def __init__(self,
xml_path=cfg.PERSON_DET_XML,
device='MYRIAD',
inp_size=1, out_size=1,
num_requests=2, plugin=None):
"""Initialize Face detector object"""
self.__net = Network()
self.plugin, (self.B, self.C, self.H, self.W) = self.__net.load_model(
xml_path, device, inp_size, out_size, num_requests, plugin=plugin)
def __init__(self,
xml_path=cfg.HEAD_POSE_XML,
device='MYRIAD',
inp_size=1,
out_size=3,
num_requests=2,
plugin=None):
self.__net = Network()
self.plugin, (self.B, self.C, self.H,
self.W) = self.__net.load_model(xml_path,
device,
inp_size,
out_size,
num_requests,
plugin=plugin)
class HeadPoser:
def __init__(self,
xml_path=cfg.HEAD_POSE_XML,
device='MYRIAD',
inp_size=1,
out_size=3,
num_requests=2,
plugin=None):
self.__net = Network()
self.plugin, (self.B, self.C, self.H,
self.W) = self.__net.load_model(xml_path,
device,
inp_size,
out_size,
num_requests,
plugin=plugin)
def estimatePose(self, face_image):
image = cv.resize(face_image, (self.W, self.H))
image = image.transpose((2, 0, 1))
image = image.reshape((self.B, self.C, self.H, self.W))
self.__net.exec_net(0, image)
self.__net.wait(0)
angle_y = self.__net.get_output(0, 'angle_y_fc')[0, 0]
angle_p = self.__net.get_output(0, 'angle_p_fc')[0, 0]
angle_r = self.__net.get_output(0, 'angle_r_fc')[0, 0]
return angle_y, angle_p, angle_r
def getPlugin(self):
return self.plugin
class PersonREID:
def __init__(self,
xml_path=cfg.PERSON_REID_XML,
device='MYRIAD',
inp_size=1,
out_size=1,
num_requests=2,
plugin=None):
self.__net = Network()
self.plugin, (self.B, self.C, self.H,
self.W) = self.__net.load_model(xml_path,
device,
inp_size,
out_size,
num_requests,
plugin=plugin)
def forward(self, face_image):
image = cv.resize(face_image, (self.W, self.H))
#image = image.transpose((2, 0, 1))
image = image.reshape((self.B, self.C, self.H, self.W))
self.__net.exec_net(0, image)
self.__net.wait(0)
emb = self.__net.get_output(0).reshape(256)
return emb
def getPlugin(self):
return self.plugin
class FaceDetector:
"""Face Detector class"""
def __init__(self,
xml_path=cfg.FACE_DET_XML,
device='MYRIAD',
inp_size=1,
out_size=1,
num_requests=2,
plugin=None):
"""Initialize Face detector object"""
self.__net = Network()
self.plugin, (self.B, self.C, self.H,
self.W) = self.__net.load_model(xml_path,
device,
inp_size,
out_size,
num_requests,
plugin=plugin)
def getFaces(self, image, def_score=0.5):
"""Detect faces in an input image with given threshold"""
H, W = image.shape[:2]
frm = cv.resize(image, (self.W, self.H))
frm = frm.transpose((2, 0, 1))
frm = frm.reshape((self.B, self.C, self.H, self.W))
self.__net.exec_net(0, frm)
self.__net.wait(0)
res = self.__net.get_output(0)
scores, bboxes = [], []
for obj in res[0][0]:
if obj[2] > def_score:
score = obj[2]
xmin = max(0, int(obj[3] * W))
ymin = max(0, int(obj[4] * H))
xmax = min(W, int(obj[5] * W))
ymax = min(H, int(obj[6] * H))
scores.append(score)
bboxes.append([xmin, ymin, xmax, ymax])
return scores, bboxes
def getPlugin(self):
return self.plugin