对Python3+gdal 读取tiff格式数据的实例讲解
1、遇到的问题：numpy版本
im_data=dataset.ReadAsArray(0,0,im_width,im_height)#获取数据这句报错
升级numpy：pipinstall-Unumpy但是提示已经是最新版本
解决：卸载numpy重新安装
2.直接从压缩包中读取tiff图像
参考：http://gdal.org/gdal_virtual_file_systems.html#gdal_virtual_file_systems_vsizip
当前情况是2层压缩：/'/vsitar/C:/Users/summer/Desktop/a_PAN1.tiff'
3.读tiff
defreadTif(fileName):
merge_img=0
driver=gdal.GetDriverByName('GTiff')
driver.Register()
dataset=gdal.Open(fileName)
ifdataset==None:
print(fileName+"掩膜失败，文件无法打开")
return
im_width=dataset.RasterXSize#栅格矩阵的列数
print('im_width:',im_width)
im_height=dataset.RasterYSize#栅格矩阵的行数
print('im_height:',im_height)
im_bands=dataset.RasterCount#波段数
im_geotrans=dataset.GetGeoTransform()#获取仿射矩阵信息
im_proj=dataset.GetProjection()#获取投影信息
ifim_bands==1:
band=dataset.GetRasterBand(1)
im_data=dataset.ReadAsArray(0,0,im_width,im_height)#获取数据
cdata=im_data.astype(np.uint8)
merge_img=cv2.merge([cdata,cdata,cdata])
cv2.imwrite('C:/Users/summer/Desktop/a.jpg',merge_img)
#
elifim_bands==4:
# #im_data=dataset.ReadAsArray(0,0,im_width,im_height)#获取数据
# #im_blueBand=im_data[0,0:im_width,0:im_height]#获取蓝波段
# #im_greenBand=im_data[1,0:im_width,0:im_height]#获取绿波段
# #im_redBand=im_data[2,0:im_width,0:im_height]#获取红波段
# ##im_nirBand=im_data[3,0:im_width,0:im_height]#获取近红外波段
# #merge_img=cv2.merge([im_redBand,im_greenBand,im_blueBand])
# #zeros=np.zeros([im_height,im_width],dtype="uint8")
# #data1=im_redBand.ReadAsArray
# band1=dataset.GetRasterBand(1)
# band2=dataset.GetRasterBand(2)
# band3=dataset.GetRasterBand(3)
# band4=dataset.GetRasterBand(4)
data1=band1.ReadAsArray(0,0,im_width,im_height).astype(np.uint16)#r#获取数据
data2=band2.ReadAsArray(0,0,im_width,im_height).astype(np.uint16)#g#获取数据
data3=band3.ReadAsArray(0,0,im_width,im_height).astype(np.uint16)#b#获取数据
data4=band4.ReadAsArray(0,0,im_width,im_height).astype(np.uint16)#R#获取数据
# print(data1[1][45])
# output1=cv2.convertScaleAbs(data1,alpha=(255.0/65535.0))
# print(output1[1][45])
# output2=cv2.convertScaleAbs(data2,alpha=(255.0/65535.0))
# output3=cv2.convertScaleAbs(data3,alpha=(255.0/65535.0))
merge_img1=cv2.merge([output3,output2,output1])#BGR
cv2.imwrite('C:/Users/summer/Desktop/merge_img1.jpg',merge_img1)
4.图像裁剪：
importcv2 importnumpyasnp importos tiff_file='./try_img/2.tiff' save_folder='./try_img_re/' ifnotos.path.exists(save_folder): os.makedirs(save_folder) tif_img=cv2.imread(tiff_file) width,height,channel=tif_img.shape #printheight,width,channel:690873003 threshold=1000 overlap=100 step=threshold-overlap x_num=width/step+1 y_num=height/step+1 printx_num,y_num N=0 yj=0 forxiinrange(x_num): foryjinrange(y_num): #printxi ifyj<=y_num: printyj x=step*xi y=step*yj wi=min(width,x+threshold) hi=min(height,y+threshold) #printwi,hi ifwi-x<1000andhi-y<1000: im_block=tif_img[wi-1000:wi,hi-1000:hi] elifwi-x>1000andhi-y<1000: im_block=tif_img[x:wi,hi-1000:hi] elifwi-x<1000andhi-y>1000: im_block=tif_img[wi-1000:wi,y:hi] else: im_block=tif_img[x:wi,y:hi] cv2.imwrite(save_folder+'try'+str(N)+'.jpg',im_block) N+=1
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