def detect(self, frame):
"""
Detect the hand
:param frame: image frame
:return: cropped image, transformation, center
"""
hd = HandDetector(frame,
self.sync['config']['fx'],
self.sync['config']['fy'],
importer=self.importer,
refineNet=self.comrefNet)
doHS = (self.state.value == self.STATE_INIT)
if self.tracking.value and not numpy.allclose(self.lastcom, 0):
loc, handsz = hd.track(self.lastcom,
self.sync['config']['cube'],
doHandSize=doHS)
else:
loc, handsz = hd.detect(size=self.sync['config']['cube'],
doHandSize=doHS)
self.lastcom = loc
if self.state.value == self.STATE_INIT:
self.handsizes.append(handsz)
if self.verbose is True:
print(numpy.median(numpy.asarray(self.handsizes), axis=0))
else:
self.handsizes = []
if self.state.value == self.STATE_INIT and len(
self.handsizes) >= self.numinitframes:
cfg = self.sync['config']
cfg['cube'] = tuple(
numpy.median(numpy.asarray(self.handsizes),
axis=0).astype('int'))
self.sync.update(config=cfg)
self.state.value = self.STATE_RUN
self.handsizes = []
if numpy.allclose(loc, 0):
return numpy.zeros(
(self.poseNet.input_images.get_shape()[1].value,
self.poseNet.input_images.get_shape()[2].value),
dtype='float32'), numpy.eye(3), loc
else:
crop, M, com = hd.cropArea3D(
com=loc,
size=self.sync['config']['cube'],
dsize=(self.poseNet.input_images.get_shape()[1].value,
self.poseNet.input_images.get_shape()[2].value))
com3D = self.importer.jointImgTo3D(com)
sc = (self.sync['config']['cube'][2] / 2.)
crop[crop == 0] = com3D[2] + sc
crop.clip(com3D[2] - sc, com3D[2] + sc)
crop -= com3D[2]
crop /= sc
return crop, M, com3D
def detect(self, frame):
"""
Detect the hand
:param frame: image frame
:return: cropped image, transformation, center
"""
hd = HandDetector(frame,
self.config['fx'],
self.config['fy'],
importer=self.importer,
refineNet=self.comrefNet)
doHS = (self.state == self.STATE_INIT)
if self.tracking and not numpy.allclose(self.lastcom, 0):
loc, handsz = hd.track(self.lastcom,
self.config['cube'],
doHandSize=doHS)
else:
loc, handsz = hd.detect(size=self.config['cube'], doHandSize=doHS)
self.lastcom = loc
if self.state == self.STATE_INIT:
self.handsizes.append(handsz)
print numpy.median(numpy.asarray(self.handsizes), axis=0)
else:
self.handsizes = []
if self.state == self.STATE_INIT and len(
self.handsizes) >= self.numinitframes:
self.config['cube'] = tuple(
numpy.median(numpy.asarray(self.handsizes),
axis=0).astype('int'))
self.state = self.STATE_RUN
self.handsizes = []
if numpy.allclose(loc, 0):
return numpy.zeros((self.poseNet.cfgParams.inputDim[2],
self.poseNet.cfgParams.inputDim[3]),
dtype='float32'), numpy.eye(3), loc
else:
crop, M, com = hd.cropArea3D(
loc,
size=self.config['cube'],
dsize=(self.poseNet.layers[0].cfgParams.inputDim[2],
self.poseNet.layers[0].cfgParams.inputDim[3]))
com3D = self.importer.jointImgTo3D(com)
crop[crop == 0] = com3D[2] + (self.config['cube'][2] / 2.)
crop[crop >= com3D[2] +
(self.config['cube'][2] / 2.)] = com3D[2] + (
self.config['cube'][2] / 2.)
crop[crop <= com3D[2] -
(self.config['cube'][2] / 2.)] = com3D[2] - (
self.config['cube'][2] / 2.)
crop -= com3D[2]
crop /= (self.config['cube'][2] / 2.)
return crop, M, com3D