def processData(self, data):
s = self.stateGroup.state()
if s['direction'] == 'rising':
d = 1
else:
d = -1
return functions.threshold(data, s['threshold'], d)
def f3(self):
if self.ld1:
sav(imgtmp,functions.threshold(imgtmp))
self.ids.imgt.reload()
self.set_stat("Listo")
else:
self.set_stat(upsall)
def slider_image_change(self, event): # wxGlade: main.<event_handler>
id = self.slider_imagens.GetValue()
path = globs[id]
for child in self.panel_original.GetChildren():
child.Destroy()
wx.StaticBitmap(
self.panel_original, wx.ID_ANY,
functions.genImage(path, *self.sizer_original.GetSize()))
for child in self.panel_threshold.GetChildren():
child.Destroy()
conf = [
self.slider_h.GetValue(),
self.slider_s.GetValue(),
self.slider_v.GetValue(),
self.slider_h1.GetValue(),
self.slider_s1.GetValue(),
self.slider_v1.GetValue()
]
wx.StaticBitmap(
self.panel_threshold, wx.ID_ANY,
functions.threshold(path,
size=self.sizer_threshold.GetSize(),
hsv=conf))
def set_function(self, func):
if func.value == "threshold":
try:
t = int(func.sub_param_list[0].value)
except KeyError:
print "Failed to load threshold value!"
f = functions.threshold(t)
elif func.value == "indicator":
try:
t = int(func.sub_param_list[0].value)
except KeyError:
print "Failed to load threshold value!"
f = functions.indicator(t)
elif func.value == "biThreshold":
try:
kup = int(func.sub_param_list[0].value)
kdown = int(func.sub_param_list[1].value)
except KeyError:
print "Failed to load threshold value!"
f = functions.biThreshold(kup, kdown)
elif func.value == "inverseThreshold":
try:
t = int(func.sub_param_list[0].value)
except KeyError:
print "Failed to load threshold value!"
f = functions.inverseThreshold(t)
elif func.value == "dynBiThreshold":
try:
D01up = int(func.sub_param_list[0].value)
D10up = int(func.sub_param_list[1].value)
D01down = int(func.sub_param_list[2].value)
D10down = int(func.sub_param_list[3].value)
except KeyError:
print "Failed to load threshold value!"
f = functions.dynBiThreshold(D01up, D10up, D01down, D10down)
elif func.value == "wolfram":
try:
r = int(func.sub_param_list[0].value)
except KeyError:
print "Failed to load rule number!"
f = functions.wolfram(r)
elif func.value == "parity":
f = functions.parity
elif func.value == "majority":
f = functions.majority
elif func.value == "nor":
f = functions.nor
elif func.value == "nand":
f = functions.nand
else:
raise Exception(
"""Error: Unknown function type! Available options:
<threshold, indicator, biThreshold, inverseThreshold, dynBiThreshold, wolfram, parity, majority, nor, nand>"""
)
return f
def maxima(img):
height, width = img.shape
img_auxiliar = np.copy(img)
for j in range(0, height):
for i in range(0, width):
if img_auxiliar[j, i] > 0:
img_auxiliar[j, i] = img_auxiliar[j, i] - 1
img_auxiliar = geodesic_dilation(img, img_auxiliar)
img = img - img_auxiliar
img = f.threshold(img, 1)
return img
def remove_noise(image):
image = fs.threshold(image) # 이미지 이진화
mask = np.zeros(image.shape, np.uint8) # 보표 영역만 추출하기 위해 마스크 생성
cnt, labels, stats, centroids = cv2.connectedComponentsWithStats(
image) # 레이블링
for i in range(1, cnt):
x, y, w, h, area = stats[i]
if w > image.shape[1] * 0.5: # 보표 영역에만
cv2.rectangle(mask, (x, y, w, h), (255, 0, 0), -1) # 사각형 그리기
masked_image = cv2.bitwise_and(image, mask) # 보표 영역 추출
return masked_image