mirror of https://github.com/open-mmlab/mmyolo.git
add v0.1.3 changelog (#275)
Haian Huang(深度眸)
huanghaian
parent
7f14183082
commit
abcde7679a
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@ -71,6 +71,11 @@ And the figure of P6 model is in [model_design.md](docs/en/algorithm_description
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## What's New
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💎 **v0.1.3** was released on 10/11/2022:
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1. Fix training failure when saving best weights based on mmengine 0.3.1
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2. Fix `add_dump_metric` error based on mmdet 3.0.0rc3
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💎 **v0.1.2** was released on 3/11/2022:
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1. Support [YOLOv5/YOLOv6/YOLOX/RTMDet deployments](https://github.com/open-mmlab/mmyolo/blob/main/configs/deploy) for ONNXRuntime and TensorRT
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@ -137,6 +142,7 @@ For different parts from MMDetection, we have also prepared user guides and adva
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- [Data flow](docs/en/advanced_guides/data_flow.md)
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- [How to](docs/en/advanced_guides/how_to.md)
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- [Plugins](docs/en/advanced_guides/plugins.md)
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## Overview of Benchmark and Model Zoo
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@ -71,6 +71,11 @@ P6 模型图详见 [model_design.md](docs/zh_CN/algorithm_descriptions/model_des
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## 最新进展
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💎 **v0.1.3** 版本已经在 2022.11.10 发布：
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1. 基于 mmengine 0.3.1 修复保存最好权重时训练失败问题
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2. 基于 mmdet 3.0.0rc3 修复 `add_dump_metric` 报错 (#253)
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💎 **v0.1.2** 版本已经在 2022.11.3 发布：
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1. 支持 ONNXRuntime 和 TensorRT 的 [YOLOv5/YOLOv6/YOLOX/RTMDet 部署](https://github.com/open-mmlab/mmyolo/blob/main/configs/deploy)
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@ -147,6 +152,7 @@ MMYOLO 用法和 MMDetection 几乎一致，所有教程都是通用的，你也
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- [数据流](docs/zh_cn/advanced_guides/data_flow.md)
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- [How to](docs/zh_cn/advanced_guides/how_to.md)
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- [插件](docs/zh_cn/advanced_guides/plugins.md)
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- [解读文章和资源汇总](docs/zh_cn/article.md)
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@ -21,10 +21,7 @@ def parse_args():
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parser.add_argument('config', help='Config file')
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parser.add_argument('checkpoint', help='Checkpoint file')
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parser.add_argument(
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'--out-dir',
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default='',
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help='Path to output directory, '
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'if the user not set this flag then will show each image')
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'--out-dir', default='./output', help='Path to output file')
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parser.add_argument(
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'--target-layers',
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default=['backbone'],
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@ -41,6 +38,8 @@ def parse_args():
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'--device', default='cuda:0', help='Device used for inference')
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parser.add_argument(
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'--score-thr', type=float, default=0.3, help='Bbox score threshold')
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parser.add_argument(
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'--show', action='store_true', help='Show the featmap results')
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parser.add_argument(
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'--channel-reduction',
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default='select_max',
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@ -112,7 +111,7 @@ def main():
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model = init_detector(args.config, args.checkpoint, device=args.device)
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if not os.path.exists(args.out_dir):
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if not os.path.exists(args.out_dir) and not args.show:
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os.mkdir(args.out_dir)
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if args.preview_model:
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@ -158,8 +157,7 @@ def main():
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filename = os.path.relpath(image_path, args.img).replace('/', '_')
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else:
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filename = os.path.basename(image_path)
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out_file = None if args.out_dir != '' else os.path.join(
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args.out_dir, filename)
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out_file = None if args.show else os.path.join(args.out_dir, filename)
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# show the results
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shown_imgs = []
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@ -183,14 +181,13 @@ def main():
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arrangement=args.arrangement)
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shown_imgs.append(shown_img)
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# Add original image
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shown_imgs.append(img)
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shown_imgs = auto_arrange_images(shown_imgs)
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progress_bar.update()
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if out_file:
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mmcv.imwrite(shown_imgs[..., ::-1], out_file)
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else:
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if args.show:
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visualizer.show(shown_imgs)
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print(f'All done!'
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@ -46,7 +46,7 @@ def main():
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if args.deploy:
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switch_to_deploy(model)
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if not os.path.exists(args.out_dir):
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if not os.path.exists(args.out_dir) and not args.show:
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os.mkdir(args.out_dir)
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# init visualizer
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@ -14,3 +14,12 @@ How to
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:maxdepth: 1
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how_to.md
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Plugins
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************************
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.. toctree::
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:maxdepth: 1
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plugins.md
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@ -0,0 +1 @@
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# Plugins
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@ -1,5 +1,30 @@
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# Changelog
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## v0.1.3（10/11/2022)
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### New Features
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1. Support CBAM plug-in and provide plug-in documentation (#246)
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2. Add YOLOv5 P6 model structure diagram and related descriptions (#273)
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### Bug Fixes
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1. Fix training failure when saving best weights based on mmengine 0.3.1
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2. Fix `add_dump_metric` error based on mmdet 3.0.0rc3 (#253)
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3. Fix backbone does not support `init_cfg` issue (#272)
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4. Change typing import method based on mmdet 3.0.0rc3 (#261)
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### Improvements
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1. `featmap_vis_demo` support for folder and url input (#248)
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2. Deploy docker file refinement (#242)
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#### Contributors
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A total of 10 developers contributed to this release.
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Thank @kitecats, @triple-Mu, @RangeKing, @PeterH0323, @Zheng-LinXiao, @tkhe, @weikai520, @zytx121, @wanghonglie, @hhaAndroid
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## v0.1.2（3/11/2022)
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### Highlights
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@ -53,3 +53,4 @@ The detailed instruction of MMYOLO is as follows.
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- [Data flow](https://mmyolo.readthedocs.io/en/latest/advanced_guides/index.html#data-flow)
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- [How to](https://mmyolo.readthedocs.io/en/latest/advanced_guides/index.html#how-to)
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- [Plugins](https://mmyolo.readthedocs.io/en/latest/advanced_guides/index.html#plugins)
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@ -14,3 +14,12 @@ How to
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:maxdepth: 1
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how_to.md
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插件
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************************
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.. toctree::
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:maxdepth: 1
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plugins.md
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@ -27,7 +27,7 @@ model = dict(
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<details open>
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<summary><b>支持的插件</b></summary>
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- [x] [CBAM](mmyolo/models/plugins)
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- [x] [CBAM](https://github.com/open-mmlab/mmyolo/blob/dev/mmyolo/models/plugins/cbam.py#L84)
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- [x] [GeneralizedAttention](https://github.com/open-mmlab/mmcv/blob/2.x/mmcv/cnn/bricks/generalized_attention.py#L13)
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- [x] [NonLocal2d](https://github.com/open-mmlab/mmcv/blob/2.x/mmcv/cnn/bricks/non_local.py#L250)
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- [x] [ContextBlock](https://github.com/open-mmlab/mmcv/blob/2.x/mmcv/cnn/bricks/context_block.py#L18)
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@ -1,5 +1,30 @@
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# 更新日志
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## v0.1.3（10/11/2022)
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### 新特性
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1. 支持 CBAM 插件并提供插件文档 (#246)
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2. 新增 YOLOv5 P6 模型结构图和相关说明 (#273)
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### Bug 修复
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1. 基于 mmengine 0.3.1 修复保存最好权重时训练失败问题
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2. 基于 mmdet 3.0.0rc3 修复 `add_dump_metric` 报错 (#253)
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3. 修复 backbone 不支持 `init_cfg` 问题 (#272)
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4. 基于 mmdet 3.0.0rc3 改变 typing 导入方式 (#261)
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### 完善
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1. `featmap_vis_demo` 支持文件夹和 url 输入 (#248)
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2. 部署 docker 文件完善 (#242)
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### 贡献者
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总共 10 位开发者参与了本次版本
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谢谢 @kitecats, @triple-Mu, @RangeKing, @PeterH0323, @Zheng-LinXiao, @tkhe, @weikai520, @zytx121, @wanghonglie, @hhaAndroid
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## v0.1.2（3/11/2022)
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### 亮点
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@ -53,5 +53,6 @@ MMYOLO 文件结构和 MMDetection 完全一致。为了能够充分复用 MMDet
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- [数据流](https://mmyolo.readthedocs.io/zh_CN/latest/advanced_guides/index.html#id1)
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- [How to](https://mmyolo.readthedocs.io/zh_CN/latest/advanced_guides/index.html#how-to)
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- [插件](https://mmyolo.readthedocs.io/zh_CN/latest/advanced_guides/index.html#id3)
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6. [解读文章和资源汇总](article.md)
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@ -10,14 +10,15 @@ from mmyolo.registry import MODELS
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class ChannelAttention(BaseModule):
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"""ChannelAttention
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"""ChannelAttention.
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Args:
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channels (int): The input (and output) channels of the
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ChannelAttention.
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reduce_ratio (int): Squeeze ratio in ChannelAttention, the intermediate
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channel will be ``int(channels/ratio)``. Default: 16.
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channel will be ``int(channels/ratio)``. Defaults to 16.
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act_cfg (dict): Config dict for activation layer
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Default: (dict(type='ReLU'), dict(type='Sigmoid')).
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Defaults to dict(type='ReLU').
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"""
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def __init__(self,
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@ -57,7 +58,7 @@ class SpatialAttention(BaseModule):
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"""SpatialAttention
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Args:
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kernel_size (int): The size of the convolution kernel in
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SpatialAttention. Default: 7.
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SpatialAttention. Defaults to 7.
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"""
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def __init__(self, kernel_size: int = 7):
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@ -82,29 +83,27 @@ class SpatialAttention(BaseModule):
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@MODELS.register_module()
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class CBAM(BaseModule):
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"""Convolutional Block Attention Module.
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"""Convolutional Block Attention Module. arxiv link:
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https://arxiv.org/abs/1807.06521v2.
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arxiv link: https://arxiv.org/abs/1807.06521v2
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Args:
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in_channels (int): The input (and output) channels of the CBAM.
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reduce_ratio (int): Squeeze ratio in ChannelAttention, the intermediate
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channel will be ``int(channels/ratio)``. Default: 16.
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channel will be ``int(channels/ratio)``. Defaults to 16.
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kernel_size (int): The size of the convolution kernel in
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SpatialAttention. Default: 7.
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SpatialAttention. Defaults to 7.
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act_cfg (dict): Config dict for activation layer in ChannelAttention
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Defaults: dict(type='ReLU').
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Defaults to dict(type='ReLU').
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init_cfg (dict or list[dict], optional): Initialization config dict.
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Defaults to None.
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"""
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def __init__(
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self,
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in_channels: int,
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reduce_ratio: int = 16,
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kernel_size: int = 7,
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act_cfg: dict = dict(type='ReLU'),
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init_cfg: OptMultiConfig = None,
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):
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def __init__(self,
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in_channels: int,
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reduce_ratio: int = 16,
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kernel_size: int = 7,
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act_cfg: dict = dict(type='ReLU'),
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init_cfg: OptMultiConfig = None):
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super().__init__(init_cfg)
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self.channel_attention = ChannelAttention(
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channels=in_channels, reduce_ratio=reduce_ratio, act_cfg=act_cfg)
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@ -1,6 +1,6 @@
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# Copyright (c) OpenMMLab. All rights reserved.
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__version__ = '0.1.2'
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__version__ = '0.1.3'
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from typing import Tuple
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