栅格数据包将图像拆分为多个 [英] R raster package split image into multiples

问题描述

我的图像如下.它是2579 * 2388像素.假设它的左下角为0,0.从该图像中，我要创建多个图像，如下所示，并将它们保存在工作文件夹中.每个图像的大小为100 * 100像素.每个图像将通过其左下角的坐标进行保存.

I have an image as below. It is 2579*2388 pixels. Lets assume that it's bottom left corner is at 0,0. From that image I want to create multiple images as follows and save them in the working folder. Each image will have size of 100*100 pixels. Each image will be saved by it's bottom left hand coordinates.

1. 第一个图像的左下角为0,0.右上 手角将在100,100，并且图像将另存为 0-0.jpg
2. second的左下角为10,0.右上角 角落将为110,100，图片将另存为10-0.jpg
3. 完成下一行后，Y坐标将移动10.在 如果是第二行，则第一张图片将为0,10，而该图片 将另存为0-10.jpg

1. first image will have its bottom left hand corner at 0,0. Top right hand corner will be at 100,100 and the image will be saved as 0-0.jpg
2. second will have its bottom left hand corner at 10,0. Top right hand corner will be at 110,100 and the image will be saved as 10-0.jpg
3. Once the bottom row is completed, Y coordinate will move by 10. In case of second row, the first image will be at 0,10 and that image will be saved as 0-10.jpg

最快的方法是什么?是否有任何R软件包可以非常快速地完成它?

what is the fastest way to do this? is there any R package which could do it very fast?

我知道在当前图像的情况下，它将把它分成大约257 * 238张图像.但是我有足够的磁盘空间，我需要每个图像来执行文本检测.

I understand that in the case of the current image, it will split it into around 257*238 images. But I have sufficient disk space and i need each image to perform text detection.

推荐答案

这里是使用光栅"包的另一种方法.该功能在空间上聚合要切碎的栅格，将聚合的栅格像元转换为多边形，然后使用每个多边形的范围来裁剪输入栅格.

Here another approach using "raster" package. The function spatially aggregates the raster to be chopped, the aggregated raster cells are turned into polygons, then each polygon's extent is used to crop the input raster.

我敢肯定，有很多复杂的方法可以做到这一点，但是这种方法对我有用，我也觉得它很直观.我希望您也觉得它有用.注意第4部分和下面的5仅用于测试，它们不是该功能的一部分.

I am sure there are sophisticated and compact ways to do this but this approach works for me and I found it intuitive as well. I hope you find it useful too. Notice Part 4 & 5 below are only for testing and they are not part of the function.

logo <- raster(system.file("external/rlogo.grd", package="raster"))
plot(logo,axes=F,legend=F,bty="n",box=FALSE)

第2部分:函数本身:

# The function spatially aggregates the original raster
# it turns each aggregated cell into a polygon
# then the extent of each polygon is used to crop
# the original raster.
# The function returns a list with all the pieces
# in case you want to keep them in the memory. 
# it saves and plots each piece
# The arguments are:
# raster = raster to be chopped            (raster object)
# ppside = pieces per side                 (integer)
# save   = write raster                    (TRUE or FALSE)
# plot   = do you want to plot the output? (TRUE or FALSE)
SplitRas <- function(raster,ppside,save,plot){
  h        <- ceiling(ncol(raster)/ppside)
  v        <- ceiling(nrow(raster)/ppside)
  agg      <- aggregate(raster,fact=c(h,v))
  agg[]    <- 1:ncell(agg)
  agg_poly <- rasterToPolygons(agg)
  names(agg_poly) <- "polis"
  r_list <- list()
  for(i in 1:ncell(agg)){
    e1          <- extent(agg_poly[agg_poly$polis==i,])
    r_list[[i]] <- crop(raster,e1)
  }
  if(save==T){
    for(i in 1:length(r_list)){
      writeRaster(r_list[[i]],filename=paste("SplitRas",i,sep=""),
                  format="GTiff",datatype="FLT4S",overwrite=TRUE)  
    }
  }
  if(plot==T){
    par(mfrow=c(ppside,ppside))
    for(i in 1:length(r_list)){
      plot(r_list[[i]],axes=F,legend=F,bty="n",box=FALSE)  
    }
  }
  return(r_list)
}

第3部分:测试功能

SplitRas(raster=logo,ppside=3,save=TRUE,plot=TRUE)
# in this example we chopped the raster in 3 pieces per side
# so 9 pieces in total
# now the raster pieces should be ready 
# to be processed in the default directory
# A feature I like about this function is that it plots
# the pieces in the original order. 

第4部分:在每篇文章上都运行一个代码&将它们保存回目录

# notice if you cropped a rasterbrick 
# use "brick" instead of "raster" to read
# the piece back in R
list2 <- list()
for(i in 1:9){ # change this 9 depending on your number of pieces
  rx <- raster(paste("SplitRas",i,".tif",sep=""))
  # piece_processed <- HERE YOU RUN YOUR CODE
  writeRaster(piece_processed,filename=paste("SplitRas",i,sep=""),
              format="GTiff",datatype="FLT4S",overwrite=TRUE)
}
# once a code has been ran on those pieces
# we save them back in the directory 
# with the same name for convenience

第5部分:让我们将各个部分放回一起

# read each piece back in R
list2 <- list()
for(i in 1:9){ # change this 9 depending on your number of pieces
  rx <- raster(paste("SplitRas",i,".tif",sep=""))
  list2[[i]] <- rx
}
# mosaic them, plot mosaic & save output
list2$fun   <- max
rast.mosaic <- do.call(mosaic,list2)
plot(rast.mosaic,axes=F,legend=F,bty="n",box=FALSE)
writeRaster(rast.mosaic,filename=paste("Mosaicked_ras",sep=""),
            format="GTiff",datatype="FLT4S",overwrite=TRUE)

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