587 lines
20 KiB
Python
587 lines
20 KiB
Python
"""
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2025.09.16 切片增加后缀 _image.png _image.tiff
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2025.09.22 增加港口切片要求
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"""
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from osgeo import ogr, gdal
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import os
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import argparse
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import numpy as np
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from PIL import Image
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import math
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from pathlib import Path
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portsliceSize=5000
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shipsliceSize=1024
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BlockOverLayer=0.25
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def existOrCreate(dirpath):
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if not os.path.exists(dirpath):
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os.makedirs(dirpath)
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def get_filename_without_ext(path):
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base_name = os.path.basename(path)
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if '.' not in base_name or base_name.startswith('.'):
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return base_name
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return base_name.rsplit('.', 1)[0]
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def read_tif(path):
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dataset = gdal.Open(path) # 打开TIF文件
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if dataset is None:
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print("无法打开文件")
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return None, None, None
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cols = dataset.RasterXSize # 图像宽度
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rows = dataset.RasterYSize # 图像高度
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bands = dataset.RasterCount
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im_proj = dataset.GetProjection() # 获取投影信息
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im_Geotrans = dataset.GetGeoTransform() # 获取仿射变换信息
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im_data = dataset.ReadAsArray(0, 0, cols, rows) # 读取栅格数据为NumPy数组
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print("行数：", rows)
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print("列数：", cols)
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print("波段：", bands)
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del dataset # 关闭数据集
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return im_proj, im_Geotrans, im_data
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def write_envi(im_data, im_geotrans, im_proj, output_path):
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"""
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将数组数据写入ENVI格式文件
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:param im_data: 输入的numpy数组（2D或3D）
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:param im_geotrans: 仿射变换参数（6元组）
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:param im_proj: 投影信息（WKT字符串）
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:param output_path: 输出文件路径（无需扩展名，会自动生成.dat和.hdr）
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"""
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im_bands = 1
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im_height, im_width = im_data.shape
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# 创建ENVI格式驱动
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driver = gdal.GetDriverByName("GTiff")
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dataset = driver.Create(output_path, im_width, im_height, 1, gdal.GDT_Byte)
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if dataset is not None:
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dataset.SetGeoTransform(im_geotrans) # 设置地理变换参数
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dataset.SetProjection(im_proj) # 设置投影
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dataset.GetRasterBand(1).WriteArray(im_data)
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dataset.FlushCache() # 确保数据写入磁盘
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dataset = None # 关闭文件
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def write_tiff(im_data, im_geotrans, im_proj, output_path):
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"""
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将数组数据写入ENVI格式文件
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:param im_data: 输入的numpy数组（2D或3D）
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:param im_geotrans: 仿射变换参数（6元组）
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:param im_proj: 投影信息（WKT字符串）
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:param output_path: 输出文件路径（无需扩展名，会自动生成.dat和.hdr）
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"""
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im_bands = 1
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im_height, im_width = im_data.shape
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# 创建ENVI格式驱动
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driver = gdal.GetDriverByName("GTiff")
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dataset = driver.Create(output_path, im_width, im_height, 1, gdal.GDT_Float32)
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if dataset is not None:
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dataset.SetGeoTransform(im_geotrans) # 设置地理变换参数
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dataset.SetProjection(im_proj) # 设置投影
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dataset.GetRasterBand(1).WriteArray(im_data)
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dataset.FlushCache() # 确保数据写入磁盘
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dataset = None # 关闭文件
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def Strech_linear(im_data):
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im_data_dB=10*np.log10(im_data)
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immask=np.isfinite(im_data_dB)
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infmask = np.isinf(im_data_dB)
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imvail_data=im_data[immask]
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im_data_dB=0
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minvalue=np.nanmin(imvail_data)
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maxvalue=np.nanmax(imvail_data)
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infmask = np.isinf(im_data_dB)
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im_data[infmask] = minvalue-100
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im_data = (im_data - minvalue) / (maxvalue - minvalue) * 254+1
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im_data=np.clip(im_data,0,255)
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return im_data.astype(np.uint8)
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def Strech_linear1(im_data):
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im_data_dB = 10 * np.log10(im_data)
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immask = np.isfinite(im_data_dB)
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infmask = np.isinf(im_data_dB)
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imvail_data = im_data[immask]
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im_data_dB=0
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minvalue=np.percentile(imvail_data,1)
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maxvalue = np.percentile(imvail_data, 99)
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im_data[infmask] = minvalue - 100
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im_data = (im_data - minvalue) / (maxvalue - minvalue) * 254 + 1
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im_data = np.clip(im_data, 0, 255)
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return im_data.astype(np.uint8)
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def Strech_linear2(im_data):
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im_data_dB = 10 * np.log10(im_data)
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immask = np.isfinite(im_data_dB)
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infmask = np.isinf(im_data_dB)
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imvail_data = im_data[immask]
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im_data_dB = 0
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minvalue = np.percentile(imvail_data, 2)
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maxvalue = np.percentile(imvail_data, 98)
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im_data[infmask] = minvalue - 100
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im_data = (im_data - minvalue) / (maxvalue - minvalue) * 254 + 1
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im_data = np.clip(im_data, 0, 255)
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return im_data.astype(np.uint8)
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def Strech_linear5(im_data):
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im_data_dB = 10 * np.log10(im_data)
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immask = np.isfinite(im_data_dB)
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infmask = np.isinf(im_data_dB)
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imvail_data = im_data[immask]
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im_data_dB = 0
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minvalue = np.percentile(imvail_data, 5)
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maxvalue = np.percentile(imvail_data, 95)
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im_data[infmask] = minvalue - 100
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im_data = (im_data - minvalue) / (maxvalue - minvalue) * 254 + 1
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im_data = np.clip(im_data, 0, 255)
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return im_data.astype(np.uint8)
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def Strech_SquareRoot(im_data):
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# 判断是否为dB
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# immask = np.isfinite(im_data)
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# imvail_data = im_data[immask]
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# minvalue = np.percentile(imvail_data,30)
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# if minvalue<0 :
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# im_data=np.power(10.0,im_data/10.0)
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im_data=np.sqrt(im_data)
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immask = np.isfinite(im_data)
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imvail_data = im_data[immask]
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minvalue=np.nanmin(imvail_data)
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maxvalue=np.nanmax(imvail_data)
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minvalue_01Prec = np.percentile(imvail_data, 2) # 20250904 1%拉伸
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maxvalue_999Prec = np.percentile(imvail_data, 98)
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print('sqrt root min - max ', minvalue,maxvalue)
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if (maxvalue-minvalue)/(maxvalue_999Prec-minvalue_01Prec)>3: # 表示 拉伸之后，像素值绝大部分很有可能集中在 80
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minvalue=minvalue_01Prec
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maxvalue=maxvalue_999Prec
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print('sqrt root min(0.1) - max(99.9) ', minvalue, maxvalue)
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im_data = (im_data - minvalue) / (maxvalue - minvalue) * 254 + 1
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im_data = np.clip(im_data, 0, 255)
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return im_data.astype(np.uint8)
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def DataStrech(im_data,strechmethod):
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# [,"Linear1","Linear2","Linear5","SquareRoot"]
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if strechmethod == "Linear" :
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return Strech_linear(im_data)
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elif strechmethod == "Linear1":
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return Strech_linear1(im_data)
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elif strechmethod == "Linear2":
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return Strech_linear2(im_data)
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elif strechmethod == "Linear5":
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return Strech_linear5(im_data)
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elif strechmethod == "SquareRoot":
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return Strech_SquareRoot(im_data)
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else:
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return im_data.astype(np.uint8)
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# 文件模式
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def stretchProcess(infilepath,outfilepath,strechmethod):
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im_proj, im_Geotrans, im_data=read_tif(infilepath)
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envifilepath=get_filename_without_ext(outfilepath)+".bin"
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envifilepath=os.path.join(os.path.dirname(outfilepath),envifilepath)
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im_data = DataStrech(im_data,strechmethod)
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im_data = im_data.astype(np.uint8)
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write_envi(im_data,im_Geotrans,im_proj,envifilepath)
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Image.fromarray(im_data).save(outfilepath,compress_level=0)
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print("图像拉伸处理结束")
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def getsliceGeotrans(GeoTransform,Xpixel,Ypixel):
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XGeo = GeoTransform[0]+GeoTransform[1]*Xpixel+GeoTransform[2]*Ypixel
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YGeo = GeoTransform[3]+GeoTransform[4]*Xpixel+GeoTransform[5]*Ypixel
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result=[
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XGeo,GeoTransform[1],GeoTransform[2],
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YGeo,GeoTransform[4],GeoTransform[5]
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]
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return result
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def is_all_same(lst):
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arr = np.array(lst)
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# arr_num=arr.size
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sum_data=np.sum(arr != arr[0])
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return sum_data<400
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def getNextSliceNumber(n,sliceSize,overlap=0.25):
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step=int(sliceSize*(1-overlap))+1
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ti = list(range(0, n, step))
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newN= n if ti[-1]+1024 < n else ti[-1]+1024
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# 评价重叠率
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movelayer=[]
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for i in range(len(ti)-1):
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movelayer.append((ti[i] + 1024 - ti[i + 1]) / 1024 * 100.0)
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print("重叠率：",movelayer)
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return newN,ti
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def sliceShipDataset(rootname,im_data,src_im_data, im_Geotrans, im_proj, outfolder):
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binfolder=os.path.join(outfolder,"舰船","unit8binfolder")
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pngfolder=os.path.join(outfolder,"舰船","pngfolder")
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tifffolder=os.path.join(outfolder,"舰船","tifffolder")
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h,w=im_data.shape
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nextH,ht=getNextSliceNumber(h,shipsliceSize,BlockOverLayer)
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nextW,wt=getNextSliceNumber(w,shipsliceSize,BlockOverLayer)
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padH=nextH-h
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padW=nextW-w
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im_data=np.pad(im_data,((0,padH),(0,padW)),mode='constant',constant_values=0)
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src_im_data=np.pad(src_im_data,((0,padH),(0,padW)),mode='constant',constant_values=0)
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slice_ID=0
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for hi in ht:
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for wi in wt:
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geotrans_temp=getsliceGeotrans(im_Geotrans,wi,hi)
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im_data_temp=im_data[hi:hi+shipsliceSize,wi:wi+shipsliceSize]
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src_im_data_temp=src_im_data[hi:hi+shipsliceSize,wi:wi+shipsliceSize]
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slice_ID = slice_ID + 1
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if not is_all_same(im_data_temp):
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sliceBinPath=os.path.join(binfolder, rootname+"_"+str(slice_ID).zfill(4)+"_image.tiff")
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slicepngPath=os.path.join(pngfolder, rootname+"_"+str(slice_ID).zfill(4)+"_image.png")
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slicesrctiffPath=os.path.join(tifffolder, rootname+"_"+str(slice_ID).zfill(4)+"_image.tiff")
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write_tiff(src_im_data_temp, geotrans_temp, im_proj, slicesrctiffPath)
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write_envi(im_data_temp,geotrans_temp,im_proj,sliceBinPath)
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Image.fromarray(im_data_temp).save(slicepngPath,compress_level=0)
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print("图像切片结束")
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return slice_ID
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def ishasPort(im_Geotrans,im_data,MLCPoints,JLCPoints,MJLCPoints):
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LCpoints=MLCPoints+JLCPoints+MJLCPoints
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# 获取范围
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rows=im_data.shape[0]
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cols=im_data.shape[1]
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x1=im_Geotrans[0]+im_Geotrans[1]*0
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x2=im_Geotrans[0]+im_Geotrans[1]*cols
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y1=im_Geotrans[3]+im_Geotrans[5]*0
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y2=im_Geotrans[3]+im_Geotrans[5]*rows
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xmin=min(x1,x2)
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xmax=max(x1,x2)
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ymin=min(y1,y2)
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ymax=max(y1,y2)
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# 数据处理
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for p in LCpoints:
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x_in_range = (p[0] >= xmin) & (p[0]<= xmax)
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y_in_range = (p[1] >= ymin) & (p[1] <= ymax)
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within_rect_indices_mask = x_in_range & y_in_range
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if within_rect_indices_mask:
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return True
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return False
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def slicePortDataset(rootname,im_data,src_im_data, im_Geotrans, im_proj, outfolder,slice_ID,portfilestr):
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# 读取portfilestr 中文件
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MLCPoints=[]
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JLCPoints=[]
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MJLCPoints=[]
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portfilelines=[]
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with open(portfilestr,"r",encoding="utf-8") as portfile:
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portfilelines=portfile.readlines()
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for line in portfilelines:
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if(len(line)>3):
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linemetas=line.split("\t\t")
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clsname=linemetas[0]
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pointstr=linemetas[1]
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pointx=float(pointstr.split(",")[0]) # PX
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pointy=float(pointstr.split(",")[1]) # Py
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if clsname=="JLC":
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JLCPoints.append([pointx,pointy])
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elif clsname=="MJLC":
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MJLCPoints.append([pointx,pointy])
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elif clsname=="MLC":
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MLCPoints.append([pointx,pointy])
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# 处理文件脚本
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if len(MLCPoints)==0 and len(JLCPoints)==0 and len(MJLCPoints)==0:
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return
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else:
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pass
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# 切片主流程
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binfolder=os.path.join(outfolder,"港口","unit8binfolder")
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pngfolder=os.path.join(outfolder,"港口","pngfolder")
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tifffolder=os.path.join(outfolder,"港口","tifffolder")
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for P in JLCPoints:
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Px=P[0]
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Py=P[1]
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Sx=P[0]-portsliceSize/2
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Sy=P[1]-portsliceSize/2
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wi=Sx if Sx>0 else 0
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hi=Sy if Sy>0 else 0
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slice_ID = slice_ID + 1
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im_data_temp = im_data[hi:hi + portsliceSize, wi:wi + portsliceSize]
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src_im_data_temp = src_im_data[hi:hi + portsliceSize, wi:wi + portsliceSize]
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sliceBinPath = os.path.join(binfolder, rootname + "_" + str(slice_ID).zfill(4) + "_image.tiff")
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slicepngPath = os.path.join(pngfolder, rootname + "_" + str(slice_ID).zfill(4) + "_image.png")
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slicesrctiffPath = os.path.join(tifffolder, rootname + "_" + str(slice_ID).zfill(4) + "_image.tiff")
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geotrans_temp = getsliceGeotrans(im_Geotrans, wi, hi)
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write_tiff(src_im_data_temp, geotrans_temp, im_proj, slicesrctiffPath)
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write_envi(im_data_temp, geotrans_temp, im_proj, sliceBinPath)
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Image.fromarray(im_data_temp).save(slicepngPath, compress_level=4)
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for P in MJLCPoints:
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Px = P[0]
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Py = P[1]
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Sx = P[0] - portsliceSize / 2
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Sy = P[1] - portsliceSize / 2
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wi = Sx if Sx > 0 else 0
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hi = Sy if Sy > 0 else 0
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slice_ID = slice_ID + 1
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im_data_temp = im_data[hi:hi + portsliceSize, wi:wi + portsliceSize]
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src_im_data_temp = src_im_data[hi:hi + portsliceSize, wi:wi + portsliceSize]
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sliceBinPath = os.path.join(binfolder, rootname + "_" + str(slice_ID).zfill(4) + "_image.tiff")
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slicepngPath = os.path.join(pngfolder, rootname + "_" + str(slice_ID).zfill(4) + "_image.png")
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slicesrctiffPath = os.path.join(tifffolder, rootname + "_" + str(slice_ID).zfill(4) + "_image.tiff")
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geotrans_temp = getsliceGeotrans(im_Geotrans, wi, hi)
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write_tiff(src_im_data_temp, geotrans_temp, im_proj, slicesrctiffPath)
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write_envi(im_data_temp, geotrans_temp, im_proj, sliceBinPath)
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Image.fromarray(im_data_temp).save(slicepngPath, compress_level=4)
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for P in MLCPoints:
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Px = P[0]
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Py = P[1]
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Sx = P[0] - portsliceSize / 2
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Sy = P[1] - portsliceSize / 2
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wi = Sx if Sx > 0 else 0
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hi = Sy if Sy > 0 else 0
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slice_ID = slice_ID + 1
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im_data_temp = im_data[hi:hi + portsliceSize, wi:wi + portsliceSize]
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src_im_data_temp = src_im_data[hi:hi + portsliceSize, wi:wi + portsliceSize]
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sliceBinPath = os.path.join(binfolder, rootname + "_" + str(slice_ID).zfill(4) + "_image.tiff")
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slicepngPath = os.path.join(pngfolder, rootname + "_" + str(slice_ID).zfill(4) + "_image.png")
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slicesrctiffPath = os.path.join(tifffolder, rootname + "_" + str(slice_ID).zfill(4) + "_image.tiff")
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geotrans_temp = getsliceGeotrans(im_Geotrans, wi, hi)
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write_tiff(src_im_data_temp, geotrans_temp, im_proj, slicesrctiffPath)
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write_envi(im_data_temp, geotrans_temp, im_proj, sliceBinPath)
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Image.fromarray(im_data_temp).save(slicepngPath, compress_level=4)
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print("图像切片结束")
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return slice_ID
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def sliceLabelPortDataset(rootname,im_data,src_im_data, im_Geotrans, im_proj, outfolder,slice_ID,portfilestr):
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# 读取portfilestr 中文件
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MLCPoints=[]
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JLCPoints=[]
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MJLCPoints=[]
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with open(portfilestr,"r",encoding="utf-8") as portfile:
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for line in portfile.readlines():
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if(len(line)>3):
|
||
linemetas=line.split("\t\t")
|
||
clsname=linemetas[0]
|
||
pointstr=linemetas[1]
|
||
pointx=float(pointstr.split(",")[0])
|
||
pointy=float(pointstr.split(",")[1])
|
||
if clsname=="JLC":
|
||
JLCPoints.append([pointx,pointy])
|
||
elif clsname=="MJLC":
|
||
MJLCPoints.append([pointx,pointy])
|
||
elif clsname=="MLC":
|
||
MLCPoints.append([pointx,pointy])
|
||
# 处理文件脚本
|
||
if len(MLCPoints)==0 and len(JLCPoints)==0 and len(MJLCPoints)==0:
|
||
return
|
||
else:
|
||
pass
|
||
# 切片主流程
|
||
portuint8Tifffolder=os.path.join(outfolder,"港口","unit8tiff")
|
||
portlabelfolder=os.path.join(outfolder,"港口","MLCLabels")
|
||
unit8tiffPath=os.path.join(portuint8Tifffolder,"{}_uint8.tiff".format(rootname))
|
||
uint8labelPath=os.path.join(portlabelfolder,"{}_uint8.csv".format(rootname))
|
||
write_envi(im_data,im_Geotrans,im_proj,unit8tiffPath)
|
||
with open(portfilestr,"r",encoding="utf-8") as portfile:
|
||
with open(uint8labelPath, "w", encoding="utf-8") as labelfile:
|
||
for line in portfile.readlines():
|
||
if (len(line) > 3):
|
||
linemetas = line.split("\t\t")
|
||
clsname = linemetas[0]
|
||
pointstr = linemetas[1]
|
||
pointx = float(pointstr.split(",")[0])
|
||
pointy = float(pointstr.split(",")[1])
|
||
labelfile.write("{},{},{}\n".format(pointx,pointy,clsname))
|
||
|
||
return None
|
||
|
||
|
||
|
||
|
||
def stretchSliceProcess(infilepath, outfolder,portfilestr, strechmethod):
|
||
shipbinfolder=os.path.join(outfolder,"舰船","unit8binfolder")
|
||
shippngfolder=os.path.join(outfolder,"舰船","pngfolder")
|
||
shiptifffolder=os.path.join(outfolder,"舰船","tifffolder")
|
||
allpngfolder = os.path.join(outfolder, "allpngfolder")
|
||
|
||
portbinfolder=os.path.join(outfolder,"港口","unit8binfolder")
|
||
portpngfolder=os.path.join(outfolder,"港口","pngfolder")
|
||
porttifffolder=os.path.join(outfolder,"港口","tifffolder")
|
||
|
||
portuint8Tifffolder=os.path.join(outfolder,"港口","unit8tiff")
|
||
portlabelfolder=os.path.join(outfolder,"港口","PortLabels")
|
||
|
||
existOrCreate(shipbinfolder)
|
||
existOrCreate(shippngfolder)
|
||
existOrCreate(shiptifffolder)
|
||
existOrCreate(allpngfolder)
|
||
existOrCreate(portbinfolder)
|
||
existOrCreate(portpngfolder)
|
||
existOrCreate(porttifffolder)
|
||
existOrCreate(portuint8Tifffolder)
|
||
existOrCreate(portlabelfolder)
|
||
|
||
|
||
im_proj, im_Geotrans, im_data=read_tif(infilepath)
|
||
src_im_data=im_data*1.0
|
||
im_data = DataStrech(im_data,strechmethod) # 拉伸
|
||
im_data = im_data.astype(np.uint8)
|
||
rootname=Path(infilepath).stem
|
||
allImagePath=os.path.join(allpngfolder, rootname+"_all.png")
|
||
Image.fromarray(im_data).save(allImagePath,compress_level=0)
|
||
slice_ID=0
|
||
slice_ID=sliceShipDataset(rootname,im_data, src_im_data,im_Geotrans, im_proj, outfolder) # 舰船切片
|
||
slice_ID=slice_ID+1
|
||
slice_ID=slicePortDataset(rootname,im_data, src_im_data,im_Geotrans, im_proj, outfolder,slice_ID,portfilestr)
|
||
# slice_ID=sliceLabelPortDataset(rootname,im_data, src_im_data,im_Geotrans, im_proj, outfolder,slice_ID,portfilestr) # 港口拉伸
|
||
print("图像切片与拉伸完成")
|
||
pass
|
||
|
||
|
||
def getParams():
|
||
parser = argparse.ArgumentParser()
|
||
parser.add_argument('-i','--infile',type=str,default=r"F:\天仪SAR卫星数据集\舰船数据\bc2-sp-org-vv-20250205t032055-021998-000036-0055ee-01.tiff", help='输入shapefile文件')
|
||
parser.add_argument('-p', '--portfile',type=str,default=r"F:\天仪SAR卫星数据集\舰船数据\bc2-sp-org-vv-20250205t032055-021998-000036-0055ee-01.txt", help='输出geojson文件')
|
||
parser.add_argument('-o', '--outfile',type=str,default=r"F:\天仪SAR卫星数据集\舰船数据\切片结果", help='输出geojson文件')
|
||
group = parser.add_mutually_exclusive_group()
|
||
group.add_argument(
|
||
'--filemode',
|
||
action='store_const',
|
||
const='filemode',
|
||
dest='mode',
|
||
help='文件模式'
|
||
)
|
||
group.add_argument(
|
||
'--slicemode',
|
||
action='store_const',
|
||
const='slicemode',
|
||
dest='mode',
|
||
help='切片模式'
|
||
)
|
||
parser.set_defaults(mode='slicemode')
|
||
group = parser.add_mutually_exclusive_group()
|
||
group.add_argument(
|
||
'--Linear',
|
||
action='store_const',
|
||
const='Linear',
|
||
dest='method',
|
||
help='线性拉伸'
|
||
)
|
||
group.add_argument(
|
||
'--Linear1prec',
|
||
action='store_const',
|
||
const='Linear1',
|
||
dest='method',
|
||
help='1%线性拉伸'
|
||
)
|
||
group.add_argument(
|
||
'--Linear2prec',
|
||
action='store_const',
|
||
const='Linear2',
|
||
dest='method',
|
||
help='2%线性拉伸'
|
||
)
|
||
group.add_argument(
|
||
'--Linear5prec',
|
||
action='store_const',
|
||
const='Linear5',
|
||
dest='method',
|
||
help='5%线性拉伸'
|
||
)
|
||
group.add_argument(
|
||
'--SquareRoot',
|
||
action='store_const',
|
||
const='SquareRoot',
|
||
dest='method',
|
||
help='平方根拉伸'
|
||
)
|
||
parser.set_defaults(method='SquareRoot')
|
||
|
||
args = parser.parse_args()
|
||
return args
|
||
|
||
if __name__ == '__main__':
|
||
try:
|
||
parser = getParams()
|
||
intiffPath=parser.infile
|
||
modestr=parser.mode
|
||
methodstr = parser.method
|
||
|
||
if modestr == "filemode":
|
||
outbinPath = parser.outfile
|
||
print('infile=', intiffPath)
|
||
print('outfile=', outbinPath)
|
||
print('method=', methodstr)
|
||
stretchProcess(intiffPath, outbinPath, methodstr)
|
||
elif modestr == "slicemode":
|
||
outfolder = parser.outfile
|
||
portfilestr = parser.portfile
|
||
print('infile=', intiffPath)
|
||
print('outfolder=', outfolder)
|
||
print('method=', methodstr)
|
||
print('portfile=', portfilestr)
|
||
stretchSliceProcess(intiffPath, outfolder,portfilestr, methodstr)
|
||
pass
|
||
else:
|
||
print("模式错误")
|
||
exit(2)
|
||
except Exception as e:
|
||
print(e)
|
||
exit(3)
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|