遥感语义分割数据集中的切图策略

遥感语义分割数据集中的切图策略

# 切图脚本
import argparse
import glob
import math
import os
import os.path as osp
import tempfile
import zipfile

import mmcv
import numpy as np
from mmengine.utils import ProgressBar, mkdir_or_exist

def clip_big_image(image_path, clip_save_dir, to_label=False):
    # Original image of Vaihingen dataset is very large, thus pre-processing
    # of them is adopted. Given fixed clip size and stride size to generate
    # clipped image, the intersection　of width and height is determined.
    # For example, given one 5120 x 5120 original image, the clip size is
    # 512 and stride size is 256, thus it would generate 20x20 = 400 images
    # whose size are all 512x512.
    image = mmcv.imread(image_path)

    h, w, c = image.shape
    cs = 512 # todo 分割的大小
    ss = 256 # todo 分割的步长

    num_rows = math.ceil((h - cs) / ss) if math.ceil(
        (h - cs) / ss) * ss + cs >=