Update for release 1.4 (#2380)

* updated for 1.4.0rc3

* update changelog & release note

* bump datumaro version up

---------

Co-authored-by: Songki Choi <songki.choi@intel.com>

CHANGELOG.md

@@ -8,32 +8,31 @@ All notable changes to this project will be documented in this file.
 
 - Support encrypted dataset training (<https://github.com/openvinotoolkit/training_extensions/pull/2209>)
 - Add custom max iou assigner to prevent CPU OOM when large annotations are used (<https://github.com/openvinotoolkit/training_extensions/pull/2228>)
-- Auto train type detection for Semi-SL, Self-SL and Incremental: "--train-type" now is optional (https://github.com/openvinotoolkit/training_extensions/pull/2195)
-- Add per-class XAI saliency maps for Mask R-CNN model (https://github.com/openvinotoolkit/training_extensions/pull/2227)
+- Auto train type detection for Semi-SL, Self-SL and Incremental: "--train-type" now is optional (<https://github.com/openvinotoolkit/training_extensions/pull/2195>)
+- Add per-class XAI saliency maps for Mask R-CNN model (<https://github.com/openvinotoolkit/training_extensions/pull/2227>)
 - Add new object detector Deformable DETR (<https://github.com/openvinotoolkit/training_extensions/pull/2249>)
-- Add new object detector DINO(<https://github.com/openvinotoolkit/training_extensions/pull/2266>)
-- Add new visual prompting task: train/eval (https://github.com/openvinotoolkit/training_extensions/pull/2203)
-- Add new visual prompting task: export (https://github.com/openvinotoolkit/training_extensions/pull/2274)
-- Add new visual prompting task: deploy (https://github.com/openvinotoolkit/training_extensions/pull/2311)
-- Add new visual prompting task: documentation (https://github.com/openvinotoolkit/training_extensions/pull/2354)
-- Add new visual prompting task: optimize (PTQ) (https://github.com/openvinotoolkit/training_extensions/pull/2318)
+- Add new object detector DINO (<https://github.com/openvinotoolkit/training_extensions/pull/2266>)
+- Add new visual prompting task (<https://github.com/openvinotoolkit/training_extensions/pull/2203>, <https://github.com/openvinotoolkit/training_extensions/pull/2274>, <https://github.com/openvinotoolkit/training_extensions/pull/2311>, <https://github.com/openvinotoolkit/training_extensions/pull/2354>, <https://github.com/openvinotoolkit/training_extensions/pull/2318>)
 - Add new object detector ResNeXt101-ATSS (<https://github.com/openvinotoolkit/training_extensions/pull/2309>)
 
 ### Enhancements
 
 - Introduce channel_last parameter to improve the performance (<https://github.com/openvinotoolkit/training_extensions/pull/2205>)
-- Decrease a time for making a workspace (<https://github.com/openvinotoolkit/training_extensions/pull/2223>)
+- Decrease time for making a workspace (<https://github.com/openvinotoolkit/training_extensions/pull/2223>)
 - Set persistent_workers and pin_memory as True in detection task (<https://github.com/openvinotoolkit/training_extensions/pull/2224>)
-- New algorithm for Semi-SL semantic segmentation based on metric lerning via class prototypes (https://github.com/openvinotoolkit/training_extensions/pull/2156)
-- Self-SL for classification now can recieve just folder with any images to start contrastive pretraining (https://github.com/openvinotoolkit/training_extensions/pull/2219)
+- New algorithm for Semi-SL semantic segmentation based on metric learning via class prototypes (<https://github.com/openvinotoolkit/training_extensions/pull/2156>)
+- Self-SL for classification now can recieve just folder with any images to start contrastive pretraining (<https://github.com/openvinotoolkit/training_extensions/pull/2219>)
 - Update OpenVINO version to 2023.0, and NNCF verion to 2.5 (<https://github.com/openvinotoolkit/training_extensions/pull/2090>)
-- Improve XAI saliency map generation for tiling detection and tiling instance segmentation (https://github.com/openvinotoolkit/training_extensions/pull/2240)
+- Improve XAI saliency map generation for tiling detection and tiling instance segmentation (<https://github.com/openvinotoolkit/training_extensions/pull/2240>)
+- Remove CenterCrop from Classification test pipeline and editing missing docs link(<https://github.com/openvinotoolkit/training_extensions/pull/2375>)
 
 ### Bug fixes
 
 - Fix the bug that auto adapt batch size is unavailable with IterBasedRunner (<https://github.com/openvinotoolkit/training_extensions/pull/2182>)
 - Fix the bug that learning rate isn't scaled when multi-GPU trianing is enabled(<https://github.com/openvinotoolkit/training_extensions/pull/2254>)
 - Fix the bug that label order is misaligned when model is deployed from Geti (<https://github.com/openvinotoolkit/training_extensions/pull/2369>)
+- Fix NNCF training on CPU (<https://github.com/openvinotoolkit/training_extensions/pull/2373>)
+- Fix H-label classification (<https://github.com/openvinotoolkit/training_extensions/pull/2377>)
 
 ### Known issues
 

docs/source/guide/release_notes/index.rst

@@ -1,6 +1,19 @@
 Releases
 ========
 
+***************
+[v1.4.0] (3Q23)
+***************
+
+- Support encrypted dataset training
+- Add custom max iou assigner to prevent CPU OOM when large annotations are used
+- Auto train type detection for Semi-SL, Self-SL and Incremental: "--train-type" now is optional
+- Add per-class XAI saliency maps for Mask R-CNN model
+- Add new object detector Deformable DETR
+- Add new object detector DINO
+- Add new visual prompting task
+- Add new object detector ResNeXt101-ATSS
+
 ***************
 [v1.3.0] (2Q23)
 ***************

requirements/base.txt

@@ -4,7 +4,7 @@ natsort>=6.0.0
 prettytable
 protobuf>=3.20.0
 pyyaml
-datumaro==1.4.0rc3
+datumaro==1.4.0rc4
 psutil
 scipy>=1.8
 bayesian-optimization>=1.2.0

src/otx/__init__.py

@@ -3,5 +3,5 @@
 # Copyright (C) 2021-2023 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
-__version__ = "1.4.0rc2"
+__version__ = "1.4.0rc3"
 # NOTE: Sync w/ src/otx/api/usecases/exportable_code/demo/requirements.txt on release

src/otx/api/usecases/exportable_code/demo/requirements.txt

@@ -1,4 +1,4 @@
 openvino==2023.0
 openvino-model-api==0.1.3
-otx==1.4.0rc2
+otx==1.4.0rc3
 numpy>=1.21.0,<=1.23.5  # np.bool was removed in 1.24.0 which was used in openvino runtime