2022-09-30 17:25:28 +08:00

691 lines
26 KiB
Python

from datetime import datetime
from osgeo import gdal
import math,os
import time
from PyQt5 import QtWidgets
from sklearn.cluster import k_means
from rscder.utils.geomath import geo2imageRC, imageRC2geo
from rscder.utils.project import Project, PairLayer
from misc import Register, AlgFrontend
VEG_CD = Register('植被变化检测方法')
import numpy as np
from .ACD import ACD
from .AHT import AHT
from .OCD import OCD
from .LHBA import LHBA
from .SH import SH
def warp(file,ds:gdal.Dataset,srcWin=[0,0,0,0]):
driver = gdal.GetDriverByName('GTiff')
xsize=ds.RasterXSize
ysize=ds.RasterYSize
geo=ds.GetGeoTransform()
orj=ds.GetProjection()
band=ds.RasterCount
if os.path.exists(file):
os.remove(file)
out_ds:gdal.Dataset=driver.Create(file, xsize, ysize, band, gdal.GDT_Byte)
out_ds.SetGeoTransform(geo)
out_ds.SetProjection(orj)
for b in range(1,band+1):
out_ds.GetRasterBand(b).WriteArray(ds.ReadAsArray(*srcWin,band_list=[b]),*(0,0))
del out_ds
@VEG_CD.register
class BasicCD(AlgFrontend):
@staticmethod
def get_name():
return '差分法'
@staticmethod
def run_alg(pth1:str,pth2:str,layer_parent:PairLayer,send_message = None,*args, **kargs):
ds1:gdal.Dataset=gdal.Open(pth1)
ds2:gdal.Dataset=gdal.Open(pth2)
cell_size = layer_parent.cell_size
xsize = layer_parent.size[0]
ysize = layer_parent.size[1]
band = ds1.RasterCount
yblocks = ysize // cell_size[1]
driver = gdal.GetDriverByName('GTiff')
out_tif = os.path.join(Project().other_path, 'temp.tif')
out_ds = driver.Create(out_tif, xsize, ysize, 1, gdal.GDT_Float32)
geo=layer_parent.grid.geo
proj=layer_parent.grid.proj
out_ds.SetGeoTransform(geo)
out_ds.SetProjection(proj)
max_diff = 0
min_diff = math.inf
start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
for j in range(yblocks + 1):#该改这里了
if send_message is not None:
send_message.emit(f'计算{j}/{yblocks}')
block_xy1 = (start1x, start1y+j * cell_size[1])
block_xy2 = (start2x,start2y+j*cell_size[1])
block_xy=(0,j * cell_size[1])
if block_xy1[1] > end1y or block_xy2[1] > end2y:
break
block_size=(xsize, cell_size[1])
block_size1 = (xsize, cell_size[1])
block_size2 = (xsize,cell_size[1])
if block_xy[1] + block_size[1] > ysize:
block_size = (xsize, ysize - block_xy[1])
if block_xy1[1] + block_size1[1] > end1y:
block_size1 = (xsize,end1y - block_xy1[1])
if block_xy2[1] + block_size2[1] > end2y:
block_size2 = (xsize, end2y - block_xy2[1])
block_data1 = ds1.ReadAsArray(*block_xy1, *block_size1)
block_data2 = ds2.ReadAsArray(*block_xy2, *block_size2)
if band == 1:
block_data1 = block_data1[None, ...]
block_data2 = block_data2[None, ...]
# pdb.set_trace()
block_diff = block_data1.sum(0) - block_data2.sum(0)
block_diff = block_diff.astype(np.float32)
block_diff = np.abs(block_diff)
min_diff = min(min_diff, block_diff[block_diff > 0].min())
max_diff = max(max_diff, block_diff.max())
out_ds.GetRasterBand(1).WriteArray(block_diff, *block_xy)
if send_message is not None:
send_message.emit(f'完成{j}/{yblocks}')
del ds2
del ds1
out_ds.FlushCache()
del out_ds
if send_message is not None:
send_message.emit('归一化概率中...')
temp_in_ds = gdal.Open(out_tif)
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
out_normal_ds = driver.Create(out_normal_tif, xsize, ysize, 1, gdal.GDT_Byte)
out_normal_ds.SetGeoTransform(geo)
out_normal_ds.SetProjection(proj)
# hist = np.zeros(256, dtype=np.int32)
for j in range(yblocks+1):
block_xy = (0, j * cell_size[1])
if block_xy[1] > ysize:
break
block_size = (xsize, cell_size[1])
if block_xy[1] + block_size[1] > ysize:
block_size = (xsize, ysize - block_xy[1])
block_data = temp_in_ds.ReadAsArray(*block_xy, *block_size)
block_data = (block_data - min_diff) / (max_diff - min_diff) * 255
block_data = block_data.astype(np.uint8)
out_normal_ds.GetRasterBand(1).WriteArray(block_data, *block_xy)
# hist_t, _ = np.histogram(block_data, bins=256, range=(0, 256))
# hist += hist_t
# print(hist)
del temp_in_ds
del out_normal_ds
try:
os.remove(out_tif)
except:
pass
if send_message is not None:
send_message.emit('差分法计算完成')
return out_normal_tif
@VEG_CD.register
class LSTS(AlgFrontend):
@staticmethod
def get_name():
return 'LSTS'
@staticmethod
def get_widget(parent=None):
widget = QtWidgets.QWidget(parent)
return widget
@staticmethod
def get_params(widget=None):
return dict(n=5, w_size=(3,3))
@staticmethod
def run_alg(pth1:str,pth2:str,layer_parent:PairLayer,send_message=None,n=5,w_size=(3,3), *args, **kws):
ds1:gdal.Dataset=gdal.Open(pth1)
ds2:gdal.Dataset=gdal.Open(pth2)
cell_size = layer_parent.cell_size
xsize = layer_parent.size[0]
ysize = layer_parent.size[1]
band = ds1.RasterCount
yblocks = ysize // cell_size[1]
driver = gdal.GetDriverByName('GTiff')
out_tif = os.path.join(Project().other_path, '%d.tif'%(int(datetime.now().timestamp() * 1000)))
out_ds = driver.Create(out_tif, xsize, ysize, 1, gdal.GDT_Float32)
geo=layer_parent.grid.geo
proj=layer_parent.grid.proj
out_ds.SetGeoTransform(geo)
out_ds.SetProjection(proj)
pixnum=w_size[0]*w_size[1]
# send_message.emit('pixnum:'pixnum)
max_diff = 0
min_diff = math.inf
win_h=w_size[0]//2 #half hight of window
win_w=w_size[1]//2 #half width of window
a=[[(i+1)**j for j in range(n+1)] for i in range(pixnum)]
A=np.array(a).astype(np.float64)#
k_=np.array(range(1,n+1))
df1=np.zeros(pixnum).astype(np.float64)
df2=np.zeros(pixnum).astype(np.float64)
start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
for j in range(yblocks + 1):
if send_message is not None:
send_message.emit(f'计算{j}/{yblocks}')
block_xy1 = (start1x, start1y+j * cell_size[1])
block_xy2 = (start2x,start2y+j*cell_size[1])
block_xy=(0,j * cell_size[1])
if block_xy1[1] > end1y or block_xy2[1] > end2y:
break
block_size=(xsize, cell_size[1])
block_size1 = (xsize, cell_size[1])
block_size2 = (xsize,cell_size[1])
if block_xy[1] + block_size[1] > ysize:
block_size = (xsize, ysize - block_xy[1])
if block_xy1[1] + block_size1[1] > end1y:
block_size1 = (xsize,end1y - block_xy1[1])
if block_xy2[1] + block_size2[1] > end2y:
block_size2 = (xsize, end2y - block_xy2[1])
block_data1 = ds1.ReadAsArray(*block_xy1, *block_size1)
block_data2 = ds2.ReadAsArray(*block_xy2, *block_size2)
if band == 1:
block_data1 = block_data1[None, ...]
block_data2 = block_data2[None, ...]
# pdb.set_trace()
else:
block_data1=np.mean(block_data1,0)
block_data2=np.mean(block_data2,0)
block_diff=np.zeros(block_data1.shape).astype(np.float64)
for i in range(win_h,block_size1[1]-win_h):
for j_ in range(win_w,block_size1[0]-win_w):
pix=0
#get b
# b1=block_data[i+win_h:i+win_h] c in range(j_-win_w,j_+win_w+1)
b1=block_data1[i-win_h:i+win_h+1,j_-win_w:j_+win_w+1]
b2=block_data2[i-win_h:i+win_h+1,j_-win_w:j_+win_w+1]
b1=[b if (r+1)//2 else b[::-1] for r,b in enumerate(b1)]
b2=[b if (r+1)//2 else b[::-1] for r,b in enumerate(b2)]
b1=np.expand_dims(np.concatenate(b1,0),1)
b2=np.expand_dims(np.concatenate(b2,0),1)
x1=np.squeeze(np.linalg.pinv(A).dot(b1))
x2=np.squeeze(np.linalg.pinv(A).dot(b2))
#df
k_=range(1,n+1)
for pix in range(1,pixnum+1):
df1[pix-1]=x1[1:n+1].dot(np.array([k*(pix**(k-1)) for k in k_]))
df2[pix-1]=x2[1:n+1].dot(np.array([k*(pix**(k-1)) for k in k_]))
#distance 欧式距离
block_diff[i][j_]=np.dot(df1-df2,df1-df2)**0.5
min_diff = min(min_diff, block_diff[block_diff > 0].min())
max_diff = max(max_diff, block_diff.max())
out_ds.GetRasterBand(1).WriteArray(block_diff, *block_xy)
send_message.emit(f'完成{j}/{yblocks}')
del ds2
del ds1
out_ds.FlushCache()
del out_ds
if send_message is not None:
send_message.emit('归一化概率中...')
temp_in_ds = gdal.Open(out_tif)
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
out_normal_ds = driver.Create(out_normal_tif, xsize, ysize, 1, gdal.GDT_Byte)
out_normal_ds.SetGeoTransform(geo)
out_normal_ds.SetProjection(proj)
# hist = np.zeros(256, dtype=np.int32)
for j in range(yblocks+1):
block_xy = (0, j * cell_size[1])
if block_xy[1] > ysize:
break
block_size = (xsize, cell_size[1])
if block_xy[1] + block_size[1] > ysize:
block_size = (xsize, ysize - block_xy[1])
block_data = temp_in_ds.ReadAsArray(*block_xy, *block_size)
block_data = (block_data - min_diff) / (max_diff - min_diff) * 255
block_data = block_data.astype(np.uint8)
out_normal_ds.GetRasterBand(1).WriteArray(block_data, *block_xy)
# hist_t, _ = np.histogram(block_data, bins=256, range=(0, 256))
# hist += hist_t
# print(hist)
del temp_in_ds
del out_normal_ds
try:
os.remove(out_tif)
except:
pass
if send_message is not None:
send_message.emit('LSTS法计算完成')
return out_normal_tif
@VEG_CD.register
class CVAAlg(AlgFrontend):
@staticmethod
def get_name():
return 'CVA'
@staticmethod
def run_alg(pth1:str,pth2:str,layer_parent:PairLayer,send_message = None, *args, **kargs):
ds1:gdal.Dataset=gdal.Open(pth1)
ds2:gdal.Dataset=gdal.Open(pth2)
cell_size = layer_parent.cell_size
xsize = layer_parent.size[0]
ysize = layer_parent.size[1]
band = ds1.RasterCount
yblocks = ysize // cell_size[1]
driver = gdal.GetDriverByName('GTiff')
out_tif = os.path.join(Project().other_path, 'temp.tif')
out_ds = driver.Create(out_tif, xsize, ysize, 1, gdal.GDT_Float32)
geo=layer_parent.grid.geo
proj=layer_parent.grid.proj
out_ds.SetGeoTransform(geo)
out_ds.SetProjection(proj)
max_diff = 0
min_diff = math.inf
start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
for j in range(yblocks + 1):
if send_message is not None:
send_message.emit(f'计算{j}/{yblocks}')
block_xy1 = (start1x, start1y+j * cell_size[1])
block_xy2 = (start2x,start2y+j*cell_size[1])
block_xy=(0,j * cell_size[1])
if block_xy1[1] > end1y or block_xy2[1] > end2y:
break
block_size=(xsize, cell_size[1])
block_size1 = (xsize, cell_size[1])
block_size2 = (xsize,cell_size[1])
if block_xy[1] + block_size[1] > ysize:
block_size = (xsize, ysize - block_xy[1])
if block_xy1[1] + block_size1[1] > end1y:
block_size1 = (xsize,end1y - block_xy1[1])
if block_xy2[1] + block_size2[1] > end2y:
block_size2 = (xsize, end2y - block_xy2[1])
block_data1 = ds1.ReadAsArray(*block_xy1, *block_size1)
block_data2 = ds2.ReadAsArray(*block_xy2, *block_size2)
if band == 1:
block_data1 = block_data1[None, ...]
block_data2 = block_data2[None, ...]
# pdb.set_trace()
block_diff=np.sum((block_data1-block_data2)**2,0)**0.5
min_diff = min(min_diff, block_diff[block_diff > 0].min())
max_diff = max(max_diff, block_diff.max())
out_ds.GetRasterBand(1).WriteArray(block_diff, *block_xy)
if send_message is not None:
send_message.emit(f'完成{j}/{yblocks}')
del ds2
del ds1
out_ds.FlushCache()
del out_ds
if send_message is not None:
send_message.emit('归一化概率中...')
temp_in_ds = gdal.Open(out_tif)
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
out_normal_ds = driver.Create(out_normal_tif, xsize, ysize, 1, gdal.GDT_Byte)
out_normal_ds.SetGeoTransform(geo)
out_normal_ds.SetProjection(proj)
# hist = np.zeros(256, dtype=np.int32)
for j in range(yblocks+1):
block_xy = (0, j * cell_size[1])
if block_xy[1] > ysize:
break
block_size = (xsize, cell_size[1])
if block_xy[1] + block_size[1] > ysize:
block_size = (xsize, ysize - block_xy[1])
block_data = temp_in_ds.ReadAsArray(*block_xy, *block_size)
block_data = (block_data - min_diff) / (max_diff - min_diff) * 255
block_data = block_data.astype(np.uint8)
out_normal_ds.GetRasterBand(1).WriteArray(block_data, *block_xy)
# hist_t, _ = np.histogram(block_data, bins=256, range=(0, 256))
# hist += hist_t
# print(hist)
del temp_in_ds
del out_normal_ds
try:
os.remove(out_tif)
except:
pass
if send_message is not None:
send_message.emit('欧式距离计算完成')
return out_normal_tif
@VEG_CD.register
class ACDAlg(AlgFrontend):
@staticmethod
def get_name():
return 'ACD'
@staticmethod
def run_alg(pth1:str,pth2:str,layer_parent:PairLayer,send_message = None, *args, **kargs):
if send_message is None:
class Empty:
def emit(self, *args, **kws):
print(args)
send_message = Empty()
# send_message.emit = print
xsize = layer_parent.size[0]
ysize = layer_parent.size[1]
geo=layer_parent.grid.geo
proj=layer_parent.grid.proj
#提取公共部分
send_message.emit('提取重叠区域数据.....')
ds2:gdal.Dataset=gdal.Open(pth2)
temp_tif2 = os.path.join(Project().other_path,'temp2.tif')
start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
warp(temp_tif2,ds2,srcWin=[start2x,start2y,xsize,ysize])
del ds2
send_message.emit('图像二提取完成')
ds1:gdal.Dataset=gdal.Open(pth1)
temp_tif1 = os.path.join(Project().other_path, 'temp1.tif')
start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
warp(temp_tif1,ds1,srcWin=[start1x,start1y,xsize,ysize])
del ds1
send_message.emit('图像一提取完成')
#运算
send_message.emit('开始ACD计算.....')
time.sleep(0.1)
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
ACD(temp_tif1,temp_tif2,out_normal_tif)
#添加投影
send_message.emit('录入投影信息.....')
time.sleep(0.1)
ds=gdal.Open(out_normal_tif,1)
ds.SetGeoTransform(geo)
ds.SetProjection(proj)
del ds
return out_normal_tif
@VEG_CD.register
class AHTAlg(AlgFrontend):
@staticmethod
def get_name():
return 'AHT'
@staticmethod
def run_alg(pth1:str,pth2:str,layer_parent:PairLayer,send_message = None, *args, **kargs):
if send_message is None:
class Empty:
def emit(self, *args, **kws):
print(args)
send_message = Empty()
xsize = layer_parent.size[0]
ysize = layer_parent.size[1]
geo=layer_parent.grid.geo
proj=layer_parent.grid.proj
#提取公共部分
send_message.emit('提取重叠区域数据.....')
ds2:gdal.Dataset=gdal.Open(pth2)
temp_tif2 = os.path.join(Project().other_path,'temp2.tif')
start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
warp(temp_tif2,ds2,srcWin=[start2x,start2y,xsize,ysize])
del ds2
send_message.emit('图像二提取完成')
ds1:gdal.Dataset=gdal.Open(pth1)
temp_tif1 = os.path.join(Project().other_path, 'temp1.tif')
start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
warp(temp_tif1,ds1,srcWin=[start1x,start1y,xsize,ysize])
del ds1
send_message.emit('图像一提取完成')
#运算
send_message.emit('开始AHT计算.....')
time.sleep(0.1)
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
AHT(temp_tif1,temp_tif2,out_normal_tif)
#添加投影
send_message.emit('录入投影信息.....')
time.sleep(0.1)
ds=gdal.Open(out_normal_tif,1)
ds.SetGeoTransform(geo)
ds.SetProjection(proj)
del ds
return out_normal_tif
@VEG_CD.register
class OCDAlg(AlgFrontend):
@staticmethod
def get_name():
return 'OCD'
@staticmethod
def run_alg(pth1:str,pth2:str,layer_parent:PairLayer,send_message = None, *args, **kargs):
if send_message is None:
class Empty:
def emit(self, *args, **kws):
print(args)
send_message = Empty()
xsize = layer_parent.size[0]
ysize = layer_parent.size[1]
geo=layer_parent.grid.geo
proj=layer_parent.grid.proj
#提取公共部分
send_message.emit('提取重叠区域数据.....')
ds2:gdal.Dataset=gdal.Open(pth2)
temp_tif2 = os.path.join(Project().other_path,'temp2.tif')
start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
warp(temp_tif2,ds2,srcWin=[start2x,start2y,xsize,ysize])
del ds2
send_message.emit('图像二提取完成')
ds1:gdal.Dataset=gdal.Open(pth1)
temp_tif1 = os.path.join(Project().other_path, 'temp1.tif')
start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
warp(temp_tif1,ds1,srcWin=[start1x,start1y,xsize,ysize])
del ds1
send_message.emit('图像一提取完成')
#运算
send_message.emit('开始OCD计算.....')
time.sleep(0.1)
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
OCD(temp_tif1,temp_tif2,out_normal_tif,Project().other_path)
#添加投影
send_message.emit('录入投影信息.....')
time.sleep(0.1)
ds=gdal.Open(out_normal_tif,1)
ds.SetGeoTransform(geo)
ds.SetProjection(proj)
del ds
return out_normal_tif
@VEG_CD.register
class LHBAAlg(AlgFrontend):
@staticmethod
def get_name():
return 'LHBA'
@staticmethod
def run_alg(pth1:str,pth2:str,layer_parent:PairLayer,send_message = None, *args, **kargs):
if send_message is None:
class Empty:
def emit(self, *args, **kws):
print(args)
send_message = Empty()
xsize = layer_parent.size[0]
ysize = layer_parent.size[1]
geo=layer_parent.grid.geo
proj=layer_parent.grid.proj
#提取公共部分
send_message.emit('提取重叠区域数据.....')
ds2:gdal.Dataset=gdal.Open(pth2)
temp_tif2 = os.path.join(Project().other_path,'temp2.tif')
start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
warp(temp_tif2,ds2,srcWin=[start2x,start2y,xsize,ysize])
del ds2
send_message.emit('图像二提取完成')
ds1:gdal.Dataset=gdal.Open(pth1)
temp_tif1 = os.path.join(Project().other_path, 'temp1.tif')
start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
warp(temp_tif1,ds1,srcWin=[start1x,start1y,xsize,ysize])
del ds1
send_message.emit('图像一提取完成')
#运算
send_message.emit('开始LHBA计算.....')
time.sleep(0.1)
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
LHBA(temp_tif1,temp_tif2,out_normal_tif)
#添加投影
send_message.emit('录入投影信息.....')
time.sleep(0.1)
ds=gdal.Open(out_normal_tif,1)
ds.SetGeoTransform(geo)
ds.SetProjection(proj)
del ds
return out_normal_tif
@VEG_CD.register
class SHAlg(AlgFrontend):
@staticmethod
def get_name():
return 'SH'
@staticmethod
def run_alg(pth1:str,pth2:str,layer_parent:PairLayer,send_message = None, *args, **kargs):
if send_message is None:
class Empty:
def emit(self, *args, **kws):
print(args)
send_message = Empty()
xsize = layer_parent.size[0]
ysize = layer_parent.size[1]
geo=layer_parent.grid.geo
proj=layer_parent.grid.proj
#提取公共部分
send_message.emit('提取重叠区域数据.....')
ds2:gdal.Dataset=gdal.Open(pth2)
temp_tif2 = os.path.join(Project().other_path,'temp2.tif')
start2x,start2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end2x,end2y=geo2imageRC(ds2.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
warp(temp_tif2,ds2,srcWin=[start2x,start2y,xsize,ysize])
del ds2
send_message.emit('图像二提取完成')
ds1:gdal.Dataset=gdal.Open(pth1)
temp_tif1 = os.path.join(Project().other_path, 'temp1.tif')
start1x,start1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[0],layer_parent.mask.xy[1])
end1x,end1y=geo2imageRC(ds1.GetGeoTransform(),layer_parent.mask.xy[2],layer_parent.mask.xy[3])
warp(temp_tif1,ds1,srcWin=[start1x,start1y,xsize,ysize])
del ds1
send_message.emit('图像一提取完成')
#运算
send_message.emit('开始SH计算.....')
time.sleep(0.1)
out_normal_tif = os.path.join(Project().cmi_path, '{}_{}_cmi.tif'.format(layer_parent.name, int(np.random.rand() * 100000)))
SH(temp_tif1,temp_tif2,out_normal_tif)
#添加投影
send_message.emit('录入投影信息.....')
time.sleep(0.1)
ds=gdal.Open(out_normal_tif,1)
ds.SetGeoTransform(geo)
ds.SetProjection(proj)
del ds
return out_normal_tif