def outputtestpart():
deleteAllFiles('../data/processed/testdata')
count = 0
for fn in glob('../data/dataset/origin/*.jpg'):
img = cv2.imread(fn, 0)
for i in range(3):
img_part = img[300:, (i + 1) * 500:(i + 2) * 500]
ret1, img_part_bin = cv2.threshold(
cv2.GaussianBlur(cv2.equalizeHist(img_part), (3, 3), 0), 127,
255, cv2.THRESH_BINARY)
theta1 = hh.hough_theta(img_part_bin)
img_rot = hh.Rotate(img_part, theta1)
img_rawout = img_rot[300:1540,
imgtemplate(img_rot):imgtemplate(img_rot) +
240]
img_rawout = cv2.pyrDown(cv2.pyrDown(img_rawout))
filename = "../data/processed/testdata/%d_%d.jpg" % (count, i)
cv2.imwrite(filename, img_rawout)
count += 1
if os.path.isfile('../output.txt'):
os.remove('../output.txt')
with open('../output.txt', 'a+') as f:
for fn in glob('../data/processed/testdata/*.jpg'):
f.write(fn + ' ' + '0' + '\n')
def outputpasspart():
deleteAllFiles('../data/processed/passdata')
count = 0
for fn in glob('../data/dataset/pass/*.jpg'):
img = cv2.imread(fn, 0)
for i in range(3):
img_part = img[300:, (i + 1) * 500:(i + 2) * 500]
ret1, img_part_bin = cv2.threshold(
cv2.GaussianBlur(cv2.equalizeHist(img_part), (3, 3), 0), 127,
255, cv2.THRESH_BINARY)
theta1 = hh.hough_theta(img_part_bin)
img_rot = hh.Rotate(img_part, theta1)
img_rawout = img_rot[140:1380,
imgtemplate(img_rot):imgtemplate(img_rot) +
240]
img_rawout = cv2.pyrDown(cv2.pyrDown(img_rawout))
img_rawout_reverse1 = img_rawout[::-1]
filename = "../data/processed/passdata/%d_%d.jpg" % (count, i)
filename1 = "../data/processed/passdata/%d_%dr1.jpg" % (count, i)
cv2.imwrite(filename, img_rawout)
cv2.imwrite(filename1, img_rawout_reverse1)
count += 1
def outputfailpart():
deleteAllFiles('../data/processed/faildata')
count = 0
for fn in glob('../data/dataset/fail/*.jpg'):
# divide the filename
filename = [0, 0, 0]
if "三" in fn:
filename = [1, 1, 1]
continue
elif "左" in fn:
filename[0] = 1
elif "中" in fn:
filename[1] = 1
elif "右" in fn:
filename[2] = 1
else:
continue
# read image
img = cv2.imread(fn, 0)
for i in range(3):
if not filename[i]:
continue
img_part = img[300:, (i + 1) * 500:(i + 2) * 500]
ret1, img_part_bin = cv2.threshold(
cv2.GaussianBlur(cv2.equalizeHist(img_part), (3, 3), 0), 127,
255, cv2.THRESH_BINARY)
theta1 = hh.hough_theta(img_part_bin)
img_rot = hh.Rotate(img_part, theta1)
img_rawout = img_rot[300:1540,
imgtemplate(img_rot):imgtemplate(img_rot) +
240]
img_rawout = cv2.pyrDown(cv2.pyrDown(img_rawout))
img_rawout_reverse1 = img_rawout[::-1]
img_rawout_reverse2 = cv2.flip(img_rawout, 1)
img_rawout_reverse3 = cv2.flip(img_rawout[::-1], 0)
filename = "../data/processed/faildata/%d_%d.jpg" % (count, i)
filename1 = "../data/processed/faildata/%d_%dr1.jpg" % (count, i)
filename2 = "../data/processed/faildata/%d_%dr2.jpg" % (count, i)
filename3 = "../data/processed/faildata/%d_%dr3.jpg" % (count, i)
cv2.imwrite(filename, img_rawout)
cv2.imwrite(filename1, img_rawout_reverse1)
cv2.imwrite(filename2, img_rawout_reverse2)
cv2.imwrite(filename3, img_rawout_reverse3)
count += 1
# Start
# First read each image and divide into three parts
for fn in path_list:
img = cv2.imread(imgpath + fn, 0)
os.remove('../tmp/tmp.txt')
deleteAllFiles('../tmp/tmpimg')
# for each part do enhance
for i in range(3):
img_part = img[300:, (i + 1) * 500:(i + 2) * 500]
ret1, img_part_bin = cv2.threshold(
cv2.GaussianBlur(cv2.equalizeHist(img_part), (3, 3), 0), 127,
255, cv2.THRESH_BINARY)
theta1 = hh.hough_theta(img_part_bin)
img_rot = hh.Rotate(img_part, theta1)
img_rawout = img_rot[300:1540,
imgtemplate(img_rot):imgtemplate(img_rot) +
240]
img_rawout = cv2.pyrDown(cv2.pyrDown(img_rawout))
filename = "../tmp/tmpimg/%d.jpg" % i
cv2.imwrite(filename, img_rawout)
# Write to fileswe
with open('../tmp/tmp.txt', 'a+') as f:
f.write(filename + ' ' + '0' + '\n')
# Make an Iterator of one image
op_data = ImageDataGenerator('../tmp/tmp.txt',