from . import AI_METHOD from plugins.misc import AlgFrontend from rscder.utils.icons import IconInstance from rscder.utils.project import PairLayer from osgeo import gdal, gdal_array import os from rscder.utils.project import Project from rscder.utils.geomath import geo2imageRC, imageRC2geo import math from .packages import get_model import numpy as np class BasicAICD(AlgFrontend): @staticmethod def get_icon(): return IconInstance().ARITHMETIC3 @staticmethod def run_alg(pth1: str, pth2: str, layer_parent: PairLayer, send_message=None, model=None, *args, **kargs): if model is None and send_message is not None: send_message.emit('未能加载模型！') return ds1: gdal.Dataset = gdal.Open(pth1) ds2: gdal.Dataset = gdal.Open(pth2) cell_size = (512, 512) xsize = layer_parent.size[0] ysize = layer_parent.size[1] band = ds1.RasterCount yblocks = ysize // cell_size[1] xblocks = xsize // cell_size[0] 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}') for i in range(xblocks +1): block_xy1 = [start1x + i * cell_size[0], start1y+j * cell_size[1]] block_xy2 = [start2x + i * cell_size[0], start2y+j * cell_size[1]] block_xy = [i * cell_size[0], j * cell_size[1]] if block_xy1[1] > end1y or block_xy2[1] > end2y: break if block_xy1[0] > end1x or block_xy2[0] > end2x: break block_size = list(cell_size) if block_xy[1] + block_size[1] > ysize: block_xy[1] = (ysize - block_size[1]) if block_xy[0] + block_size[0] > xsize: block_xy[0] = ( xsize - block_size[0]) if block_xy1[1] + block_size[1] > end1y: block_xy1[1] = (end1y - block_size[1]) if block_xy1[0] + block_size[0] > end1x: block_xy1[0] = (end1x - block_size[0]) if block_xy2[1] + block_size[1] > end2y: block_xy2[1] = (end2y - block_size[1]) if block_xy2[0] + block_size[0] > end2x: block_xy2[0] = (end2x - block_size[0]) # if block_size1[0] * block_size1[1] == 0 or block_size2[0] * block_size2[1] == 0: # continue block_data1 = ds1.ReadAsArray(*block_xy1, *block_size) block_data2 = ds2.ReadAsArray(*block_xy2, *block_size) # if block_data1.shape[0] == 0: # continue if band == 1: block_data1 = block_data1[None, ...] block_data2 = block_data2[None, ...] block_diff = model(block_data1, block_data2) 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]) np.seterr(divide='ignore',invalid='ignore') block_data = temp_in_ds.ReadAsArray(*block_xy, *block_size) max_diff=block_data.max() min_diff=block_data.min() 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) # os.system('pause') # 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.system('pause') os.remove(out_tif) except: pass if send_message is not None: send_message.emit('计算完成') return out_normal_tif @AI_METHOD.register class DVCA(BasicAICD): @staticmethod def get_name(): return 'DVCA' @staticmethod def run_alg(pth1: str, pth2: str, layer_parent: PairLayer, send_message=None, *args, **kargs): model = get_model('DVCA') return BasicAICD.run_alg(pth1, pth2, layer_parent, send_message, model, *args, **kargs) @AI_METHOD.register class DPFCN(BasicAICD): @staticmethod def get_name(): return 'DPFCN' @staticmethod def run_alg(pth1: str, pth2: str, layer_parent: PairLayer, send_message=None, *args, **kargs): model = get_model('DPFCN') return BasicAICD.run_alg(pth1, pth2, layer_parent, send_message, model, *args, **kargs) @AI_METHOD.register class RCNN(BasicAICD): @staticmethod def get_name(): return 'RCNN' @staticmethod def run_alg(pth1: str, pth2: str, layer_parent: PairLayer, send_message=None, *args, **kargs): model = get_model('RCNN') return BasicAICD.run_alg(pth1, pth2, layer_parent, send_message, model, *args, **kargs)