Bump to v2.5.0

docs/changelog.md

@@ -1,5 +1,60 @@
 ## Changelog
 
+### v2.5.0 (5/10/2020)
+
+#### Highlights
+
+- Support new methods: [YOLACT](https://arxiv.org/abs/1904.02689), [CentripetalNet](https://arxiv.org/abs/2003.09119).
+- Add more documentations for easier and more clear usage.
+
+#### Backwards Incompatible Changes
+
+**FP16 related methods are imported from mmcv instead of mmdet. (#3766, #3822)**
+Mixed precision training utils in `mmdet.core.fp16` are moved to `mmcv.runner`, including `force_fp32`, `auto_fp16`, `wrap_fp16_model`, and `Fp16OptimizerHook`. A deprecation warning will be raised if users attempt to import those methods from `mmdet.core.fp16`, and will be finally removed in V2.8.0.
+
+**[0, N-1] represents foreground classes and N indicates background classes for all models. (#3221)**
+Before v2.5.0, the background label for RPN is 0, and N for other heads. Now the behavior is consistent for all models. Thus `self.background_labels` in `dense_heads` is removed and all heads use `self.num_classes` to indicate the class index of background labels.
+This change has no effect on the pre-trained models in the v2.x model zoo, but will affect the training of all models with RPN heads. Two-stage detectors whose RPN head uses softmax will be affected because the order of categories is changed.
+
+**Only call `get_subset_by_classes` when `test_mode=True` and `self.filter_empty_gt=True` (#3695)**
+Function `get_subset_by_classes` in dataset is refactored and only filters out images when `test_mode=True` and `self.filter_empty_gt=True`.
+    In the original implementation, `get_subset_by_classes` is not related to the flag `self.filter_empty_gt` and will only be called when the classes is set during initialization no matter `test_mode` is `True` or `False`. This brings ambiguous behavior and potential bugs in many cases. After v2.5.0, if `filter_empty_gt=False`, no matter whether the classes are specified in a dataset, the dataset will use all the images in the annotations. If `filter_empty_gt=True` and `test_mode=True`, no matter whether the classes are specified, the dataset will call ``get_subset_by_classes` to check the images and filter out images containing no GT boxes. Therefore, the users should be responsible for the data filtering/cleaning process for the test dataset.
+
+#### New Features
+
+- Test time augmentation for single stage detectors (#3844, #3638)
+- Support to show the name of experiments during training (#3764)
+- Add `Shear`, `Rotate`, `Translate` Augmentation (#3656, #3619, #3687)
+- Add image-only transformations including `Constrast`, `Equalize`, `Color`, and `Brightness`. (#3643)
+- Support [YOLACT](https://arxiv.org/abs/1904.02689) (#3456)
+- Support [CentripetalNet](https://arxiv.org/abs/2003.09119) (#3390)
+- Support PyTorch 1.6 in docker (#3905)
+
+#### Bug Fixes
+
+- Fix the bug of training ATSS when there is no ground truth boxes (#3702)
+- Fix the bug of using Focal Loss when there is `num_pos` is 0 (#3702)
+- Fix the label index mapping in dataset browser (#3708)
+- Fix Mask R-CNN training stuck problem when ther is no positive rois (#3713)
+- Fix the bug of `self.rpn_head.test_cfg` in `RPNTestMixin` by using `self.rpn_head` in rpn head (#3808)
+- Fix deprecated `Conv2d` from mmcv.ops (#3791)
+- Fix device bug in RepPoints (#3836)
+- Fix SABL validating bug (#3849)
+- Use `https://download.openmmlab.com/mmcv/dist/index.html` for installing MMCV (#3840)
+- Fix nonzero in NMS for PyTorch 1.6.0 (#3867)
+- Fix the API change bug of PAA (#3883)
+- Fix typo in bbox_flip (#3886)
+- Fix cv2 import error of ligGL.so.1 in Dockerfile (#3891)
+
+#### Improvements
+
+- Change to use `mmcv.utils.collect_env` for collecting environment information to avoid duplicate codes (#3779)
+- Update checkpoint file names to v2.0 models in documentation (#3795)
+- Update tutorials for changing runtime settings (#3778), modifing loss (#3777)
+- Improve the function of `simple_test_bboxes` in SABL (#3853)
+- Convert mask to bool before using it as img's index for robustness and speedup (#3870)
+- Improve documentation of modules and dataset customization (#3821)
+
 ### v2.4.0 (5/9/2020)
 
 **Highlights**
@@ -57,7 +112,6 @@ This change influences all the test APIs in MMDetection and downstream codebases
 - Update urls to download.openmmlab.com (#3665)
 - Support non-mask training for CocoDataset (#3711)
 
-
 ### v2.3.0 (5/8/2020)
 
 **Highlights**

docs/install.md

@@ -73,6 +73,7 @@ pip install mmcv-full
 | MMDetection version |    MMCV version     |
 |:-------------------:|:-------------------:|
 | master              | mmcv-full>=1.1.5, <=1.2|
+| 2.5.0               | mmcv-full>=1.1.5, <=1.2|
 | 2.4.0               | mmcv-full>=1.1.1, <=1.2|
 | 2.3.0               | mmcv-full==1.0.5|
 | 2.3.0rc0            | mmcv-full>=1.0.2    |

mmdet/version.py

@@ -1,6 +1,6 @@
 # Copyright (c) Open-MMLab. All rights reserved.
 
-__version__ = '2.4.0'
+__version__ = '2.5.0'
 short_version = __version__