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：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：

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

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