def FouriorTrans():
if os.path.exists("Output/"):
if Init.SystemJudge() == 0:
os.system("rm -r Output")
else:
os.system("rmdir /s /q directory")
NameArr = Pretreatment.FigureInput(1)
try:
if NameArr == -1:
return
except:
pass
#Figure traversal
for kase in range(0, len(NameArr)):
img = np.array(Image.open(NameArr[kase]).convert("L"))
Statistic = [0 for n in range(0, 260)]
TTL = 0
for i in range(0, len(img)):
for j in range(0, len(img[i])):
Statistic[img[i][j]] += 1
TTL += 1
#Drecrete PDE
Prob = [0.00 for n in range(260)]
for i in range(0, len(Prob)):
Prob[i] = Statistic[i] / TTL
#HF = np.fft.fft(Prob).real
fig1 = plt.figure()
ax = fig1.add_subplot(111)
plt.xlim(-1, 260)
plt.ylim(0, 0.2)
#Printing loop
for i in range(0, len(Prob)):
ax.add_patch(patches.Rectangle((i, 0), 1, Prob[i], color = 'black'))
Name = ""
Hajimari = False
for i in range(len(NameArr[kase]) - 1, -1, -1):
if NameArr[kase][i] == ".":
Hajimari = True
continue
elif NameArr[kase][i] == "/":
break
else:
if Hajimari == False:
continue
else:
Name = NameArr[kase][i] + Name
Name += "_Histogram.png"
print(Name)
plt.savefig(Name)
return
def BWError():
if os.path.exists("Output/"):
if Init.SystemJudge() == 0:
os.system("rm -r Output")
else:
os.system("rmdir /s /q directory")
NameArr = Pretreatment.FigureInput(1)
try:
if NameArr == -1:
return
except:
pass
#Figure traversal
for kase in range(0, len(NameArr)):
img = np.array(Image.open(NameArr[kase]).convert("L"))
"""
for i in range(0, len(img)):
for j in range(0, len(img[i])):
if random.randint(1, 50) == 1:
img[i][j] += np.random.normal(img[i][j], 64)
img[i][j] = max(0, img[i][j])
img[i][j] = min(255, img[i][j])
"""
Name = "Figure_"
Name += str(Init.GetTime())
Name += ".png"
Pretreatment.Output(img, Name, 2)
def MainFunction():
#CRIEA Start!
if os.path.exists("Output/"):
if Init.SystemJudge() == 0:
os.system("rm -r Output")
else:
os.system("rmdir /s /q directory")
NameArr = Pretreatment.FigureInput(1)
try:
if NameArr == -1:
return
except:
pass
#Figure traversal
for kase in range(0, len(NameArr)):
img = np.array(Image.open(NameArr[kase]).convert("L"))
img = Pretreatment.BFSmooth(img)
[Tobimg, NodeInfo] = Algorithm.Toboggan(img)
[Upground, Background] = Algorithm.HandSeed(Tobimg, img, Surround)
Seeds = Upground | Background
ProbBlock = []
VarL = 0
if Method == "Lap":
NodeInfo, VarL = Functions.SeedFirst(NodeInfo, Seeds)
LapEqu = Algorithm.Laplacian(NodeInfo, VarL)
ProbBlock = Functions.LinearEquation(LapEqu,
len(NodeInfo) - VarL, VarL)
"""
def MainFunction():
if os.path.exists("Output/"):
if Init.SystemJudge() == 0:
os.system("rm -r Output")
else:
os.system("rmdir /s /q directory")
NameArr = Pretreatment.FigureInput(1)
try:
if NameArr == -1:
return
except:
pass
#Figure traversal
for kase in range(0, len(NameArr)):
img = np.array(Image.open(NameArr[kase]).convert("L"))
img1 = img.deepcopy()