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16 changes: 8 additions & 8 deletions README.md
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<img src="https://user-images.githubusercontent.com/12907710/137271636-56ba1cd2-b110-4812-8221-b4c120320aa9.png"/>


[📘Documentation](https://mmdetection.readthedocs.io/en/v2.18.0/) |
[🛠️Installation](https://mmdetection.readthedocs.io/en/v2.18.0/get_started.html) |
[👀Model Zoo](https://mmdetection.readthedocs.io/zh_CN/v2.18.0/model_zoo.html) |
[🆕Update News](https://mmdetection.readthedocs.io/en/v2.18.0/changelog.html) |
[📘Documentation](https://mmdetection.readthedocs.io/en/v2.18.1/) |
[🛠️Installation](https://mmdetection.readthedocs.io/en/v2.18.1/get_started.html) |
[👀Model Zoo](https://mmdetection.readthedocs.io/zh_CN/v2.18.1/model_zoo.html) |
[🆕Update News](https://mmdetection.readthedocs.io/en/v2.18.1/changelog.html) |
[🚀Ongoing Projects](https://github.com/open-mmlab/mmdetection/projects) |
[🤔Reporting Issues](https://github.com/open-mmlab/mmdetection/issues/new/choose)

Expand Down Expand Up @@ -60,10 +60,10 @@ This project is released under the [Apache 2.0 license](LICENSE).

## Changelog

**2.18.0** was released in 27/10/2021:
- Support [QueryInst](http://arxiv.org/abs/2105.01928).
- Refactor dense_head to decouple onnx export from get_bboxes and speed up inference time.
- Support infinite sampler to accelerate training when using iter based runner.
**2.18.1** was released in 15/11/2021:
- Release [QueryInst](http://arxiv.org/abs/2105.01928) pre-trained weights.
- Support plot confusion matrix.
- Fix SpatialReductionAttention in PVT and fix trunc_normal_init in both PVT and Swin-Transformer.

Please refer to [changelog.md](docs/changelog.md) for details and release history.

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16 changes: 8 additions & 8 deletions README_zh-CN.md
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<img src="https://user-images.githubusercontent.com/12907710/137271636-56ba1cd2-b110-4812-8221-b4c120320aa9.png"/>


[📘使用文档](https://mmdetection.readthedocs.io/zh_CN/v2.18.0/) |
[🛠️安装教程](https://mmdetection.readthedocs.io/zh_CN/v2.18.0/get_started.html) |
[👀模型库](https://mmdetection.readthedocs.io/zh_CN/v2.18.0/model_zoo.html) |
[🆕更新日志](https://mmdetection.readthedocs.io/en/v2.18.0/changelog.html) |
[📘使用文档](https://mmdetection.readthedocs.io/zh_CN/v2.18.1/) |
[🛠️安装教程](https://mmdetection.readthedocs.io/zh_CN/v2.18.1/get_started.html) |
[👀模型库](https://mmdetection.readthedocs.io/zh_CN/v2.18.1/model_zoo.html) |
[🆕更新日志](https://mmdetection.readthedocs.io/en/v2.18.1/changelog.html) |
[🚀进行中的项目](https://github.com/open-mmlab/mmdetection/projects) |
[🤔报告问题](https://github.com/open-mmlab/mmdetection/issues/new/choose)

Expand Down Expand Up @@ -59,10 +59,10 @@ MMDetection 是一个基于 PyTorch 的目标检测开源工具箱。它是 [Ope

## 更新日志

最新的 **2.18.0** 版本已经在2021.10.27发布:
- 支持 [QueryInst](http://arxiv.org/abs/2105.01928)
- 重构 dense_head 以将 onnx 导出与 get_bboxes 解耦并加快推理时间
- 支持 infinite sampler 加速 iter based runner 训练
最新的 **2.18.1** 版本已经在2021.11.15发布:
- 发布了 [QueryInst](http://arxiv.org/abs/2105.01928) 的预训练模型
- 支持绘制混淆矩阵
- 修复了 PVT 中的 SpatialReductionAttention 以及 PVT 和 Swin-Transformer 中 trunc_normal_init 的错误用法

如果想了解更多版本更新细节和历史信息,请阅读[更新日志](docs/changelog.md)

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10 changes: 5 additions & 5 deletions configs/queryinst/README.md
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| Model | Backbone | Style | Lr schd | Number of Proposals |Multi-Scale| RandomCrop | box AP | mask AP | Config | Download |
|:------------:|:---------:|:-------:|:-------:|:-------: |:-------: |:---------:|:------:|:------:|:------:|:--------:|
| QueryInst | R-50-FPN | pytorch | 1x | 100 | False | False | 42.0 | 37.5 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/queryinst/queryinst_r50_fpn_1x_coco.py) | [model]() &#124; [log]() |
| QueryInst | R-50-FPN | pytorch | 3x | 100 | True | False | 44.8 | 39.8 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/queryinst/queryinst_r50_fpn_mstrain_480-800_3x_coco.py) | [model]() &#124; [log]() |
| QueryInst | R-50-FPN | pytorch | 3x | 300 | True | True | 47.5 | 41.7 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/queryinst/queryinst_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py) | [model]() &#124; [log]() |
| QueryInst | R-101-FPN | pytorch | 3x | 100 | True | False | 46.4 | 41.0 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/queryinst/queryinst_r101_fpn_mstrain_480-800_3x_coco.py) | [model]() &#124; [log]() |
| QueryInst | R-101-FPN | pytorch | 3x | 300 | True | True | 49.0 | 42.9 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/queryinst/queryinst_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py) | [model]() &#124; [log]() |
| QueryInst | R-50-FPN | pytorch | 1x | 100 | False | False | 42.0 | 37.5 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/queryinst/queryinst_r50_fpn_1x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r50_fpn_1x_coco/queryinst_r50_fpn_1x_coco_20210907_084916-5a8f1998.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r50_fpn_1x_coco/queryinst_r50_fpn_1x_coco_20210907_084916.log.json) |
| QueryInst | R-50-FPN | pytorch | 3x | 100 | True | False | 44.8 | 39.8 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/queryinst/queryinst_r50_fpn_mstrain_480-800_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r50_fpn_mstrain_480-800_3x_coco/queryinst_r50_fpn_mstrain_480-800_3x_coco_20210901_103643-7837af86.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r50_fpn_mstrain_480-800_3x_coco/queryinst_r50_fpn_mstrain_480-800_3x_coco_20210901_103643.log.json) |
| QueryInst | R-50-FPN | pytorch | 3x | 300 | True | True | 47.5 | 41.7 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/queryinst/queryinst_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco/queryinst_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco_20210904_101802-85cffbd8.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco/queryinst_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco_20210904_101802.log.json) |
| QueryInst | R-101-FPN | pytorch | 3x | 100 | True | False | 46.4 | 41.0 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/queryinst/queryinst_r101_fpn_mstrain_480-800_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r101_fpn_mstrain_480-800_3x_coco/queryinst_r101_fpn_mstrain_480-800_3x_coco_20210904_104048-91f9995b.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r101_fpn_mstrain_480-800_3x_coco/queryinst_r101_fpn_mstrain_480-800_3x_coco_20210904_104048.log.json) |
| QueryInst | R-101-FPN | pytorch | 3x | 300 | True | True | 49.0 | 42.9 | [config](https://github.com/open-mmlab/mmdetection/tree/master/configs/queryinst/queryinst_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco.py) | [model](https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco/queryinst_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco_20210904_153621-76cce59f.pth) &#124; [log](https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco/queryinst_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco_20210904_153621.log.json) |
10 changes: 5 additions & 5 deletions configs/queryinst/metafile.yml
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Expand Up @@ -33,7 +33,7 @@ Models:
Dataset: COCO
Metrics:
mask AP: 37.5
Weights:
Weights: https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r50_fpn_1x_coco/queryinst_r50_fpn_1x_coco_20210907_084916-5a8f1998.pth

- Name: queryinst_r50_fpn_mstrain_480-800_3x_coco
In Collection: QueryInst
Expand All @@ -49,7 +49,7 @@ Models:
Dataset: COCO
Metrics:
mask AP: 39.8
Weights:
Weights: https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r50_fpn_mstrain_480-800_3x_coco/queryinst_r50_fpn_mstrain_480-800_3x_coco_20210901_103643-7837af86.pth

- Name: queryinst_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco
In Collection: QueryInst
Expand All @@ -65,7 +65,7 @@ Models:
Dataset: COCO
Metrics:
mask AP: 41.7
Weights:
Weights: https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco/queryinst_r50_fpn_300_proposals_crop_mstrain_480-800_3x_coco_20210904_101802-85cffbd8.pth

- Name: queryinst_r101_fpn_mstrain_480-800_3x_coco
In Collection: QueryInst
Expand All @@ -81,7 +81,7 @@ Models:
Dataset: COCO
Metrics:
mask AP: 41.0
Weights:
Weights: https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r101_fpn_mstrain_480-800_3x_coco/queryinst_r101_fpn_mstrain_480-800_3x_coco_20210904_104048-91f9995b.pth

- Name: queryinst_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco
In Collection: QueryInst
Expand All @@ -97,4 +97,4 @@ Models:
Dataset: COCO
Metrics:
mask AP: 42.9
Weights:
Weights: https://download.openmmlab.com/mmdetection/v2.0/queryinst/queryinst_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco/queryinst_r101_fpn_300_proposals_crop_mstrain_480-800_3x_coco_20210904_153621-76cce59f.pth
2 changes: 1 addition & 1 deletion docker/Dockerfile
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Expand Up @@ -13,7 +13,7 @@ RUN apt-get update && apt-get install -y ffmpeg libsm6 libxext6 git ninja-build
&& rm -rf /var/lib/apt/lists/*

# Install MMCV
RUN pip install mmcv-full==1.3.14 -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.6.0/index.html
RUN pip install mmcv-full==1.3.17 -f https://download.openmmlab.com/mmcv/dist/cu101/torch1.6.0/index.html

# Install MMDetection
RUN conda clean --all
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Expand Up @@ -3,8 +3,8 @@ ARG CUDA="10.1"
ARG CUDNN="7"
FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel

ARG MMCV="1.3.14"
ARG MMDET="2.18.0"
ARG MMCV="1.3.17"
ARG MMDET="2.18.1"

ENV PYTHONUNBUFFERED TRUE

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Expand Up @@ -257,7 +257,7 @@ For more detailed usages, please refer to the [Case 1](1_exist_data_model.md).
To test the trained model, you can simply run

```shell
python tools/test.py configs/balloon/mask_rcnn_r50_caffe_fpn_mstrain-poly_1x_balloon.py work_dirs/mask_rcnn_r50_caffe_fpn_mstrain-poly_1x_balloon.py/latest.pth --eval bbox segm
python tools/test.py configs/balloon/mask_rcnn_r50_caffe_fpn_mstrain-poly_1x_balloon.py work_dirs/mask_rcnn_r50_caffe_fpn_mstrain-poly_1x_balloon/latest.pth --eval bbox segm
```

For more detailed usages, please refer to the [Case 1](1_exist_data_model.md).
36 changes: 36 additions & 0 deletions docs/changelog.md
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## Changelog

### v2.18.1 (15/11/2021)

#### Highlights

- Release [QueryInst](http://arxiv.org/abs/2105.01928) pre-trained weights (#6460)
- Support plot confusion matrix (#6344)

#### New Features

- Release [QueryInst](http://arxiv.org/abs/2105.01928) pre-trained weights (#6460)
- Support plot confusion matrix (#6344)

#### Bug Fixes

- Fix aug test error when the number of prediction bboxes is 0 (#6398)
- Fix SpatialReductionAttention in PVT (#6488)
- Fix wrong use of `trunc_normal_init` in PVT and Swin-Transformer (#6432)

#### Improvements

- Save the printed AP information of COCO API to logger (#6505)
- Always map location to cpu when load checkpoint (#6405)
- Set a random seed when the user does not set a seed (#6457)

#### Documents

- Chinese version of [Corruption Benchmarking](docs/robustness_benchmarking.mddocs/robustness_benchmarking.md) (#6375)
- Fix config path in docs (#6396)
- Update GRoIE readme (#6401)

#### Contributors

A total of 11 developers contributed to this release.
Thanks @st9007a, @hachreak, @HarborYuan, @vealocia, @chhluo, @AndreaPi, @AronLin, @BIGWangYuDong, @hhaAndroid, @RangiLyu, @ZwwWayne


### v2.18.0 (27/10/2021)

#### Highlights
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7 changes: 7 additions & 0 deletions docs/compatibility.md
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# Compatibility of MMDetection 2.x

## MMDetection 2.18.1

### MMCV compatibility

In order to fix the wrong weight reference bug in BaseTransformerLayer, the logic in batch first mode of MultiheadAttention has been changed.
We recommend to use MMCV v1.3.17 or higher. For more details, please refer to [MMCV PR #1418](https://github.com/open-mmlab/mmcv/pull/1418).

## MMDetection 2.18.0

### DIIHead compatibility
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18 changes: 18 additions & 0 deletions docs/useful_tools.md
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Expand Up @@ -472,3 +472,21 @@ differential_evolution step 489: f(x)= 0.386625
2021-07-19 19:46:40,776 - mmdet - INFO Anchor differential evolution result:[[10, 12], [15, 30], [32, 22], [29, 59], [61, 46], [57, 116], [112, 89], [154, 198], [349, 336]]
2021-07-19 19:46:40,798 - mmdet - INFO Result saved in work_dirs/anchor_optimize_result.json
```

## Confution Matrix

A confusion matrix is a summary of prediction results.

`tools/analysis_tools/confusion_matrix.py` can analyze the prediction results and plot a confution matrix table.

First, run `tools/test.py` to save the `.pkl` detection results.

Then, run

```
python tools/analysis_tools/confusion_matrix.py ${CONFIG} ${DETECTION_RESULTS} ${SAVE_DIR} --show
```

And you will get a confution matrix like this:

![confution_matrix_example](https://user-images.githubusercontent.com/12907710/140513068-994cdbf4-3a4a-48f0-8fd8-2830d93fd963.png)
7 changes: 7 additions & 0 deletions docs_zh-CN/compatibility.md
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# MMDetection v2.x 兼容性说明

## MMDetection 2.18.1

### MMCV compatibility

为了修复 BaseTransformerLayer 中的权重引用问题, MultiheadAttention 中 batch first 的逻辑有所改变。
我们推荐使用 MMCV v1.3.17 或更高版本。 更多信息请参考 [MMCV PR #1418](https://github.com/open-mmlab/mmcv/pull/1418)

## MMDetection 2.18.0

### DIIHead 兼容性
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3 changes: 2 additions & 1 deletion docs_zh-CN/get_started.md
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Expand Up @@ -11,7 +11,8 @@ MMDetection 和 MMCV 版本兼容性如下所示,需要安装正确的 MMCV

| MMDetection 版本 | MMCV 版本 |
| :--------------: | :----------------------: |
| master | mmcv-full>=1.3.14, <1.4.0 |
| master | mmcv-full>=1.3.17, <1.4.0 |
| 2.18.1 | mmcv-full>=1.3.17, <1.4.0 |
| 2.18.0 | mmcv-full>=1.3.14, <1.4.0 |
| 2.17.0 | mmcv-full>=1.3.14, <1.4.0 |
| 2.16.0 | mmcv-full>=1.3.8, <1.4.0 |
Expand Down
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