simple pyopenpose usage
- Before last post, the introduction of installation of openpose . For now, as you are a learner of python, so you should learn how to use the python api of openpose.
Test your pyopenpose
- Fisrt way (Recommand)
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3python
>>> import openpose
>>> from openpose import pyopenpose as op - Second way
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3python
>>> import pyopenpose as op
>>> - So if that’s OK, then you are OK.
Simple Usage of pyopenpose
Main Steps
- Initializing the parameters, refer to include/openpose/flags.hpp for more parameters
- Process inputs (images, videos etc.)
- Get outputs
Example, hand detection from image, video or webcam.
Remember to set the path of your openpose models
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104#!/usr/bin/python3
#!--*-- coding:utf-8 --*--
#! Author: Tim Chan, motoleisure@gmail.com
import cv2
import time
import os.path
import sys
import argparse
import numpy as np
from openpose import pyopenpose as op
def readCap(args):
outputFile = "openpose_out_py.mp4"
if (args.image):
# Open the image file
if not os.path.isfile(args.image):
print("Input image file ", args.image, " doesn't exist")
sys.exit(1)
cap = cv2.VideoCapture(args.image)
outputFile = args.image[:-4]+'_openpose_out_py.jpg'
elif (args.video):
# Open the video file
if not os.path.isfile(args.video):
print("Input video file ", args.video, " doesn't exist")
sys.exit(1)
cap = cv2.VideoCapture(args.video)
outputFile = args.video[:-4]+'_openpose_out_py.mp4'
else:
# Webcam input
cap = cv2.VideoCapture(0)
cap.set(3, 720)
cap.set(4, 1280)
return cap, outputFile
def processing_openpose(args):
# Initialize the openpose parameters
# Custom Params (refer to include/openpose/flags.hpp for more parameters)
params = {}
params["model_folder"] = "/home/ares2/openpose/models"
params["hand"] = True
# Starting OpenPose
opWrapper = op.WrapperPython()
opWrapper.configure(params)
opWrapper.start()
# cv2 display setups
winName = 'Deep learning object detection in OpenCV'
cv2.namedWindow(winName, cv2.WINDOW_NORMAL)
cap, outputFile = readCap(args)
# Get the video writer initialized to save the output video
if (not args.image):
vid_writer = cv2.VideoWriter(outputFile, cv2.VideoWriter_fourcc('M', 'J', 'P', 'G'),
30, (round(cap.get(cv2.CAP_PROP_FRAME_WIDTH)),
round(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))))
while cv2.waitKey(1) < 0:
start_time = time.time()
# get frame from the video
hasFrame, frame = cap.read()
# Stop the program if reached end of video
if not hasFrame:
print("Done processing !!!")
print("Output file is stored as ", outputFile)
cv2.waitKey(3000)
# Release device
cap.release()
break
# openpose input
datum = op.Datum()
datum.cvInputData = frame
opWrapper.emplaceAndPop([datum])
# openpose output
frame = datum.cvOutputData
end_time = time.time()
t = end_time - start_time
label = 'Inference time: %.2f ms' % ( 1.0 / t)
cv2.putText(frame, label, (0, 15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255))
# Write the frame with the detection boxes
if (args.image):
cv2.imwrite(outputFile, frame.astype(np.uint8))
else:
vid_writer.write(frame.astype(np.uint8))
cv2.imshow(winName, frame)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Openpose Python API usage example')
parser.add_argument('--image', help='Path to image file.')
parser.add_argument('--video', help='Path to video file.')
args = parser.parse_args()
processing_openpose(args)
Just have a try and be happy.
References
- 本文标题：simple pyopenpose usage
- 创建时间：2019-08-01 10:59:47
- 本文链接：2019/08/01/ML/simple-pyopenpose-usage/
- 版权声明：本博客所有文章除特别声明外，均采用 BY-NC-SA 许可协议。转载请注明出处！
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