Python 将tif文件分割成多个小tif
个人整理的python地理信息库,本文代码也在其中，欢迎使用: https://github.com/Adam0429/geo-py
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投简历戳这里，英视睿达欢迎您！
原始图像是这样的
目标是剪裁出指定大小的若干小tif
代码很简单，直接放了
from tqdm import tqdm
from osgeo import gdal,ogr,osr
import numpy as np
from glob import glob
def read_tif(tif_path):
ds = gdal.Open(tiff_path)
row = ds.RasterXSize
col = ds.RasterYSize
band = ds.RasterCount
for i in range(band):
data = ds.GetRasterBand(i+1).ReadAsArray()
data = np.expand_dims(data , 2)
if i == 0:
allarrays = data
else:
allarrays = np.concatenate((allarrays, data), axis=2)
return {'data':allarrays,'transform':ds.GetGeoTransform(),'projection':ds.GetProjection(),'bands':band,'width':row,'height':col}
# 左上角点坐标 GeoTransform[0],GeoTransform[3] Transform[1] is the pixel width, and Transform[5] is the pixel height
def write_tif(fn_out, im_data, transform,proj=None):
'''
功能:
----------
将矩阵按某种投影写入tif，需指定仿射变换矩阵，可选渲染为rgba
参数:
----------
fn_out:str
输出tif图的绝对文件路径
im_data: np.array
tif图对应的矩阵
transform: list/tuple
gdal-like仿射变换矩阵，若im_data矩阵起始点为左上角且投影为4326，则为
(lon_x.min(), delta_x, 0,
lat_y.max(), 0, delta_y)
proj: str（wkt格式）
投影，默认投影坐标为4326，可用osr包将epsg转化为wkt格式，如
srs = osr.SpatialReference()# establish encoding
srs.ImportFromEPSG(4326) # WGS84 lat/lon
proj = srs.ExportToWkt() # create wkt fromat of proj
# 设置投影，proj为wkt format
if proj is None:
proj = 'GEOGCS["WGS 84",\
DATUM["WGS_1984",\
SPHEROID["WGS 84",6378137,298.257223563, \
AUTHORITY["EPSG","7030"]], \
AUTHORITY["EPSG","6326"]], \
PRIMEM["Greenwich",0, \
AUTHORITY["EPSG","8901"]], \
UNIT["degree",0.0174532925199433, \
AUTHORITY["EPSG","9122"]],\
AUTHORITY["EPSG","4326"]]'
# 渲染为rgba矩阵
# 设置数据类型
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
# 将(通道数、高、宽)顺序调整为(高、宽、通道数)
# print('shape of im data:', im_data.shape)
im_bands = min(im_data.shape)
im_shape = list(im_data.shape)
im_shape.remove(im_bands)
im_height, im_width = im_shape
band_idx = im_data.shape.index(im_bands)
# 找出波段是在第几个
# 创建文件
driver = gdal.GetDriverByName("GTiff")
dataset = driver.Create(fn_out, im_width, im_height, im_bands, datatype)
# if dataset is not None:
dataset.SetGeoTransform(transform) # 写入仿射变换参数
dataset.SetProjection(proj) # 写入投影
if im_bands == 1:
# print(im_data[:, 0,:].shape)
if band_idx == 0:
dataset.GetRasterBand(1).WriteArray(im_data[0, :, :])
elif band_idx == 1:
dataset.GetRasterBand(1).WriteArray(im_data[:, 0, :])
elif band_idx == 2:
dataset.GetRasterBand(1).WriteArray(im_data[:, :, 0])
else:
for i in range(im_bands):
if band_idx == 0:
dataset.GetRasterBand(i + 1).WriteArray(im_data[i, :, :])
elif band_idx == 1:
dataset.GetRasterBand(i + 1).WriteArray(im_data[:, i, :])
elif band_idx == 2:
dataset.GetRasterBand(i + 1).WriteArray(im_data[:, :, i])
dataset.FlushCache()
del dataset
driver = None
def split(origin_data,origin_transform,output_size):
origin_size = origin_data.shape
x = origin_transform[0]
y = origin_transform[3]
x_step = origin_transform[1]
y_step = origin_transform[5]
output_x_step = x_step
output_y_step = y_step
for i in range(origin_size[0]//output_size[0]):
for j in range(origin_size[1]//output_size[1]):
output_data = origin_data[i*output_size[0]:(i+1)*output_size[0],j*output_size[1]:(j+1)*output_size[1],:]
output_transform = (x+j*output_x_step*output_size[0],output_x_step,0,y+i*output_y_step*output_size[0],0,output_y_step)
write_tif(f'test/{i}_{j}.tif', output_data, output_transform)
data = read_tif('/Users/0_20210508GF2.tif')
split(origin_data=data['data'],origin_transform=data['transform'],output_size=(255,255))
放下最终效果，中心部分就是截取出的小tif，覆盖在原tif之上会有色差，这是因为软件对不同tif文件显示不同色域的原因。