @sungmanc in #2436
• Enable multi-gpus for weekly by @yunchu in #2364
• Add MaskRCNN SwinTransformer-T by @eugene123tw in #2423
• Fix i-seg e2e test code by @eunwoosh in #2446
• Stabilize multi GPU training by @eunwoosh in #2443
• Merge load / resize / cache to optimize data loading efficiency for classification by @goodsong81 in #2438
• Refactor configurer - Phase 3 by @jaegukhyun in #2442
• Merge load / resize / cache to optimize data loading efficiency for detection & instance segmentation by @goodsong81 in #2453
• Align resume batch size with train batch size in i-seg e2e test by @eunwoosh in #2458
• Merge load / resize / cache to optimize data loading efficiency for semantic segmentation by @goodsong81 in #2460
• Apply load+resize cache to validation pipelines by @goodsong81 in #2463
• Add a new object detector, Lite-DINO by @jaegukhyun in #2457
• Bump datumaro version by @yunchu in #2466
• Set tox version constraint by @yunchu in #2471
• Add utilization of the unlabeled subset in PTQ optimization by @kprokofi in #2468
• Remove unnecessary workflows by @yunchu in #2474
• Add unit tests for DINO and Lite-DINO by @jaegukhyun in #2475
• Mergeback 1.4.2rc2 by @yunchu in #2464
• Added quantization configs for SegNext T S B by @nikita-savelyevv in #2477
• Update regression criteria for anomaly task by @yunchu in #2476
• Fix some issues on cls regression tests by @yunchu in #2478
• Adjust PTQ fq target by @chuneuny-emily in #2480
• Add Semi-SL Instance Segmentation by @kprokofi in #2444
• Fix some bugs for reg tests by @yunchu in #2481
• Fix sampler degradation issue by @sungmanc in #2482
• Make MaskRCNN-SwinT from experimental to production by @eugene123tw in #2454
• Remove mpa legacy by @jaegukhyun in #2486
• Fix some regression test issues for segmentation by @yunchu in #2488
• Re-organization of configurer by @jaegukhyun in #2484
• Model revamp for Geti - Object Detection by @jaegukhyun in #2485
• Fix e2e tests for xai_sanity_classification by @GalyaZalesskaya in #2490
• Fix object detection e2e tests by @jaegukhyun in #2492
• Add Semi-SL Instance Segmentation Documentation by @kprokofi in #2487
• Update unit tests for XAI by @GalyaZalesskaya in #2491
• Update .pre-commit-config.yaml by @yunchu in #2494
• Align batch size in instance segmentation task for Semi-SL to avoid OOM error by @kprokofi in #2493
• Fix unit tests for XAI by @GalyaZalesskaya in #2495
• Update inst-seg end2end test fake quantization by @eugene123tw in #2496
• Add new argument to track CPU&GPU utilization and memory usage by @eunwoosh in #2500
• Fix a bug that fp16 key error is raised when training without GPU by @eunwoosh in #2501
• Move configuration of configs in task.py to configurer.py by @jaegukhyun in #2498
• Fix reg summary bug by @yunchu in #2503
• Set mem-cache-1G as a default training by @sungmanc in #2489
• Add Self-SL configs for SegNext by @sungchul2 in #2215
• Update Inst Seg Model Revamp by @eugene123tw in #2506
• Add human right disclaimer in README.md by @goodsong81 in #2508
• Fix e2e failed case of visual prompting task by @sungchul2 in #2509
• Support torch==2.0.1 by @goodsong81 in #2465
• Mergeback 1.4.2rc5 by @yunchu in #2511
• Adapt input size automatically based on dataset statistics by @goodsong81 in #2499
• Fix rotated detection by @sungmanc in #2512
• Adjust FQ criteria in anomaly/instance seg tasks by @chuneuny-emily in #2517
• Set "Auto" as default input size mode by @goodsong81 in #2515
• Correct artifact csv name by @yunchu in #2516
• Fix E2E tests for detection by @sungmanc in #2520
• Add skips to E2E detection tests by @sungmanc in #2521
• Delete mem cache handler after training is done by @eunwoosh in #2535
• Fix bug that auto batch size doesn't consider distributed training by @eunwoosh in #2533
• Apply fix progress hook to release 1.5.0 by @sungmanc in #2539
• Mirror Anomaly ModelAPI changes by @ashwinvaidya17 in #2531
• Re-introduce adaptive training by @jaegukhyun in #2543
• Fix auto input size mismatch in eval & export by @goodsong81 in #2530
• Update ref. fq number for anomaly e2e2 by @yunchu in #2547
• Skip e2e det tests by issue2548 by @yunchu in #2550
• Add skip to chained TC for issue #2548 by @yunchu in #2552

Full Changelog: 1.4.3...1.5.0rc1