【GIS】GDAL Python 影像裁剪
阿新 • • 發佈：2018-11-30
# -*- coding: utf-8 -*- """ Created on Fri Nov 30 11:45:03 2018 @author: Administrator """ from osgeo import gdal from osgeo import osr import numpy as np import math import time lonMeter = 0.00001141 latMeter = 0.00000899 #MeterParam = 0.00001 * 42496 / (124.44282531738276-124.3288421630859) MeterParam = 3.7282702222226876 defgetSRSPair(dataset): ''' 獲得給定資料的投影參考系和地理參考系 :param dataset: GDAL地理資料 :return: 投影參考系和地理參考系 ''' prosrs = osr.SpatialReference() prosrs.ImportFromWkt(dataset.GetProjection()) geosrs = prosrs.CloneGeogCS() return prosrs, geosrs def geo2lonlat(dataset, x, y): '''將投影座標轉為經緯度座標（具體的投影座標系由給定資料確定） :param dataset: GDAL地理資料 :param x: 投影座標x :param y: 投影座標y :return: 投影座標(x, y)對應的經緯度座標(lon, lat) ''' prosrs, geosrs = getSRSPair(dataset) ct = osr.CoordinateTransformation(prosrs, geosrs) coords = ct.TransformPoint(x, y) return coords[:2]def lonlat2geo(dataset, lon, lat): ''' 將經緯度座標轉為投影座標（具體的投影座標系由給定資料確定） :param dataset: GDAL地理資料 :param lon: 地理座標lon經度 :param lat: 地理座標lat緯度 :return: 經緯度座標(lon, lat)對應的投影座標 ''' prosrs, geosrs = getSRSPair(dataset) ct = osr.CoordinateTransformation(geosrs, prosrs) coords = ct.TransformPoint(lon, lat) return coords[:2] def imagexy2geo(dataset, row, col): ''' 根據GDAL的六引數模型將影像圖上座標（行列號）轉為投影座標或地理座標（根據具體資料的座標系統轉換） :param dataset: GDAL地理資料 :param row: 畫素的行號 :param col: 畫素的列號 :return: 行列號(row, col)對應的投影座標或地理座標(x, y) ''' trans = dataset.GetGeoTransform() px = trans[0] + col * trans[1] + row * trans[2] py = trans[3] + col * trans[4] + row * trans[5] return px, py def geo2imagexy(dataset, x, y): ''' 根據GDAL的六 引數模型將給定的投影或地理座標轉為影像圖上座標（行列號） :param dataset: GDAL地理資料 :param x: 投影或地理座標x :param y: 投影或地理座標y :return: 影座標或地理座標(x, y)對應的影像圖上行列號(row, col) ''' trans = dataset.GetGeoTransform() a = np.array([[trans[1], trans[2]], [trans[4], trans[5]]]) b = np.array([x - trans[0], y - trans[3]]) return np.linalg.solve(a, b) # 使用numpy的linalg.solve進行二元一次方程的求解 def imagexy2lonlat(dataset,row, col): ''' 影像行列轉經緯度： ：通過影像行列轉平面座標 ：平面座標轉經緯度 ''' coords = imagexy2geo(dataset, row, col) coords2 = geo2lonlat(dataset,coords[0], coords[1]) return (coords2[0], coords2[1]) def lonlat2imagexy(dataset,x, y): ''' 影像行列轉經緯度： ：通過經緯度轉平面座標 ：平面座標轉影像行列 ''' coords = lonlat2geo(dataset, x, y) coords2 = geo2imagexy(dataset,coords[0], coords[1]) return (int(round(abs(coords2[0]))), int(round(abs(coords2[1])))) if __name__ == '__main__': gdal.AllRegister() dataset = gdal.Open(r"D:\RSData\DAQING_SHAERTU\薩爾圖區_大圖：拼接\L19.tif") print('資料投影：') projection = dataset.GetProjection() print(projection) print('資料的大小（行，列）：') print('(%s %s)' % (dataset.RasterYSize, dataset.RasterXSize)) geotransform = dataset.GetGeoTransform() print('地理座標：') print(geotransform) x = 464201 y = 5818760 lon = 122.47242 lat = 52.51778 row = 0 col = 0 # print('投影座標 -> 經緯度：') # coords = geo2lonlat(dataset, x, y) # print('(%s, %s)->(%s, %s)' % (x, y, coords[0], coords[1])) # # print('經緯度 -> 投影座標：') # coords = lonlat2geo(dataset, lon, lat) # print('(%s, %s)->(%s, %s)' % (lon, lat, coords[0], coords[1])) # # print('圖上座標 -> 投影座標：') # coords = imagexy2geo(dataset, row, col) # print('(%s, %s)->(%s, %s)' % (row, col, coords[0], coords[1])) # # print('投影座標 -> 圖上座標：') # coords = geo2imagexy(dataset, x, y) # print('(%s, %s)->(%s, %s)' % (x, y, coords[0], coords[1])) # print('圖上座標 -> 投影座標：') # coords = imagexy2geo(dataset, row, col) # print('(%s, %s)->(%s, %s)' % (row, col, coords[0], coords[1])) # print('投影座標 -> 經緯度：') # coords2 = geo2lonlat(dataset,coords[0], coords[1]) # print('(%s, %s)->(%s, %s)' % (coords[0], coords[1], coords2[0], coords2[1])) # coords = imagexy2lonlat(dataset, row, col) # print('影像畫素 -> 經緯度：') # print('(%s, %s)->(%s, %s)' % ( row, col, coords[0], coords[1])) # coords = imagexy2lonlat(dataset, dataset.RasterXSize, dataset.RasterYSize) # print('影像畫素 -> 經緯度：') # print('(%s, %s)->(%s, %s)' % ( dataset.RasterXSize, dataset.RasterYSize, coords[0], coords[1])) # # coords = lonlat2imagexy(dataset, 124.3288421630859, 46.391464001559044) # print('經緯度 -> 影像畫素 ：') # print('(%s, %s)->(%s, %s)' % ( 124.3288421630859, 46.391464001559044, coords[0], coords[1])) # coords = lonlat2imagexy(dataset, 124.44282531738276, 46.32796494040744) # print('經緯度 -> 影像畫素 ：') # print('(%s, %s)->(%s, %s)' % ( 124.44282531738276, 46.32796494040744, coords[0], coords[1])) #經緯度轉畫素 xoffset=0 yoffset=0 x,y = 125.059,46.894 xoffset,yoffset = lonlat2imagexy(dataset, x,y) print('座標轉換-對應行列畫素位置') print('(%s, %s)->(%s, %s)' % (x,y, xoffset,yoffset)) width=int(500 * MeterParam) height=int(500 * MeterParam) if xoffset - width <= 0 and yoffset - height <= 0 : print("左上角") xoffset = 0 yoffset = 0 elif xoffset - width <= 0 and yoffset - height > 0 : print("左邊") xoffset = 0 elif xoffset - width > 0 and yoffset - height <= 0 : print("頂邊") yoffset = 0 else : print("中間區域") xoffset = xoffset - width yoffset = yoffset - height width = width * 2 height = height * 2 print('切割範圍') print('寬高(%s, %s)->偏移起點(%s, %s)' % (width, height, xoffset,yoffset)) # xoffset,yoffset,width,height = 175360/2,123136/2,1000,1000 newData = np.zeros([width,height,3]) band = dataset.GetRasterBand(1) r=band.ReadAsArray(xoffset,yoffset,width,height) NoData = band.GetNoDataValue() newData[:,:,0] = r band = dataset.GetRasterBand(2) g=band.ReadAsArray(xoffset,yoffset,width,height) band = dataset.GetRasterBand(3) b=band.ReadAsArray(xoffset,yoffset,width,height) ticks = time.time() resultPath = "D:\\RS%s.jpg" % (int(ticks)) newData[:,:,0] = r newData[:,:,1] = g newData[:,:,2] = b format = "GTiff" driver = gdal.GetDriverByName(format) ds = driver.Create(resultPath, width, height, 3, gdal.GDT_Float32) geotransform1 = geotransform px = geotransform[0] + xoffset * geotransform[1] + yoffset * geotransform[2] py = geotransform[3] + xoffset * geotransform[4] + yoffset * geotransform[5] geotransform1 = (px, 0.29858214173896974, 0.0, py, 0.0, -0.29858214173896974) # print(geotransform1[0]) ds.SetGeoTransform(geotransform1) ds.SetProjection(projection) lay01= ds.GetRasterBand(1) lay02= ds.GetRasterBand(2) lay03= ds.GetRasterBand(3) # ds.GetRasterBand(1).SetNoDataValue(0) # ds.GetRasterBand(2).SetNoDataValue(0) # ds.GetRasterBand(3).SetNoDataValue(0) lay01.WriteArray(b) lay02.WriteArray(g) lay03.WriteArray(r) # ds.FlushCache() # ds = None del ds import cv2 import matplotlib.pyplot as plt img2=cv2.merge([r,g,b]) plt.imshow(img2) plt.xticks([]),plt.yticks([]) # 不顯示座標軸 plt.show() ticks = time.time() # cv2.imwrite("D:\\RS%s.jpg" % (int(ticks)) , img2) print("OK")