openpose

最新推荐文章于 2025-05-30 09:18:14 发布

原创最新推荐文章于 2025-05-30 09:18:14 发布 · 671 阅读

2 ·

CC 4.0 BY-SA版权

文章标签：

#openpose #Unbuntu #安装

深度学习同时被 3 个专栏收录

73 篇文章

订阅专栏

算法

48 篇文章

订阅专栏

工具

37 篇文章

订阅专栏

本文档详细介绍了在Ubuntu系统中编译安装OpenPose的步骤，包括下载源码、配置子模块、解决依赖问题、编译错误以及安装过程。同时，提供了OpenPose的测试和使用方法，包括不同输入输出参数的设置和JSON输出格式的解析。在安装过程中可能会遇到的问题，如找不到boost_system库，以及CUDA版本匹配等，都给出了相应的解决方案。

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

openpose编译安装

下载开源包

git clone https://github.com.cnpmjs.org/CMU-Perceptual-Computing-Lab/openpose

修改子模块的配置文件.gitmodules
同步子模块信息
```
git submodule sync
```

下载子模块

git submodule update --init --recursive

下载模型
```
cd openpose/models
./getModels.sh
```
启动cmake-gui界面
```
cd openpose
makedir build
cmake-gui
```
配置路径
出错

安装libgoogle-glog-dev
root用户下安装：

apt-get install libgoogle-glog-dev # install
apt-get remove libgoogle-glog-dev # uninstall

非root用户下安装：

#打开sudoer文件
visudo
#添加
xxx    ALL=(ALL:ALL) ALL
#退出
ctl+x
#安装
sudo apt-get install libgoogle-glog-dev

点击configure，重新配置生成。
编译
```
cd build
make -j`nproc`
```
执行make时会出现找不到boost_system的问题，可以重新编译boost，如果boost和cmake有关联，需要删掉，因为cmake可以不用安装直接解压添加环境变量使用，如果重新编译cmake会出现cmake和boost相关联，并且root用户也安装了boost库，在编译的过程中就不知道调用哪个boost库，从而导致出现问题。

注意：如果环境中是cuda-9.0，cmake-gui配置时，需要注意cuda选项是否是cuda-9.0，我的默认是cuda-8.0，不纠正该选项会出现找不到xxx.cu.o文件问题。

错误

查看启动的进程
```
ps aux | wc -l
```
通过该命令可以看到进程数一直在增加，查看输出一直在重复进行的输出如下信息。

重新下载openpose源码重新编译，不会重复出现重复Rerunning cmake after building Caffe submodule模块，运行成功。

生成

# 安装到默认目录
make install 
# 安装到指定目录
make install DESTDIR=/mnt/disk2/xxx/smb-share/soft/openpose

测试
在openpose根目录下执行如下命令

./build/examples/openpose/openpose.bin  --video examples/media/video.avi

openpose 使用

输入输出参数

输入参数

# 输入参数
# Running on Images, Video, or Webcam
--image_dir : image path
--video : video path
--camera : camera number
# Face and Hands
--face : detect face point
--hand : detect hand point
# Not Running All GPUs
--num_gpu : sets the number of total GPUs
--num_gpu_start : the first GPU to use
# Maximum Accuracy Configuration
# this command provides the most accurate results we have been able to achieve for body, hand and face keypoint detection.
--net_resolution
--scale_number
--scale_gap

# Running on Images, Video, or Webcam
./build/examples/openpose/openpose.sh --image_dir examples/media/
./build/examples/openpose/openpose.sh --video examples/media/video.avi
./build/example/openpose/openpose.sh --camera 0
# Face and Hands
./build/examples/openpose/openpose.bin --image_dir examples/media/ --face --hand
./build/examples/openpose/openpose.bin --video examples/media/video.avi --face --hand
./build/examples/openpose/openpose.bin --face --hand
# Not Running All GPUs
./build/examples/openpose/openpose.bin --video examples/media/video.avi --num_gpu 2 --num_gpu_start 1
# Maximum Accuracy Configuration
# Ubuntu and Mac: Body
./build/examples/openpose/openpose.bin --net_resolution "1312x736" --scale_number 4 --scale_gap 0.25
# Ubuntu and Mac: Body + Hand + Face
./build/examples/openpose/openpose.bin --net_resolution "1312x736" --scale_number 4 --scale_gap 0.25 --hand --hand_scale_number 6 --hand_scale_range 0.4 --face

在这里插入图片描述

输出参数

# 输出参数
# Different Outputs(JSON, Images, Video, UI)
--write_json : output json path
--write_video : output video path
--write_images : output image path
--write_images_format : write images format
--display : disable the UI visualization or not
--render_pose : overlay skeletons with the input images or not
# Only Skeleton without Background Image
--disable_blending : visualize/save the skeleton without the original image overlaid or blended

# Different Outputs(JSON, Images, Video, UI)
# Save the skeletons in a set of JSON files
# Ubuntu and Mac (same flags for Windows)
./build/examples/openpose/openpose.bin --image_dir examples/media/ --write_json output_jsons/
./build/examples/openpose/openpose.bin --video examples/media/video.avi --write_json output_jsons/
./build/examples/openpose/openpose.bin --write_json output_jsons/
# Save on disk the visual output of OpenPose (the images with the skeletons overlaid) as an output video or set of images 
# Ubuntu and Mac (same flags for Windows)
./build/examples/openpose/openpose.bin --video examples/media/video.avi --write_video output/result.avi
./build/examples/openpose/openpose.bin --image_dir examples/media/ --write_video output/result.avi
./build/examples/openpose/openpose.bin --video examples/media/video.avi --write_images output_images/
./build/examples/openpose/openpose.bin --video examples/media/video.avi --write_images output_images/ --write_images_format jpg
./build/examples/openpose/openpose.bin --image_dir examples/media/ --write_images output_images/
./build/examples/openpose/openpose.bin --image_dir examples/media/ --write_images output_images/ --write_images_format jpg
# You can also disable the UI visualization
# Ubuntu and Mac (same flags for Windows)
./build/examples/openpose/openpose.bin --video examples/media/video.avi --write_images output_images/ --display 0
# To speed up OpenPose even further 
# Ubuntu and Mac (same flags for Windows)
./build/examples/openpose/openpose.bin --video examples/media/video.avi --write_json output_jsons/ --display 0 --render_pose 0
# Only Skeleton without Background Image
# Ubuntu and Mac (same flags for Windows)
# Only body
./build/examples/openpose/openpose.bin --video examples/media/video.avi --disable_blending

输入输出文件

JSON-UI Mapping
在这里插入图片描述

JSON Output Format
在这里插入图片描述

# 官网给出的
{
    "version":1.1,
    "people":[
        {
            "pose_keypoints_2d":[582.349,507.866,0.845918,746.975,631.307,0.587007,...],
            "face_keypoints_2d":[468.725,715.636,0.189116,554.963,652.863,0.665039,...],
            "hand_left_keypoints_2d":[746.975,631.307,0.587007,615.659,617.567,0.377899,...],
            "hand_right_keypoints_2d":[617.581,472.65,0.797508,0,0,0,723.431,462.783,0.88765,...]
            "pose_keypoints_3d":[582.349,507.866,507.866,0.845918,507.866,746.975,631.307,0.587007,...],
            "face_keypoints_3d":[468.725,715.636,715.636,0.189116,715.636,554.963,652.863,0.665039,...],
            "hand_left_keypoints_3d":[746.975,631.307,631.307,0.587007,631.307,615.659,617.567,0.377899,...],
            "hand_right_keypoints_3d":[617.581,472.65,472.65,0.797508,472.65,0,0,0,723.431,462.783,0.88765,...]
        }
    ],
    // If `--part_candidates` enabled
    "part_candidates":[
        {
            "0":[296.994,258.976,0.845918,238.996,365.027,0.189116],
            "1":[381.024,321.984,0.587007],
            "2":[313.996,314.97,0.377899],
            "3":[238.996,365.027,0.189116],
            "4":[283.015,332.986,0.665039],
            "5":[457.987,324.003,0.430488,283.015,332.986,0.665039],
            "6":[],
            "7":[],
            "8":[],
            "9":[],
            "10":[],
            "11":[],
            "12":[],
            "13":[],
            "14":[293.001,242.991,0.674305],
            "15":[314.978,241,0.797508],
            "16":[],
            "17":[369.007,235.964,0.88765]
        }
    ]
}

# 测试结果
{
    "version": 1.3,
    "people": [
        {
            "person_id": [
                -1
            ],
            "pose_keypoints_2d": [
                93.4962,
                38.5496,
                0.830378,
                87.8299,
                87.1173,
                0.796927,
                49.1132,
                82.1957,
                0.658523,
                42.7829,
                149.15,
                0.651932,
                46.2776,
                206.192,
                0.696771,
                125.866,
                89.957,
                0.669954,
                132.251,
                152.643,
                0.68547,
                148.421,
                209.705,
                0.542522,
                71.6597,
                210.421,
                0.323036,
                0,
                0,
                0,
                0,
                0,
                0,
                120.965,
                207.594,
                0.36855,
                0,
                0,
                0,
                0,
                0,
                0,
                87.1342,
                30.8119,
                0.918732,
                103.341,
                31.5191,
                0.871637,
                75.8563,
                34.322,
                0.829309,
                111.12,
                37.8224,
                0.789115
            ],
            "face_keypoints_2d": [
                
            ],
            "hand_left_keypoints_2d": [
                
            ],
            "hand_right_keypoints_2d": [
                
            ],
            "pose_keypoints_3d": [
                
            ],
            "face_keypoints_3d": [
                
            ],
            "hand_left_keypoints_3d": [
                
            ],
            "hand_right_keypoints_3d": [
                
            ]
        }
    ]
}