[Python知识库][自用代码]ENVI输出的Sentinel-1图像预处理(翻转，滑动窗口裁剪)

import cv2
import os
from osgeo import gdal 
import numpy as np

def tif_jpg(rasterfile):
    in_ds = gdal.Open(rasterfile)  # 打开样本文件
    xsize = in_ds.RasterXSize  # 获取行列数
    ysize = in_ds.RasterYSize
    block_data = in_ds.ReadAsArray(0, 0, xsize, ysize).astype(np.float32)
    B = block_data[:, :]
    data2 = cv2.merge([B]).astype(np.int16)
    return data2

将envi输出的tif文件翻转并保存为jpg图像

path = './tif_folder'
nameList = os.listdir(path)
for i in nameList:
    new_path = os.path.join(path,i)
    img = tif_jpg(new_path)
    img1 = cv2.flip(img,1)
    new_name = new_path.split('\\')[-1].split('.')[0]+'.jpg'
    cv2.imwrite(new_name,img1)
    print(new_name,'----done')

0315VH.jpg
0327VH.jpg

利用滑动窗口裁剪大尺寸图片

def create_folder(path):
    if not os.path.exists(path):
        os.mkdir(path)

def slid_win(imgpp, out_folder, win = 256, step_num = 5):
    create_folder(out_folder)
    height, width, _ = img.shape
    step = win//step_num
    y, x = 0,0
    count = 0
    while y+win <= height:
        while x+win <= width:
            x += step
            count+=1
            new_img = imgpp[y:y+win,x:x+win]
            new_name = str(count).zfill(5)+'.jpg'
            new_path = os.path.join(out_folder,new_name)
            cv2.imwrite(new_path,new_img)
        y += step
    print('left:',height-y,width-x,'total:',count)

path = './jpg_folder'
nameList = os.listdir(path)
for i in range(len(nameList)):
    img_path = os.path.join(path,nameList[i])
    img = cv2.imread(img_path)
    # print('img'+str(i))
    new_folder = 'img'+str(i)
    slid_win(img, win = 256, step_num = 5, out_folder=new_folder)

left: 253 236 total: 499
left: 253 236 total: 499