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update mmengine/mmdet version and article (#201) 

* update mmengine and mmdet version

* update
pull/249/head
Haian Huang(深度眸) 2022-10-27 13:30:18 +08:00 committed by Haian Huang(深度眸)
parent a381c0f932
commit 89588b60fb
13 changed files with 43 additions and 21 deletions
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4
.circleci/test.yml
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@ -66,7 +66,7 @@ jobs:
name: Install mmyolo dependencies
command: |
pip install -U openmim
mim install 'mmengine == 0.1.0'
mim install 'mmengine >= 0.2.0'
mim install 'mmcv >= 2.0.0rc1'
pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
pip install -r requirements/albu.txt
@ -124,7 +124,7 @@ jobs:
name: Install mmyolo dependencies
command: |
docker exec mmyolo pip install -U openmim
docker exec mmyolo mim install 'mmengine == 0.1.0'
docker exec mmyolo mim install 'mmengine >= 0.2.0'
docker exec mmyolo mim install 'mmcv >= 2.0.0rc1'
docker exec mmyolo pip install -e /mmdetection
docker exec mmyolo pip install -r requirements/albu.txt

2
README.md
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@ -84,7 +84,7 @@ MMYOLO relies on PyTorch, MMCV, MMEngine, and MMDetection. Below are quick steps
conda create -n open-mmlab python=3.8 pytorch==1.10.1 torchvision==0.11.2 cudatoolkit=11.3 -c pytorch -y
conda activate open-mmlab
pip install openmim
mim install "mmengine==0.1.0"
mim install "mmengine>=0.2.0"
mim install "mmcv>=2.0.0rc1,<2.1.0"
mim install "mmdet>=3.0.0rc1,<3.1.0"
git clone https://github.com/open-mmlab/mmyolo.git

2
README_zh-CN.md
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@ -85,7 +85,7 @@ MMYOLO 依赖 PyTorch, MMCV, MMEngine 和 MMDetection，以下是安装的简要
conda create -n open-mmlab python=3.8 pytorch==1.10.1 torchvision==0.11.2 cudatoolkit=11.3 -c pytorch -y
conda activate open-mmlab
pip install openmim
mim install "mmengine==0.1.0"
mim install "mmengine>=0.2.0"
mim install "mmcv>=2.0.0rc1,<2.1.0"
mim install "mmdet>=3.0.0rc1,<3.1.0"
git clone https://github.com/open-mmlab/mmyolo.git

2
docker/Dockerfile
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@ -26,7 +26,7 @@ RUN apt-get update \
# Install MMEngine , MMCV and MMDet
RUN pip install --no-cache-dir openmim && \
mim install --no-cache-dir "mmengine==0.1.0" "mmcv>=2.0.0rc1,<2.1.0" "mmdet>=3.0.0rc1,<3.1.0"
mim install --no-cache-dir "mmengine>=0.2.0" "mmcv>=2.0.0rc1,<2.1.0" "mmdet>=3.0.0rc1,<3.1.0"
# Install MMYOLO
RUN git clone https://github.com/open-mmlab/mmyolo.git /mmyolo && \

7
docs/en/get_started.md
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@ -6,7 +6,8 @@ Compatible MMEngine, MMCV and MMDetection versions are shown as below. Please in
| MMYOLO version | MMDetection version | MMEngine version | MMCV version |
| :------------: | :----------------------: | :----------------------: | :---------------------: |
| main | mmdet>=3.0.0rc1, \<3.1.0 | mmengine>=0.1.0, \<0.2.0 | mmcv>=2.0.0rc0, \<2.1.0 |
| main | mmdet>=3.0.0rc1, \<3.1.0 | mmengine>=0.2.0, \<1.0.0 | mmcv>=2.0.0rc0, \<2.1.0 |
| 0.1.2 | mmdet>=3.0.0rc1, \<3.1.0 | mmengine>=0.2.0, \<1.0.0 | mmcv>=2.0.0rc0, \<2.1.0 |
| 0.1.1 | mmdet>=3.0.0rc1, \<3.1.0 | mmengine>=0.1.0, \<0.2.0 | mmcv>=2.0.0rc0, \<2.1.0 |
| 0.1.0 | mmdet>=3.0.0rc0, \<3.1.0 | mmengine>=0.1.0, \<0.2.0 | mmcv>=2.0.0rc0, \<2.1.0 |
@ -49,7 +50,7 @@ conda install pytorch torchvision cpuonly -c pytorch
```shell
pip install -U openmim
mim install "mmengine==0.1.0"
mim install "mmengine>=0.2.0"
mim install "mmcv>=2.0.0rc1,<2.1.0"
mim install "mmdet>=3.0.0rc1,<3.1.0"
```
@ -155,7 +156,7 @@ To install MMEngine with pip instead of MIM, please follow \[MMEngine installati
For example, you can install MMEngine by the following command.
```shell
pip install "mmengine==0.1.0"
pip install "mmengine>=0.2.0"
```
#### Install MMCV without MIM

4
docs/en/user_guides/yolov5_tutorial.md
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@ -10,9 +10,9 @@ conda activate open-mmlab
conda install pytorch torchvision -c pytorch
# conda install pytorch torchvision cpuonly -c pytorch
pip install -U openmim
mim install "mmengine==0.1.0"
mim install "mmengine>=0.2.0"
mim install "mmcv>=2.0.0rc1,<2.1.0"
mim install "mmdet>=3.0.0rc0,<3.1.0"
mim install "mmdet>=3.0.0rc1,<3.1.0"
# for albumentations
git clone https://github.com/open-mmlab/mmyolo.git
cd mmyolo

20
docs/zh_cn/article.md
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@ -6,7 +6,9 @@
### 文章
- [社区协作，简洁易用，快来开箱新一代 YOLO 系列开源库](https://zhuanlan.zhihu.com/p/575615805)
- [MMYOLO 社区倾情贡献，RTMDet 原理社区开发者解读来啦！](https://zhuanlan.zhihu.com/p/569777684)
- [玩转 MMYOLO 基础类第一期： 配置文件太复杂？继承用法看不懂？配置全解读来了](https://zhuanlan.zhihu.com/p/577715188)
### 视频
@ -18,18 +20,36 @@
#### 基础类
| | 内容 | 视频 | 课程中的代码/文档 |
| :---: | :--------: | :---------------------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------------------------: |
| 第1讲 | 配置全解读 | [![Link](http://i1.hdslb.com/bfs/archive/e06daf640ea39b3c0700bb4dc758f1a253f33e13.jpg@112w_63h_1c.webp)](https://www.bilibili.com/video/BV1214y157ck) | [配置全解读文档](https://zhuanlan.zhihu.com/p/577715188) |
#### 实用类
#### 源码解读类
#### 演示类
| | 内容 | 视频 |
| :---: | :----------: | :---------------------------------------------------------------------------------------------------------------------------------------------------: |
| 第1期 | 特征图可视化 | [![Link](http://i0.hdslb.com/bfs/archive/081f300c84d6556f40d984cfbe801fc0644ff449.jpg@112w_63h_1c.webp)](https://www.bilibili.com/video/BV1214y157ck) |
## MMEngine 解读文章和资源
- [从 MMCV 到 MMEngine，架构升级，体验升级！](https://zhuanlan.zhihu.com/p/571830155)
## MMCV 解读文章和资源
- [MMCV 全新升级，新增超全数据变换功能，还有两大变化](https://zhuanlan.zhihu.com/p/572550592)
- [手把手教你如何高效地在 MMCV 中贡献算子](https://zhuanlan.zhihu.com/p/464492627)
## MMDetection 解读文章和资源
## 文章
- [MMDetection 3.0：目标检测新基准与前沿](https://zhuanlan.zhihu.com/p/575246786)
- [MMDetection 支持数据增强神器 Simple Copy Paste 全过程](https://zhuanlan.zhihu.com/p/559940982)
## 知乎问答和资源
- [深度学习科研，如何高效进行代码和实验管理？](https://www.zhihu.com/question/269707221/answer/2480772257)

7
docs/zh_cn/get_started.md
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@ -6,7 +6,8 @@
| MMYOLO version | MMDetection version | MMEngine version | MMCV version |
| :------------: | :----------------------: | :----------------------: | :---------------------: |
| main | mmdet>=3.0.0rc1, \<3.1.0 | mmengine>=0.1.0, \<0.2.0 | mmcv>=2.0.0rc0, \<2.1.0 |
| main | mmdet>=3.0.0rc1, \<3.1.0 | mmengine>=0.2.0, \<1.0.0 | mmcv>=2.0.0rc0, \<2.1.0 |
| 0.1.2 | mmdet>=3.0.0rc1, \<3.1.0 | mmengine>=0.2.0, \<1.0.0 | mmcv>=2.0.0rc0, \<2.1.0 |
| 0.1.1 | mmdet>=3.0.0rc1, \<3.1.0 | mmengine>=0.1.0, \<0.2.0 | mmcv>=2.0.0rc0, \<2.1.0 |
| 0.1.0 | mmdet>=3.0.0rc0, \<3.1.0 | mmengine>=0.1.0, \<0.2.0 | mmcv>=2.0.0rc0, \<2.1.0 |
@ -49,7 +50,7 @@ conda install pytorch torchvision cpuonly -c pytorch
```shell
pip install -U openmim
mim install "mmengine==0.1.0"
mim install "mmengine>=0.2.0"
mim install "mmcv>=2.0.0rc1,<2.1.0"
mim install "mmdet>=3.0.0rc1,<3.1.0"
```
@ -157,7 +158,7 @@ inference_detector(model, 'demo/demo.jpg')
例如，你可以通过以下命令安装 MMEngine：
```shell
pip install "mmengine==0.1.0"
pip install "mmengine>=0.2.0"
```
#### 不使用 MIM 安装 MMCV

4
docs/zh_cn/user_guides/yolov5_tutorial.md
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@ -10,9 +10,9 @@ conda activate open-mmlab
conda install pytorch torchvision -c pytorch
# conda install pytorch torchvision cpuonly -c pytorch
pip install -U openmim
mim install "mmengine==0.1.0"
mim install "mmengine>=0.2.0"
mim install "mmcv>=2.0.0rc1,<2.1.0"
mim install "mmdet>=3.0.0rc0,<3.1.0"
mim install "mmdet>=3.0.0rc1,<3.1.0"
# for albumentations
git clone https://github.com/open-mmlab/mmyolo.git
cd mmyolo

2
mmyolo/__init__.py
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@ -10,7 +10,7 @@ mmcv_minimum_version = '2.0.0rc0'
mmcv_maximum_version = '2.1.0'
mmcv_version = digit_version(mmcv.__version__)
mmengine_minimum_version = '0.1.0'
mmengine_minimum_version = '0.2.0'
mmengine_maximum_version = '1.0.0'
mmengine_version = digit_version(mmengine.__version__)

2
mmyolo/version.py
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@ -1,6 +1,6 @@
# Copyright (c) OpenMMLab. All rights reserved.
__version__ = '0.1.1'
__version__ = '0.1.2'
from typing import Tuple

4
requirements/mminstall.txt
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@ -1,3 +1,3 @@
mmcv>=2.0.0rc1,<2.1.0
mmdet>=3.0.0rc0
mmengine==0.1.0
mmdet>=3.0.0rc1
mmengine>=0.2.0

4
requirements/readthedocs.txt
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@ -1,5 +1,5 @@
mmcv>=2.0.0rc1,<2.1.0
mmdet>=3.0.0rc0
mmengine==0.1.0
mmdet>=3.0.0rc1
mmengine>=0.2.0
torch
torchvision