输出结果
论文复现：《Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields》
https://arxiv.org/abs/1611.08050
代码实现
更新……
import argparse
import time
import cv2
from processing import extract_parts, draw
from config_reader import config_reader
from model.cmu_model import get_testing_model
#CV：基于keras利用算法MobilenetV2实现局部相似域的多人二维姿态实时估计
#论文复现：《Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields》
if __name__ == '__main__':
parser = argparse.ArgumentParser()
# parser.add_argument('--image', type=str, required=True, help='input image')
parser.add_argument('--image', type=str, default='F:/File_Python/Python_example/Human_Posture_Detection/images/ZMS03.jpg', help='input image')
parser.add_argument('--output', type=str, default='result.png', help='output image')
parser.add_argument('--model', type=str, default='model/keras_Realtime_Multi_Person_Pose_Estimation_model.h5', help='path to the weights file')
args = parser.parse_args()
image_path = args.image
output = args.output
keras_weights_file = args.model
tic = time.time()
print('start processing...')
# load model
# authors of original model don't use
# vgg normalization (subtracting mean) on input images
model = get_testing_model()
model.load_weights(keras_weights_file)
# load config
params, model_params = config_reader()
input_image = cv2.imread(image_path) # B,G,R order
body_parts, all_peaks, subset, candidate = extract_parts(input_image, params, model, model_params)
canvas = draw(input_image, all_peaks, subset, candidate)
toc = time.time()
print('processing time is %.5f' % (toc - tic))
cv2.imshow('keras_Realtime_Multi_Person_Pose_Estimation_model',canvas)
cv2.waitKey()
cv2.imwrite(output, canvas)
cv2.destroyAllWindows()
