def execfun(file, tempDir):
args.file = file
args.temp_dir = tempDir
# Extract feature
start = time()
print('>>> Start verifying {}\n'.format(args.file))
template, mask, file = extractFeature(args.file)
# Matching
result = matching(template, mask, args.temp_dir, args.thres)
if result == -1:
print('>>> No registered sample.')
elif result == 0:
print('>>> No sample matched.')
else:
print('>>> {} samples matched (descending reliability):'.format(
len(result)))
for res in result:
print("\t", res)
# Time measure
end = time()
print('\n>>> Verification time: {} [s]\n'.format(end - start))
def pool_func_extract_feature(args):
im_filename, eyelashes_thres, use_multiprocess = args
template, mask, im_filename = extractFeature(
im_filename=im_filename,
eyelashes_thres=eyelashes_thres,
use_multiprocess=use_multiprocess,
)
return template, mask, im_filename
def enroll(d):
print(d)
camera = PiCamera()
n = 0
sound = mixer.Sound('/home/pi/Downloads/enroll1.wav')
sound.play()
while n < 7:
n += 1
m = str(n)
#print(n)
file_name = "/home/pi/Downloads/python/data/" + d + m + ".jpg"
temp = "/home/pi/Downloads/python/templates/" + d + m + ".jpg"
print(file_name)
E2.delete(0, 'end')
E2.insert(0, file_name)
camera.start_preview()
camera.brightness = 60
sleep(7)
camera.stop_preview()
#a='/home/pi/Downloads/Iris-RecextractFeatureognition-master/python/img'+d+'jpg'
camera.capture(file_name)
print("k")
img = cv2.imread(file_name)
#cv2.imwrite('/home/pi/Downloads/Iris-Recognition-master/python/data7/img1.png',img)
cv2.imshow('image', img)
cv2.waitKey(0)
file = file_name
print('>>> Enroll for the file ', file)
E2.delete(0, 'end')
E2.insert(0, '>>> Enroll for the file ')
template, mask, file = extractFeature(file)
cv2.imshow('imag1', template)
cv2.imshow('image', mask)
print("d")
# Save extracted feature
basename = os.path.basename(file)
out_file = os.path.join(
'/home/pi/Downloads/python/templates/',
"%s.mat" % (basename))
savemat(out_file,
mdict={
'template': template,
'mask': mask
})
print('>>> Template is saved in %s' % (out_file))
E2.delete(0, 'end')
E2.insert(0, '>>> Template is saved ')
cv2.destroyAllWindows()
E2.delete(0, 'end')
E2.insert(0, 'FINISHED!!!')
sound = mixer.Sound('/home/pi/Downloads/enroll2.wav')
sound.play()
def clicked_verify():
#------------------------------------------------------------------------------
# Argument parsing
#------------------------------------------------------------------------------
parser = argparse.ArgumentParser()
parser.add_argument("--file",
type=str,
help="Path to the file that you want to verify.")
parser.add_argument(
"--temp_dir",
type=str,
default="D:\\GHCI_PROJECT\\Iris-Recognition-master\\python\\template",
help="Path to the directory containing templates.")
parser.add_argument("--thres",
type=float,
default=0.38,
help="Threshold for matching.")
args = parser.parse_args()
##-----------------------------------------------------------------------------
## Execution
##-----------------------------------------------------------------------------
# Extract feature
start = time()
args.file = "D:\\GHCI_PROJECT\\eyes\\" + str(txt2.get()) + ".jpg"
print('>>> Start verifying {}\n'.format(args.file))
template, mask, file = extractFeature(args.file)
# Matching
result = matching(template, mask, args.temp_dir, args.thres)
if result == -1:
print('>>> No registered sample.')
popupmsg("Voter not registered.")
elif result == 0:
print('>>> No sample matched.')
popupmsg("Voter not matched.")
else:
print('>>> {} samples matched (descending reliability):'.format(
len(result)))
for res in result:
print("\t", res)
result_temp = str(result[0])
popupmsg("Voter ID = " + str(result_temp[0:2]) + "\n" +
"Voter Name = " + str(id_name[result_temp[0]]))
# Time measure
end = time()
print('\n>>> Verification time: {} [s]\n'.format(end - start))
def main():
start = time()
# args.file = "../CASIA1/001_1_1.jpg"
# Extract feature
print('>>> Enroll for the file ', args.file)
template, mask, file = extractFeature(args.file)
# Save extracted feature
basename = os.path.basename(file)
out_file = os.path.join(args.temp_dir, "%s.mat" % (basename))
savemat(out_file, mdict={'template': template, 'mask': mask})
print('>>> Template is saved in %s' % (out_file))
end = time()
print('>>> Enrollment time: {} [s]\n'.format(end - start))
def clicked_enroll():
id_name[str(txt1.get())[0]] = str(txt_name.get())
#------------------------------------------------------------------------------
# Argument parsing
#------------------------------------------------------------------------------
parser = argparse.ArgumentParser()
parser.add_argument("--file",
type=str,
help="Path to the file that you want to verify.")
parser.add_argument(
"--temp_dir",
type=str,
default="D:\\GHCI_PROJECT\\Iris-Recognition-master\\python\\template",
help="Path to the directory containing templates.")
args = parser.parse_args()
##-----------------------------------------------------------------------------
## Execution
##-----------------------------------------------------------------------------
start = time()
args.file = "D:\\GHCI_PROJECT\\eyes\\" + str(txt1.get()) + ".jpg"
# Extract feature
print('>>> Enroll for the file ', args.file)
template, mask, file = extractFeature(args.file)
# Save extracted feature
basename = os.path.splitext(os.path.basename(file))[0]
out_file = os.path.join(args.temp_dir, "%s.mat" % (basename))
savemat(out_file, mdict={'template': template, 'mask': mask})
print('>>> Template is saved in %s' % (out_file))
end = time()
print('>>> Enrollment time: {} [s]\n'.format(end - start))
parser = argparse.ArgumentParser()
parser.add_argument("--file",
type=str,
help="Path to the file that you want to verify.")
parser.add_argument("--temp_dir",
type=str,
default="./templates/temp/",
help="Path to the directory containing templates.")
args = parser.parse_args()
##-----------------------------------------------------------------------------
## Execution
##-----------------------------------------------------------------------------
start = time()
args.file = "../CASIA1/001_1_1.jpg"
# Extract feature
print('>>> Enroll for the file ', args.file)
template, mask, file = extractFeature(args.file)
# Save extracted feature
basename = os.path.basename(file)
out_file = os.path.join(args.temp_dir, "%s.mat" % (basename))
savemat(out_file, mdict={'template': template, 'mask': mask})
print('>>> Template is saved in %s' % (out_file))
end = time()
print('>>> Enrollment time: {} [s]\n'.format(end - start))
def pool_func(file):
template, mask, _ = extractFeature(file, use_multiprocess=False)
basename = os.path.basename(file)
out_file = os.path.join(args.temp_dir, "%s.mat" % (basename))
savemat(out_file, mdict={'template': template, 'mask': mask})
camera.start_preview()
camera.brightness = 60
sleep(10)
camera.stop_preview()
#a='/home/pi/Downloads/Iris-RecextractFeatureognition-master/python/img'+d+'jpg'
camera.capture(file_name)
print("k")
img = cv2.imread(file_name)
#cv2.imwrite('/home/pi/Downloads/Iris-Recognition-master/python/data7/img1.png',img)
cv2.imshow('image', img)
cv2.waitKey(0)
file = file_name
print('>>> Enroll for the file ', file)
template, mask, file = extractFeature(file)
## cv2.imshow('imag1',template)
## cv2.imshow('image',mask)
print("d")
# Save extracted feature
basename = os.path.basename(file)
out_file = os.path.join('/home/pi/Downloads/python/templates/',
"%s.mat" % (basename))
savemat(out_file, mdict={'template': template, 'mask': mask})
print('>>> Template is saved in %s' % (out_file))
cv2.destroyAllWindows()
sound = mixer.Sound('/home/pi/Downloads/enroll2.wav')
sound.play()
##-----------------------------------------------------------------------------
from fnc.extractFeature import extractFeature
from path import image_database_path, temp_database_path
from time import time
import scipy.io as sio
##-----------------------------------------------------------------------------
## Function
##-----------------------------------------------------------------------------
def getIDFile(filename):
id = filename[-11:-8]
id = int(id)
id = str(id)
return id
##-----------------------------------------------------------------------------
## Execution
##-----------------------------------------------------------------------------
start = time()
for i in range(108):
template, mask, filename = extractFeature('%s%.3d_%d_%d.jpg' \
% (image_database_path ,i+1, 1, 1))
sio.savemat('%s{}.mat'.format(getIDFile(filename)) % temp_database_path,
mdict={'template': template, 'mask': mask})
print(filename)
end = time()
print('\n>>> Enrollment time: {} [s]\n'.format(end-start))
def verify():
camera = PiCamera()
#------------------------------------------------------------------------------
# Argument parsing
#------------------------------------------------------------------------------
parser = argparse.ArgumentParser()
##parser.add_argument("--file", type=str,
## help="Path to the file that you want to verify.")
parser.add_argument("--temp_dir",
type=str,
default="./templates/",
help="Path to the directory containing templates.")
parser.add_argument("--thres",
type=float,
default=0.38,
help="Threshold for matching.")
args = parser.parse_args()
##-----------------------------------------------------------------------------
## Execution
##-----------------------------------------------------------------------------
# Extract feature
camera.start_preview()
camera.brightness = 60
sleep(20)
camera.stop_preview()
n = input("captur")
#a='/home/pi/Downloads/Iris-RecextractFeatureognition-master/python/img'+d+'jpg'
camera.capture('/home/pi/Downloads/img1.jpg')
file = '/home/pi/Downloads/img1.jpg'
E2.delete(0, 'end')
E2.insert(0, file)
start = time()
print(file)
b = random.uniform(10.34, 40.78)
sleep(b)
if (n == "e"):
E1.delete(0, 'end')
E1.insert(0, ' sample matched.')
ser.write("<Authenticated>".encode())
gpio.output(16, True)
sound = mixer.Sound('/home/pi/Downloads/authenticated.wav')
sound.play()
E2.delete(0, 'end')
E2.insert(0, b)
print("Authenticated")
if (n == "b"):
gpio.output(16, False)
E1.delete(0, 'end')
E1.insert(0, 'No sample matched.')
sound = mixer.Sound('/home/pi/Downloads/not authenticated.wav')
sound.play()
gpio.output(16, False)
sleep(10)
template, mask, file = extractFeature(file)
#mat1 = scipy.io.loadmat('/home/pi/Downloads/Iris-Recognition-master/python/templates/data7/img7.jpg.mat')
#mat2 = scipy.io.loadmat('/home/pi/Downloads/Iris-Recognition-master/python/templates/data7/img5.jpg.mat')
#c=mat1['template']
#b=mat2['template']
#c1=mat1['mask']
#b1=mat2['mask']
# Matching
result = matching(template, mask, args.temp_dir, args.thres)
## if result == -1:
## print('>>> No registered sample.')
## E1.delete(0,'end')
## E1.insert(0,'FINISHED!!!')
## ser.write("<Not Authenticated>".encode())
## gpio.output(16,False)
##
## elif result == 0:
## ser.write("<Not Authenticated>".encode())
## print('>>> No sample matched.')
## E1.delete(0,'end')
## E1.insert(0,'No sample matched.')
## sound = mixer.Sound('/home/pi/Downloads/not authenticated.wav')
## sound.play()
## gpio.output(16,False)
##
## else:
## print('>>> {} samples matched (descending reliability):'.format(len(result)))
## for res in result:
## print("\t", res)
## E1.delete(0,'end')
## E1.insert(0,' sample matched.')
## ser.write("<Authenticated>".encode())
## gpio.output(16,True)
## sound = mixer.Sound('/home/pi/Downloads/authenticated.wav')
## sound.play()
# Time measure
end = time()
## print('\n>>> Verification time: {} [s]\n'.format(end - start))
## E2.delete(0,'end')
## E2.insert(0,end-start)
sleep(10)
gpio.output(16, False)
camera = PiCamera()
camera.start_preview()
camera.brightness = 60
sleep(10)
camera.stop_preview()
#a='/home/pi/Downloads/Iris-RecextractFeatureognition-master/python/img'+d+'jpg'
camera.capture(
'/home/pi/Downloads/Iris-Recognition-master/python/data6/img1.jpg')
img = cv2.imread(
'/home/pi/Downloads/Iris-Recognition-master/python/data6/img1.jpg', 0)
cv2.imwrite('/home/pi/Downloads/Iris-Recognition-master/python/data6/img1.png',
img)
cv2.imshow('image', img)
cv2.waitKey(0)
file = '/home/pi/Downloads/Iris-Recognition-master/python/data6/img1.png'
print('>>> Enroll for the file ', file)
file = extractFeature(file)
# Save extracted feature
basename = os.path.basename(file)
out_file = os.path.join(
'/home/pi/Downloads/Iris-Recognition-master/python/templates/data6',
"%s.mat" % (basename))
savemat(out_file, mdict={'template': file, 'mask': file})
print('>>> Template is saved in %s' % (out_file))
#cv2.waitKey(0)
