/
get_pulse_ck.py
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/
get_pulse_ck.py
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from lib.device import Camera
from lib.processors_noopenmdao import findFaceGetPulse
from lib.interface import plotXY, imshow, waitKey, destroyWindow
from cv2 import moveWindow
import argparse
import numpy as np
import datetime
#TODO: work on serial port comms, if anyone asks for it
#from serial import Serial
import socket
import sys
#import csv
class getPulseApp(object):
"""
Python application that finds a face in a webcam stream, then isolates the
forehead.
Then the average green-light intensity in the forehead region is gathered
over time, and the detected person's pulse is estimated.
"""
def __init__(self, args):
# Imaging device - must be a connected camera (not an ip camera or mjpeg
# stream)
serial = args.serial
baud = args.baud
self.send_serial = False
self.send_udp = False
if serial:
self.send_serial = True
if not baud:
baud = 9600
else:
baud = int(baud)
self.serial = Serial(port=serial, baudrate=baud)
udp = args.udp
if udp:
self.send_udp = True
if ":" not in udp:
ip = udp
port = 5005
else:
ip, port = udp.split(":")
port = int(port)
self.udp = (ip, port)
self.sock = socket.socket(socket.AF_INET, # Internet
socket.SOCK_DGRAM) # UDP
self.cameras = []
self.selected_cam = 0
for i in range(3):
camera = Camera(camera=i) # first camera by default
if camera.valid or not len(self.cameras):
self.cameras.append(camera)
else:
break
self.w, self.h = 0, 0
self.pressed = 0
self.v_flg = 0
self.data_acc = np.zeros((10000, 3))
# 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.)
# Init parameters for the cardiac data plot
self.bpm_plot = False
self.plot_title = "Data display - raw signal (top) and PSD (bottom)"
# Maps keystrokes to specified methods
#(A GUI window must have focus for these to work)
self.key_controls = {"s": self.toggle_search,
"d": self.toggle_display_plot,
"c": self.toggle_cam,
"f": self.write_csv}
def toggle_cam(self):
if len(self.cameras) > 1:
self.processor.find_faces = True
self.bpm_plot = False
destroyWindow(self.plot_title)
self.selected_cam += 1
self.selected_cam = self.selected_cam % len(self.cameras)
def write_csv(self):
"""
Writes current data to a csv file
"""
fn = "Webcam-pulse" + str(datetime.datetime.now())
fn = fn.replace(":", "_").replace(".", "_")
data = np.vstack((self.processor.times, self.processor.samples)).T
np.savetxt(fn + ".csv", data, delimiter=',')
print("Writing csv")
def write_csv2(self):
"""
Writes current data to a csv file
"""
fn = "Webcam-pulse" + str(datetime.datetime.now())
fn = fn.replace(":", "_").replace(".", "_")
data = self.data_acc[0:self.v_flg]
np.savetxt(fn + "_all.csv", data, delimiter=',')
print("Writing csv2")
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()
state = self.processor.find_faces_toggle()
print("face detection lock =", not state)
def toggle_display_plot(self):
"""
Toggles the data display.
"""
if self.bpm_plot:
print("bpm plot disabled")
self.bpm_plot = False
destroyWindow(self.plot_title)
else:
print("bpm plot enabled")
if self.processor.find_faces:
self.toggle_search()
self.bpm_plot = True
self.make_bpm_plot()
moveWindow(self.plot_title, self.w, 0)
def make_bpm_plot(self):
"""
Creates and/or updates the data display
"""
plotXY([[self.processor.times,
self.processor.samples],
[self.processor.freqs,
self.processor.fft]],
labels=[False, True],
showmax=[False, "bpm"],
label_ndigits=[0, 0],
showmax_digits=[0, 1],
skip=[3, 3],
name=self.plot_title,
bg=self.processor.slices[0])
def key_handler(self):
"""
Handle keystrokes, as set at the bottom of __init__()
A plotting or camera frame window must have focus for keypresses to be
detected.
"""
self.pressed = waitKey(10) & 255 # wait for keypress for 10 ms
if self.pressed == 27: # exit program on 'esc'
print("Exiting")
for cam in self.cameras:
cam.cam.release()
if self.send_serial:
self.serial.close()
#self.tmp.close()
#self.write_csv()
self.write_csv2()
sys.exit()
for key in self.key_controls.keys():
if chr(self.pressed) == key:
self.key_controls[key]()
def main_loop(self):
"""
Single iteration of the application's main loop.
"""
# Get current image frame from the camera
frame = self.cameras[self.selected_cam].get_frame()
self.h, self.w, _c = frame.shape
# 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(self.selected_cam)
# collect the output frame for display
output_frame = self.processor.frame_out
# show the processed/annotated output frame
imshow("Processed", output_frame)
# create and/or update the raw data display if needed
if self.bpm_plot:
self.make_bpm_plot()
if self.send_serial:
self.serial.write(str(self.processor.bpm) + "\r\n")
if self.send_udp:
self.sock.sendto(str(self.processor.bpm), self.udp)
# handle any key presses
self.key_handler()
#data = np.vstack((self.processor.times, self.processor.samples)).T
if len(self.processor.times) == 250:
#print(len(self.processor.times), self.processor.times[len(self.processor.times)-1], self.processor.samples[len(self.processor.times)-1])
self.data_acc[self.v_flg,0] = (self.processor.bpm)
self.data_acc[self.v_flg,1] = (self.processor.times[len(self.processor.times)-1])
self.data_acc[self.v_flg,2] = (self.processor.samples[len(self.processor.times)-1])
self.v_flg += 1
# if self.v_flg == 250:
# self.write_csv()
# self.v_flg = 1
# else:
# self.v_flg += 1
#if data.size == 500:
# #print("----------it's time to start!-----------")
# if len(self.processor.times) != 0:
# print(len(self.processor.times), self.processor.times[len(self.processor.times)-1])
# fn = "Webcam_pulse" + str(datetime.datetime.now())
# fn = fn.replace(":", "_").replace(".", "_")
# np.savetxt(fn + ".csv", data, delimiter=',')
# print("Writing csv1")
# else:
# print(len(self.processor.times))
# v_flg = 0
# if data.size == 500:
# if len(self.processor.times) != 0 & self.v_flg == 250:
# #print(len(self.processor.times), self.processor.times[len(self.processor.times)-1])
# fn = "Webcam-pulse" + str(datetime.datetime.now())
# fn = fn.replace(":", "_").replace(".", "_")
# np.savetxt(fn + ".csv", data, delimiter=',')
# print("Writing csv")
# self.v_flg = 1
# else:
# print(len(self.processor.times), self.v_flg, self.processor.times[len(self.processor.times)-1])
# self.v_flg += 1
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Webcam pulse detector.')
parser.add_argument('--serial', default=None,
help='serial port destination for bpm data')
parser.add_argument('--baud', default=None,
help='Baud rate for serial transmission')
parser.add_argument('--udp', default=None,
help='udp address:port destination for bpm data')
args = parser.parse_args()
App = getPulseApp(args)
#v_flg = 1
while True:
App.main_loop()