2022-11-07 15:24:33 +08:00

762 lines
28 KiB
Python

from rscder.utils.icons import IconInstance
from .SH import SH
from .LHBA import LHBA
from .OCD import OCD
from .AHT import AHT
from .ACD import ACD
import numpy as np
from datetime import datetime
from osgeo import gdal
import math
import 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
UNSUPER_CD = Register('无监督变化检测方法')
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
@UNSUPER_CD.register
class BasicCD(AlgFrontend):
@staticmethod
def get_name():
return '差分法'
@staticmethod
def get_icon():
return IconInstance().ARITHMETIC3
@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
@UNSUPER_CD.register
class LSTS(AlgFrontend):
@staticmethod
def get_name():
return 'LSTS'
@staticmethod
def get_icon():
return IconInstance().ARITHMETIC3
@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
@UNSUPER_CD.register
class CVAAlg(AlgFrontend):
@staticmethod
def get_name():
return 'CVA'
@staticmethod
def get_icon():
return IconInstance().ARITHMETIC3
@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
@UNSUPER_CD.register
class ACDAlg(AlgFrontend):
@staticmethod
def get_name():
return 'ACD'
@staticmethod
def get_icon():
return IconInstance().ARITHMETIC3
@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
@UNSUPER_CD.register
class AHTAlg(AlgFrontend):
@staticmethod
def get_name():
return 'AHT'
@staticmethod
def get_icon():
return IconInstance().ARITHMETIC3
@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
@UNSUPER_CD.register
class OCDAlg(AlgFrontend):
@staticmethod
def get_name():
return 'OCD'
@staticmethod
def get_icon():
return IconInstance().ARITHMETIC3
@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
@UNSUPER_CD.register
class LHBAAlg(AlgFrontend):
@staticmethod
def get_name():
return 'LHBA'
@staticmethod
def get_icon():
return IconInstance().ARITHMETIC3
@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
@UNSUPER_CD.register
class SHAlg(AlgFrontend):
@staticmethod
def get_name():
return 'SH'
@staticmethod
def get_icon():
return IconInstance().ARITHMETIC3
@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