def setup(self):
data=read.load(self.offsets[0],file=self.filename,type=self.type)
if self.xrange==None:
self.xrange=[data.getBounds()[0],data.getBounds()[1]]
if self.yrange==None:
self.yrange=[data.getBounds()[2],data.getBounds()[3]]
def setup(self):
data = read.load(self.offsets[0], file=self.filename, type=self.type)
if self.xrange == None:
self.xrange = [data.getBounds()[0], data.getBounds()[1]]
if self.yrange == None:
self.yrange = [data.getBounds()[2], data.getBounds()[3]]
def readData(self):
if self.type != 'vti':
if self.xrange[0] <=0. :
self.data=read.load(self.offset,file=self.filenameout,type=self.type,mirrorPlane=0)
else:
self.data=read.load(self.offset,file=self.filenameout,type=self.type)
else:
self.data=read.loadvti(self.offset,file=self.filenameout)
self.nx=self.data.nx
self.ny=self.data.nx
if self.xrange == None:
self.xrange = np.array(self.data.getBounds()[0:2])
if self.yrange == None:
self.yrange = np.array(self.data.getBounds()[2:4])
self.Lx = self.xrange[1] - self.xrange[0]
self.Ly = self.yrange[1] - self.yrange[0]
def readData(self):
if self.type != 'vti':
if self.xrange[0] <= 0.:
self.data = read.load(self.offset,
file=self.filenameout,
type=self.type,
mirrorPlane=0)
else:
self.data = read.load(self.offset,
file=self.filenameout,
type=self.type)
else:
self.data = read.loadvti(self.offset, file=self.filenameout)
self.nx = self.data.nx
self.ny = self.data.nx
if self.xrange == None:
self.xrange = np.array(self.data.getBounds()[0:2])
if self.yrange == None:
self.yrange = np.array(self.data.getBounds()[2:4])
self.Lx = self.xrange[1] - self.xrange[0]
self.Ly = self.yrange[1] - self.yrange[0]
def run(self):
self.setup()
offsets=np.arange(self.offsets[1]+1-self.offsets[0])+self.offsets[0]
for offset in offsets:
fo=''.join([self.filenameout,str(offset).zfill(4),'.png'])
data=read.load(offset,file=self.filename,type=self.type)
# exec ''.join(['var=',self.function])
var = self.function(data)
self.polyplot = polyplot(var,data=data,
nlevels=self.nlevels,grid=self.grid,cmap=self.cmap,
orientation=self.orientation,
xrange=self.xrange,yrange=self.yrange,
min=self.min,max=self.max,
filenameout=fo
)
self.polyplot.save(fo)
plt.close()
def run(self):
self.setup()
offsets = np.arange(self.offsets[1] + 1 -
self.offsets[0]) + self.offsets[0]
for offset in offsets:
fo = ''.join([self.filenameout, str(offset).zfill(4), '.png'])
data = read.load(offset, file=self.filename, type=self.type)
# exec ''.join(['var=',self.function])
var = self.function(data)
self.polyplot = polyplot(var,
data=data,
nlevels=self.nlevels,
grid=self.grid,
cmap=self.cmap,
orientation=self.orientation,
xrange=self.xrange,
yrange=self.yrange,
min=self.min,
max=self.max,
filenameout=fo)
self.polyplot.save(fo)
plt.close()
def getFromOffset(offset, filenameout='data', type='pvtu'):
data = read.load(offset, file=filenameout, type=type)
myradii = get(data)
myradii['offset'] = offset
return myradii
def getFromOffset(offset,filenameout='data',type='pvtu'):
data = read.load(offset,file=filenameout,type=type)
myradii=get(data)
myradii['offset'] = offset
return myradii
def output():
file = os.listdir(data_dir)
filesp = file[0].split('.')
imgwritpath = write_dir + file[0]
writepath = write_dir + filesp[0] + '.xml'
collection['file'] = file[0]
read_path = data_dir + file[0]
## png图片
# img = cv.imread(read_path)
# ### 原图
img = read.load(read_path)
img = cv.flip(img, 0, dst=None)
## 1 归一化到0，255的数据
# image= img/255
## 2 截取到-0.75，0.75区间的数据/3
img = np.expand_dims(img, -1)
imgShape = np.shape(img)
collection['shape'] = imgShape
inputTest = np.expand_dims(img, 0)
x = tf.placeholder(tf.float32,
shape=[1, imgShape[0], imgShape[1], channel])
y = U_net.inference(x, is_training=False)
variables_to_restore = []
for v in tf.global_variables():
variables_to_restore.append(v)
saver = tf.train.Saver(variables_to_restore,
write_version=tf.train.SaverDef.V2,
max_to_keep=None)
tf.global_variables_initializer().run()
saver.restore(sess, savepath)
output = sess.run(y, feed_dict={x: inputTest})
out = np.squeeze(output).astype(np.uint8)
## 1 归一化到0，255的数据
# out = out*255
## 2 截取到-0.75，0.75区间的数据
# img = ((np.squeeze(img) + 0.75) / 1.5 * 255).astype(np.uint8)
# out = out * 255
## 3 映射到0，1的数据
img = ((np.squeeze(inputTest)) * 255).astype(np.uint8)
out = np.squeeze(output).astype(np.uint8)
out = out * 255
kernel = cv.getStructuringElement(cv.MORPH_RECT, (5, 5)) # 定义结构元素
outclosing = cv.morphologyEx(out, cv.MORPH_CLOSE, kernel) # 闭运算
postproce.contourmask(img, outclosing, collection)
wrx.writeInfoToXml(writepath, collection)
# cv.imwrite(imgwritpath,img)
cv.namedWindow('imgrec', 0)
cv.resizeWindow('imgrec', 500, 500)
cv.imshow('imgrec', img)
cv.namedWindow('output', 0)
cv.resizeWindow('output', 500, 500)
cv.imshow('output', outclosing)
cv.waitKey(0)
cv.destroyAllWindows()
