parser = argparse.ArgumentParser(description='MobilePose Realtime Webcam.')
parser.add_argument(
'--model',
type=str,
default='resnet18',
choices=['mobilenetv2', 'resnet18', 'shufflenetv2', 'squeezenet'])
parser.add_argument('--inp_dim', type=int, default=224, help='input size')
parser.add_argument('--camera', type=int, default=0)
args = parser.parse_args()
# load the model
#model_path = os.path.join("./models", args.model+"_%d_adam_best.t7"%args.inp_dim)
model_path = "./models/mobilenetv2_224_adam_best.t7"
net = CoordRegressionNetwork(n_locations=6, backbone=args.model).to("cpu")
e = ResEstimator(model_path, net, args.inp_dim)
# # initial the camera
# cam = cv2.VideoCapture(args.camera)
# ret_val, image = cam.read()
# image = crop_camera(image)
# while True:
# # read image from the camera and preprocess
# ret_val , image = cam.read()
# image = crop_camera(image)
# # forward the image
# humans = e.inference(image)
# image = ResEstimator.draw_humans(image, humans, imgcopy=False)
# cv2.imshow('MobilePose Demo', image)
mid_width = width / 2.0
width_20 = width * ratio
crop_img = image[0:int(height),
int(mid_width - width_20):int(mid_width + width_20)]
return crop_img
if __name__ == '__main__':
# load the model
model_path = './models/mobilenetv2_224_adam_best.t7'
net = CoordRegressionNetwork(n_locations=16,
backbone='mobilenetv2').to('cpu')
estimator = ResEstimator(model_path, net, 224)
# initialize the camera
cam = cv2.VideoCapture(0)
ret_val, image = cam.read()
image = crop_camera(image)
while True:
# get frame
ret_val, image = cam.read()
image = crop_camera(image)
# infer through network
humans = estimator.inference(image)
# image = ResEstimator.draw_humans(
import matplotlib.pyplot as plt
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='MobilePose Realtime Webcam.')
parser.add_argument('--model',
type=str,
default='resnet',
help='mobilenet|resnet')
parser.add_argument('--camera', type=int, default=0)
args = parser.parse_args()
# load the model
w, h = model_wh(get_graph_path(args.model))
e = ResEstimator(get_graph_path(args.model), target_size=(w, h))
# initial the camera
cam = cv2.VideoCapture(args.camera)
ret_val, image = cam.read()
image = crop_camera(image)
while True:
# read image from the camera and preprocess
ret_val, image = cam.read()
image = crop_camera(image)
# forward the image
humans = e.inference(image, args.model)
image = ResEstimator.draw_humans(image, humans, imgcopy=False)
cv2.imshow('MobilePose Demo', image)