00【mmaction2 行为识别商用级别】快速搭建mmaction2 pytorch 1.6.0与 pytorch 1.8.0 版本，faster rcnn 与 slowfast

github（新版）：https://github.com/Whiffe/mmaction2_YF
码云（新版）：https://gitee.com/YFwinston/mmaction2_YF.git
github（老版本）：https://github.com/Whiffe/YF-OpenLib-mmaction2
码云（老版本）：https://gitee.com/YFwinston/YF-OpenLib-mmaction2.git
mmaction2 官网：https://github.com/open-mmlab/mmaction2
平台：极链AI
b站：https://www.bilibili.com/video/BV1tb4y1b7cy#reply5831466042

之前的mmaction2项目：【mmaction2 slowfast 行为分析(商用级别)】总目录

本系列的链接

00【mmaction2 行为识别商用级别】快速搭建mmaction2 pytorch 1.6.0与 pytorch 1.8.0 版本

03【mmaction2 行为识别商用级别】使用mmaction搭建faster rcnn批量检测图片输出为via格式

04【mmaction2 行为识别商用级别】slowfast检测算法使用yolov3来检测人

08【mmaction2 行为识别商用级别】自定义ava数据集 之 将视频裁剪为帧

12【mmaction2 行为识别商用级别】X3D复现 demo实现 检测自己的视频 Expanding Architecturesfor Efficient Video Recognition

前言

为什么会有2个版本呢，原因就在于老版本的pytorch时1.6.0，新版本的pytorch是1.8.0
这一个博客我们会快速搭建老版mmaction2与新版本mmaction2
老版本和新版本只是我按照我的项目环境来区别的

快速搭建mmaction2有多种方式
我从4个方向来讲：
1，pytorch=1.6.0 搭建mmaction2 使用AI平台
2，pytorch=1.6.0 搭建mmaction2
3，pytorch=1.8.0 搭建mmaction2 使用AI平台
2，pytorch=1.8.0 搭建mmaction2

一，mmaction2 pytorch=1.6.0 使用AI平台

1.1 在AI平台上选择镜像

极链AI

1.2 项目下载

cd home
git clone https://gitee.com/YFwinston/YF-OpenLib-mmaction2.git

1.3 环境搭建+权重下载

复制下面的内容到终端运行

pip install mmcv-full==1.2.7 -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.6.0/index.html
pip install mmpycocotools
pip install moviepy  opencv-python terminaltables seaborn decord -i https://pypi.douban.com/simple
pip install colorama

cd YF-OpenLib-mmaction2/

python setup.py develop

wget https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_2x_coco/faster_rcnn_r50_fpn_2x_coco_bbox_mAP-0.384_20200504_210434-a5d8aa15.pth -P ./Checkpionts/mmdetection/

wget https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb/slowfast_r50_8x8x1_256e_kinetics400_rgb_20200716-73547d2b.pth -P ./Checkpionts/mmaction/

1.4 测试

python demo/demo_spatiotemporal_det.py --config configs/detection/ava/slowfast_kinetics_pretrained_r50_8x8x1_20e_ava_rgb.py --checkpoint Checkpionts/mmaction/slowfast_r50_8x8x1_256e_kinetics400_rgb_20200716-73547d2b.pth --det-config demo/faster_rcnn_r50_fpn_2x_coco.py  --det-checkpoint Checkpionts/mmdetection/faster_rcnn_r50_fpn_2x_coco_bbox_mAP-0.384_20200504_210434-a5d8aa15.pth   --video demo/demo.mp4  --out-filename demo/demoOut.mp4  --det-score-thr 0.9 --action-score-thr 0.5 --output-stepsize 4  --output-fps 6

二，mmaction2 pytorch=1.6.0

2.1 创建环境

conda create -n mmaction  -y python=3.6

2.2 激活环境

conda activate mmaction

2.3 项目下载

cd home
git clone https://gitee.com/YFwinston/YF-OpenLib-mmaction2.git

2.3 环境搭建+权重下载

复制下面的内容到终端运行

pip install torch==1.6.0+cu101 torchvision==0.7.0+cu102 -f https://download.pytorch.org/whl/torch_stable.html

pip install mmcv-full==1.2.7 -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.6.0/index.html
pip install mmpycocotools
pip install moviepy  opencv-python terminaltables seaborn decord -i https://pypi.douban.com/simple
pip install colorama

cd YF-OpenLib-mmaction2/

python setup.py develop

wget https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_2x_coco/faster_rcnn_r50_fpn_2x_coco_bbox_mAP-0.384_20200504_210434-a5d8aa15.pth -P ./Checkpionts/mmdetection/

wget https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb/slowfast_r50_8x8x1_256e_kinetics400_rgb_20200716-73547d2b.pth -P ./Checkpionts/mmaction/

2.4 测试（faster rcnn + slowfast）

python demo/demo_spatiotemporal_det.py --config configs/detection/ava/slowfast_kinetics_pretrained_r50_8x8x1_20e_ava_rgb.py --checkpoint Checkpionts/mmaction/slowfast_r50_8x8x1_256e_kinetics400_rgb_20200716-73547d2b.pth --det-config demo/faster_rcnn_r50_fpn_2x_coco.py  --det-checkpoint Checkpionts/mmdetection/faster_rcnn_r50_fpn_2x_coco_bbox_mAP-0.384_20200504_210434-a5d8aa15.pth   --video demo/demo.mp4  --out-filename demo/demoOut.mp4  --det-score-thr 0.9 --action-score-thr 0.5 --output-stepsize 4  --output-fps 6

三，mmaction2 pytorch=1.8.0 使用AI平台

3.1 在AI平台上选择镜像

极链AI

3.2 项目下载

cd home
git clone https://gitee.com/YFwinston/mmaction2_YF.git

3.3 环境搭建+权重下载

复制下面的内容到终端运行

pip install mmcv-full==1.3.8 -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.8.0/index.html
pip install mmpycocotools
pip install moviepy  opencv-python terminaltables seaborn decord -i https://pypi.douban.com/simple
pip install colorama

cd mmaction2_YF/

python setup.py develop

wget https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_2x_coco/faster_rcnn_r50_fpn_2x_coco_bbox_mAP-0.384_20200504_210434-a5d8aa15.pth -P ./Checkpionts/mmdetection/

wget https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb/slowfast_r50_8x8x1_256e_kinetics400_rgb_20200716-73547d2b.pth -P ./Checkpionts/mmaction/

3.4 测试

python demo/demo_spatiotemporal_det.py --config configs/detection/ava/slowfast_kinetics_pretrained_r50_8x8x1_20e_ava_rgb.py --checkpoint Checkpionts/mmaction/slowfast_r50_8x8x1_256e_kinetics400_rgb_20200716-73547d2b.pth --det-config demo/faster_rcnn_r50_fpn_2x_coco.py  --det-checkpoint Checkpionts/mmdetection/faster_rcnn_r50_fpn_2x_coco_bbox_mAP-0.384_20200504_210434-a5d8aa15.pth   --video demo/demo.mp4  --out-filename demo/demoOut.mp4  --det-score-thr 0.9 --action-score-thr 0.5 --output-stepsize 4  --output-fps 6

四，mmaction2 pytorch=1.8.0

3.1 创建环境

conda create -n mmaction  -y python=3.8

3.2 激活环境

conda activate mmaction

3.3 项目下载

cd home
git clone https://gitee.com/YFwinston/mmaction2_YF.git

3.4 环境搭建+权重下载

复制下面的内容到终端运行

pip install torch==1.8.0+cu111 torchvision==0.9.0+cu111 -f https://download.pytorch.org/whl/torch_stable.html

pip install mmcv-full==1.3.8 -f https://download.openmmlab.com/mmcv/dist/cu111/torch1.8.0/index.html
pip install mmpycocotools
pip install moviepy  opencv-python terminaltables seaborn decord -i https://pypi.douban.com/simple
pip install colorama

cd mmaction2_YF/

python setup.py develop

wget https://download.openmmlab.com/mmdetection/v2.0/faster_rcnn/faster_rcnn_r50_fpn_2x_coco/faster_rcnn_r50_fpn_2x_coco_bbox_mAP-0.384_20200504_210434-a5d8aa15.pth -P ./Checkpionts/mmdetection/

wget https://download.openmmlab.com/mmaction/recognition/slowfast/slowfast_r50_8x8x1_256e_kinetics400_rgb/slowfast_r50_8x8x1_256e_kinetics400_rgb_20200716-73547d2b.pth -P ./Checkpionts/mmaction/

3.5 测试

python demo/demo_spatiotemporal_det.py --config configs/detection/ava/slowfast_kinetics_pretrained_r50_8x8x1_20e_ava_rgb.py --checkpoint Checkpionts/mmaction/slowfast_r50_8x8x1_256e_kinetics400_rgb_20200716-73547d2b.pth --det-config demo/faster_rcnn_r50_fpn_2x_coco.py  --det-checkpoint Checkpionts/mmdetection/faster_rcnn_r50_fpn_2x_coco_bbox_mAP-0.384_20200504_210434-a5d8aa15.pth   --video demo/demo.mp4  --out-filename demo/demoOut.mp4  --det-score-thr 0.9 --action-score-thr 0.5 --output-stepsize 4  --output-fps 6

错误解决

如果出现一下错误：

---------------------------------------------------------------------------
ImportError                               Traceback (most recent call last)
<ipython-input-1-c8ec22b3e787> in <module>
----> 1 import cv2

/opt/conda/lib/python3.8/site-packages/cv2/__init__.py in <module>
      7 
      8 from .cv2 import *
----> 9 from .cv2 import _registerMatType
     10 from . import mat_wrapper
     11 from . import gapi

ImportError: cannot import name '_registerMatType' from 'cv2.cv2' (/opt/conda/lib/python3.8/site-packages/cv2/cv2.cpython-38-x86_64-linux-gnu.so)

在终端运行：

opencv-python-headless==4.1.2.30