利用Python裁切tiff图像且读取tiff,shp文件的实例
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2020-09-17
18:03:16
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利用利用Python裁切裁切tiff图像且读取图像且读取tiff,shp文件的实例文件的实例
主要介绍了利用Python裁切tiff图像且读取tiff,shp文件的实例，具有很好的参考价值，希望对大家有所帮助。一
起跟随小编过来看看吧
我就废话不多说了，还是直接看代码吧！
from osgeo import gdal, gdalnumeric, ogr
from PIL import Image, ImageDraw
from osgeo import gdal_array
import os
import operator
from functools import reduce
gdal.UseExceptions()
def readTif(fileName):
dataset = gdal.Open(fileName)
if dataset == None:
print(fileName+"文件无法打开")
return
im_width = dataset.RasterXSize #栅格矩阵的列数
im_height = dataset.RasterYSize #栅格矩阵的行数
im_bands = dataset.RasterCount #波段数
band1=dataset.GetRasterBand(1)
print(band1)
print ('Band Type=',gdal.GetDataTypeName(band1.DataType))
im_data = dataset.ReadAsArray(0,0,im_width,im_height)#获取数据
im_geotrans = dataset.GetGeoTransform()#获取仿射矩阵信息
im_proj = dataset.GetProjection()#获取投影信息
im_blueBand = im_data[0,0:im_height,0:im_width]#获取蓝波段
im_greenBand = im_data[1,0:im_height,0:im_width]#获取绿波段
im_redBand = im_data[2,0:im_height,0:im_width]#获取红波段
im_nirBand = im_data[3,0:im_height,0:im_width]#获取近红外波段
return(im_width,im_height,im_bands,im_data,im_geotrans
,im_proj,im_blueBand,im_greenBand,im_redBand,im_nirBand)
#保存tif文件函数
import gdal
import numpy as np
def writeTiff(im_data,im_width,im_height,im_bands,im_geotrans,im_proj,path):
if 'int8' in im_data.dtype.name:
datatype = gdal.GDT_Byte
elif 'int16' in im_data.dtype.name:
datatype = gdal.GDT_UInt16
else:
datatype = gdal.GDT_Float32
if len(im_data.shape) == 3:
im_bands, im_height, im_width = im_data.shape
elif len(im_data.shape) == 2:
im_data = np.array([im_data])
else:
im_bands, (im_height, im_width) = 1,im_data.shape
#创建文件
driver = gdal.GetDriverByName("GTiff")
dataset = driver.Create(path, im_width, im_height, im_bands, datatype)
if(dataset!= None):
dataset.SetGeoTransform(im_geotrans) #写入仿射变换参数
dataset.SetProjection(im_proj) #写入投影
for i in range(im_bands):
dataset.GetRasterBand(i+1).WriteArray(im_data[i])
del dataset
# This function will convert the rasterized clipper shapefile
# to a mask for use within GDAL.
def imageToArray(i):
"""
Converts a Python Imaging Library array to a
gdalnumeric image.
"""
a=gdalnumeric.fromstring(i.tobytes(),'b')
a.shape=i.im.size[1], i.im.size[0]
return a
def arrayToImage(a):
"""
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