python姿态识别_openpose windows手势（姿态）识别

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

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)