forked from dilawar/eye-blink-detector
/
blinky_webcam.py
executable file
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blinky_webcam.py
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#!/usr/bin/env python
"""Extract blink data and visualize it using matplotlib.
"""
__author__ = "Dilawar Singh"
__copyright__ = "Copyright 2015, Dilawar Singh and NCBS Bangalore"
__credits__ = ["NCBS Bangalore"]
__license__ = "GNU GPL"
__version__ = "1.0.0"
__maintainer__ = "Dilawar Singh"
__email__ = "dilawars@ncbs.res.in"
__status__ = "Development"
import numpy as np
import gnuplotlib as gplt
import matplotlib.pyplot as plt
import matplotlib.animation as anim
import extract
import sys
import cv2
import webcam
import os
import sys
######################################
# Initialize animation here
data_ = np.zeros(shape=(1,3))
cap_ = None
box_ = []
fig_ = plt.figure()
fps_ = 0.0
axes_ = {}
lines_ = {}
ax1 = fig_.add_subplot(2, 1, 1)
ax2 = ax1.twinx()
ax3 = fig_.add_subplot(2, 1, 2)
ax4 = ax3.twinx()
# Inset for raw data.
save_video_ = False
writer_ = None
if save_video_:
fig_ax_ = fig_.add_axes([.7, .55, .2, .2], axisbg='y')
#writer_ = anim.writers['ffmpeg'](fps = 15)
else:
cv2.namedWindow('image')
axes_ = { 'raw' : ax1, 'raw_twin' : ax2, 'blink' : ax3, 'blink_twin' : ax4 }
lines_["rawA"] = ax1.plot([], [], color='blue')[0]
lines_['blinkA'] = ax3.plot([], [], 's', color = 'blue')[0]
time_template_ = 'Time = %.1f s'
time_text_ = fig_.text(0.05, 0.9, '', transform=axes_['blink'].transAxes)
tvec_ = []
y1_ = []
y2_ = []
args_ = None
def init():
# global axes_, lines_
global box_, fps_
global cap_, args_
cap_ = cv2.VideoCapture( args_['camera'] )
fps_ = cap_.get(cv2.cv.CV_CAP_PROP_FPS)
if fps_ < 1:
print('[WARN] failed to get FPS. Setting to 15')
fps_ = 15
ret, fstFrame = cap_.read()
box_ = webcam.get_bounding_box(fstFrame)
cv2.destroyWindow('Bound_eye')
cv2.destroyAllWindows()
cv2.waitKey(1)
cv2.destroyAllWindows()
# return lines_.values()
def update_axis_limits(ax, x, y):
xlim = ax.get_xlim()
if x >= xlim[1]:
ax.set_xlim(xlim[0], x+10)
ylims = ax.get_ylim()
if y >= ylims[1]:
ax.set_ylim(ylims[0], y+1)
def animate(i):
global data_
# global time_text_
global box_
global tvec_, y1_, y2_
global cap_
# global fig_ax_
t = float(i) / fps_
ret, img = cap_.read()
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
(x0, y0), (x1, y1) = box_
try:
frame = img[y0:y1,x0:x1]
except Exception as e:
print('[WARN] Frame %s dropped' % i)
return lines_.values(), time_text_
if save_video_:
fig_ax_.imshow(frame[::2,::2], interpolation='nearest')
else:
#cv2.imshow('image', frame)
cv2.waitKey(1)
inI, outI, edge, pixal = webcam.process_frame(frame)
cv2.imshow('Eye', np.concatenate((frame, outI)))
tvec_.append(t); y1_.append(edge); y2_.append(pixal)
update_axis_limits(axes_['raw'], t, edge)
update_axis_limits(axes_['raw_twin'], t, pixal)
tA, bA = [0], [0]
if i % int(fps_*0.1) == 0:
data_ = np.array((tvec_, y1_)).T
try:
tA, bA = extract.find_blinks_using_edge(data_[:,:])
except Exception as e:
print('[WARN] Failed to detect blink data using egdes in frame %s' % i)
tA, bA = [0], [0]
gplt.plot( ( np.array(tvec_[-1000:]), np.array( y1_[-1000:] ))
# , ( np.array(tA), np.array(bA), {} )
, title = 'Blink detection. Running window 1000 frames'
, terminal = 'x11'
)
def get_blinks( ):
global ani_, cap_
global save_video_
i = 0
while True:
i += 1
animate( i )
def close_all( ):
global cap_
cap.release()
def main():
global data_, args_
init()
try:
get_blinks()
except Exception as e:
print('[ERR] Failed to get blinks: %s' % e)
cap_.release()
if __name__ == '__main__':
import argparse
# Argument parser.
description = '''Detect eyeblink in live camera feed'''
parser = argparse.ArgumentParser(description=description)
parser.add_argument('--camera', '-c'
, required = False
, default = 0
, type = int
, help = 'Camera index. Default 0'
)
class Args: pass
args = Args()
parser.parse_args(namespace=args)
args_ = vars(args)
try:
main()
except KeyboardInterrupt as e:
print('[INFO] Keyboard interrupt.Quitting')
close_all()
quit()