def __init__(self,filename=(sys.argv[1] if len(sys.argv) > 1 else None)):
if (filename is None):
raise Exception("Filename unset")
self.camera = VideoStream(filename=filename) #first camera by default
self.bpms = []
#Containerized analysis of recieved image frames (an openMDAO assembly)
#is defined next.
#This assembly is designed to handle all image & signal analysis,
#such as face detection, forehead isolation, time series collection,
#heart-beat detection, etc.
#Basically, everything that isn't communication
#to the camera device or part of the GUI
self.processor = findFaceGetPulse(bpm_limits = [50,160],
data_spike_limit = 2500.,
face_detector_smoothness = 10.)
while (self.main_loop()):
sys.stderr.write(". ")
sys.stderr.write("\n\n")
def __init__(self, filename=(sys.argv[1] if len(sys.argv) > 1 else None)):
if filename is None:
raise Exception("Filename unset")
self.camera = VideoStream(filename=filename) # first camera by default
self.bpms = []
# Containerized analysis of recieved image frames (an openMDAO assembly)
# is defined next.
# This assembly is designed to handle all image & signal analysis,
# such as face detection, forehead isolation, time series collection,
# heart-beat detection, etc.
# Basically, everything that isn't communication
# to the camera device or part of the GUI
self.processor = findFaceGetPulse(bpm_limits=[50, 160], data_spike_limit=2500.0, face_detector_smoothness=10.0)
while self.main_loop():
sys.stderr.write(". ")
sys.stderr.write("\n\n")
class Pulse(object):
def __init__(self, filename=(sys.argv[1] if len(sys.argv) > 1 else None)):
if filename is None:
raise Exception("Filename unset")
self.camera = VideoStream(filename=filename) # first camera by default
self.bpms = []
# Containerized analysis of recieved image frames (an openMDAO assembly)
# is defined next.
# This assembly is designed to handle all image & signal analysis,
# such as face detection, forehead isolation, time series collection,
# heart-beat detection, etc.
# Basically, everything that isn't communication
# to the camera device or part of the GUI
self.processor = findFaceGetPulse(bpm_limits=[50, 160], data_spike_limit=2500.0, face_detector_smoothness=10.0)
while self.main_loop():
sys.stderr.write(". ")
sys.stderr.write("\n\n")
def write_csv(self):
"""
Writes current data to a csv file
"""
bpm = " " + str(int(self.processor.measure_heart.bpm))
fn = str(datetime.datetime.now()).split(".")[0] + bpm + " BPM.csv"
data = np.array([self.processor.fft.times, self.processor.fft.samples]).T
np.savetxt(fn, data, delimiter=",")
def median(self):
return np.median(self.bpms)
def toggle_search(self):
"""
Toggles a motion lock on the processor's face detection component.
Locking the forehead location in place significantly improves
data quality, once a forehead has been sucessfully isolated.
"""
state = self.processor.find_faces.toggle()
if not state:
self.processor.fft.reset()
print "face detection lock =", not state
def capture_bpms(self):
try:
if 300 > self.processor.measure_heart.bpm > 10:
self.bpms.append(self.processor.measure_heart.bpm)
else:
sys.stderr.write("D")
except NameError:
return
def main_loop(self):
"""
Single iteration of the application's main loop.
"""
# Get current image frame from the camera
try:
frame = self.camera.get_frame()
if frame is None:
print ("EOF")
return False
self.h, self.w, _c = frame.shape
except AttributeError:
print ("ERR01 yo")
return False
# display unaltered frame
imshow("Original", frame)
# set current image frame to the processor's input
self.processor.frame_in = frame
# process the image frame to perform all needed analysis
self.processor.run()
# collect the output frame for display
output_frame = self.processor.frame_out
# show the processed/annotated output frame
imshow("Processed", output_frame)
self.capture_bpms()
# create and/or update the raw data display if needed
# if self.bpm_plot:
# testfk = self.make_bpm_plot()
# print(testfk)
# handle any key presses
# self.key_handler()
return True
class Pulse(object):
def __init__(self,filename=(sys.argv[1] if len(sys.argv) > 1 else None)):
if (filename is None):
raise Exception("Filename unset")
self.camera = VideoStream(filename=filename) #first camera by default
self.bpms = []
#Containerized analysis of recieved image frames (an openMDAO assembly)
#is defined next.
#This assembly is designed to handle all image & signal analysis,
#such as face detection, forehead isolation, time series collection,
#heart-beat detection, etc.
#Basically, everything that isn't communication
#to the camera device or part of the GUI
self.processor = findFaceGetPulse(bpm_limits = [50,160],
data_spike_limit = 2500.,
face_detector_smoothness = 10.)
while (self.main_loop()):
sys.stderr.write(". ")
sys.stderr.write("\n\n")
def write_csv(self):
"""
Writes current data to a csv file
"""
bpm = " " + str(int(self.processor.measure_heart.bpm))
fn = str(datetime.datetime.now()).split(".")[0] + bpm + " BPM.csv"
data = np.array([self.processor.fft.times,
self.processor.fft.samples]).T
np.savetxt(fn, data, delimiter=',')
def median(self):
return np.median(self.bpms)
def toggle_search(self):
"""
Toggles a motion lock on the processor's face detection component.
Locking the forehead location in place significantly improves
data quality, once a forehead has been sucessfully isolated.
"""
state = self.processor.find_faces.toggle()
if not state:
self.processor.fft.reset()
print "face detection lock =",not state
def capture_bpms(self):
try:
if 300 > self.processor.measure_heart.bpm > 10:
self.bpms.append(self.processor.measure_heart.bpm)
else:
sys.stderr.write("D")
except NameError:
return
def main_loop(self):
"""
Single iteration of the application's main loop.
"""
# Get current image frame from the camera
try:
frame = self.camera.get_frame()
if ( frame is None ):
print ("EOF")
return False
self.h,self.w,_c = frame.shape
except AttributeError:
print ("ERR01 yo")
return False
#display unaltered frame
imshow("Original",frame)
#set current image frame to the processor's input
self.processor.frame_in = frame
#process the image frame to perform all needed analysis
self.processor.run()
#collect the output frame for display
output_frame = self.processor.frame_out
#show the processed/annotated output frame
imshow("Processed",output_frame)
self.capture_bpms()
#create and/or update the raw data display if needed
#if self.bpm_plot:
# testfk = self.make_bpm_plot()
# print(testfk)
#handle any key presses
#self.key_handler()
return True
