利用openpose进行手势（姿态）识别
在这里插入图片描述

1.编译源项目到windows python

需要注意的是，步骤按博客操作，需要修改地方

• 1.下载最新的源码
• 2.将博客里面的模型下载为代码中对应版本，如图所示

2.进行预测

预测视频中的手势

import cv2
import sys
import timeit
import openpose.pyopenpose as op
params = dict()
params["model_folder"] = 'openpose\\models'
# params["net_resolution"] = '128x192'
# params["render_pose"] = '1'

params["hand"] = True
params["hand_detector"] = 2
params["body"] = 0

opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
# cap = cv2.VideoCapture(0)
videodir = 'D:/py/My_work/video/2-0.mp4'
# videodir = 'D:/py/My_work/video/demo1.mp4'
cap = cv2.VideoCapture(videodir)
print('Video device Initialized.')
frame_start_time = timeit.default_timer()
frame_cnt = 0
rate = 1
handRectangles = [
        # Left/Right hands person 0
        # [
        # op.Rectangle(320.035889, 377.675049, 69.300949, 69.300949),
        # op.Rectangle(0., 0., 0., 0.),
        # ],
        # Left/Right hands person 1
        # [
        # op.Rectangle(80.155792, 407.673492, 80.812706, 80.812706),
        # op.Rectangle(46.449715, 404.559753, 98.898178, 98.898178),
        # ],
        [
        op.Rectangle(0, 0,0, 0),
        op.Rectangle(100*rate, 100*rate,300*rate, 300*rate),
        # op.Rectangle(46.449715, 404.559753, 98.898178, 98.898178),
        ],
        # Left/Right hands person 2
        # [
        # op.Rectangle(185.692673, 303.112244, 157.587555, 157.587555),
        # op.Rectangle(88.984360, 268.866547, 117.818230, 117.818230),
        # ]
    ]

while True:  # Process Image
   datum = op.Datum()
   ret, img = cap.read()  # Read camera
   img = cv2.resize(img,(int(640*rate),int(360*rate)))
   if ret == False:
          break
   imageToProcess = img
   datum.cvInputData = imageToProcess
   datum.handRectangles = handRectangles
   opWrapper.emplaceAndPop([datum])
   # print("Body keypoints: \n" + str(datum.poseKeypoints))
   m = datum.cvOutputData
   cv2.rectangle(m, (int(100*rate),int(100*rate)), (int(300*rate),int(300*rate)), (255,0,0), 3)
   cv2.imshow("Openpose Python - Press Q to Exit", m)
   frame_end_time = timeit.default_timer()
   if frame_end_time - frame_start_time > 1:
      print('fps:{}'.format(frame_cnt))
      frame_cnt = 0
      frame_start_time = frame_end_time
   frame_cnt = frame_cnt + 1
   k = cv2.waitKey(1) & 0xff
   if k == 27:
         break
cap.release()
cv2.destroyAllWindows()
exit(0)

实时预测body姿态

# From Python
# It requires OpenCV installed for Python
import sys
import cv2
import os
from sys import platform
import argparse

try:
    import openpose.pyopenpose as op
    # Flags
    parser = argparse.ArgumentParser()
    parser.add_argument("--image_path", default="1.jpg", help="Process an image. Read all standard formats (jpg, png, bmp, etc.).")
    args = parser.parse_known_args()

    # Custom Params (refer to include/openpose/flags.hpp for more parameters)
    params = dict()
    params["model_folder"] = "openpose/models/"
    params["net_resolution"] = '128x192'
    # Add others in path?
    for i in range(0, len(args[1])):
        curr_item = args[1][i]
        if i != len(args[1])-1: next_item = args[1][i+1]
        else: next_item = "1"
        if "--" in curr_item and "--" in next_item:
            key = curr_item.replace('-','')
            if key not in params:  params[key] = "1"
        elif "--" in curr_item and "--" not in next_item:
            key = curr_item.replace('-','')
            if key not in params: params[key] = next_item

    # Construct it from system arguments
    # op.init_argv(args[1])
    # oppython = op.OpenposePython()

    # Starting OpenPose
    opWrapper = op.WrapperPython(3)
    opWrapper.configure(params)
    opWrapper.execute()
except Exception as e:
    print(e)
    sys.exit(-1)