Python3+gdal 读取tiff格式数据

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：pip install -U numpy 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


    
    
     
     
      
      
       
       
      
      
      
      
       
       
        
        def readTif(fileName):
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
         merge_img = 
        
        0
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
           driver = gdal.GetDriverByName(
        
        ‘GTiff’)
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
          driver.Register()
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
            dataset = gdal.Open(fileName)
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
           
        
        if dataset == 
        
        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
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
         
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
          
        
        if im_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)
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        # 
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
           
        
        elif im_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])  
        
        #B G R
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
            
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
                cv2.imwrite(
        
        ‘C:/Users/summer/Desktop/merge_img1.jpg’, merge_img1)

4.图像裁剪：


    
    
     
     
      
      
       
       
      
      
      
      
       
       
        
        import cv2
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        import numpy 
        
        as np
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        import os
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        tiff_file = 
        
        './try_img/2.tiff'
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        save_folder = 
        
        './try_img_re/'
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        if 
        
        not os.path.exists(save_folder):
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
         os.makedirs(save_folder)
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        tif_img = cv2.imread(tiff_file)
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        width, height, channel = tif_img.shape
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        # print height, width, channel : 6908 7300 3
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        threshold = 
        
        1000
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        overlap = 
        
        100
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        step = threshold - overlap
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        x_num = width/step + 
        
        1
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        y_num = height/step + 
        
        1
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        print x_num, y_num
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        N = 
        
        0
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        yj = 
        
        0 
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
        for xi 
        
        in range(x_num):
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
        
        for yj 
        
        in range(y_num):
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
        
        # print xi
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
               
        
        if yj <= y_num:
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
                   
        
        print yj
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
                  x = step*xi
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
                 y = step*yj
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
                    wi = min(width,x+threshold)
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
                 hi = min(height,y+threshold)
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
                   
        
        # print wi , hi
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
                 
        
        if wi-x < 
        
        1000 
        
        and hi-y < 
        
        1000:
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
                     im_block = tif_img[wi
        
        -1000:wi, hi
        
        -1000:hi]
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
                  
        
        elif wi-x > 
        
        1000 
        
        and hi-y < 
        
        1000:
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
       
        
                       im_block = tif_img[x:wi, hi
        
        -1000:hi]
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
        
       
       
      
      
     
     
      
      
       
       
      
      
      
      
       
                 
        
        elif wi-x < 
        
        1000 
        
        and hi-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

https://blog.csdn.net/summermaoz/article/details/78346929