Oops. I accidentally typed TWICE qemu-img resize hdd.img +100GB and now I have an image who thinks it can grow to 340GB on a 300GB disk.
Trying qemu-img resize hdd.img -100GB returns :
qcow2 doesn't support shrinking images yet
Please advice :-)
EDIT: # qemu-img info dev1hdd1.img:
image: hdd.img
file format: qcow2
virtual size: 340G (365072220160 bytes)
disk size: 100G
cluster_size: 65536
Format specific information:
compat: 0.10
Given the lack of shrink support, I believe your only option is to create a new image with the correct size and use qemu-img convert to copy the data across
Related
I have a big GeoTIFF that I want to stream through a WMS within GeoServer (v.2.11). The size of the image is about 7GB, consisting on a very large high resolution RGB image. I have allowed enough heap space within JVM in order to display the imagery. However, I would like to compress the image so it can be more responsive when exploring through and so it will allocate less memory. I have followed some of the recommendations here.
My strategy was to compress the GeoTIFF with JPEG compression and use that as a data store in GeoServer. However, this seems not to work. This is the gdal command I have used to translate the image:
gdal_translate -of GTiff -co "BIGTIFF=YES" -co "COMPRESS=JPEG" -co "TILED=YES" -co "BLOCKXSIZE=512" -co "BLOCKYSIZE=512" -a_srs "EPSG:3057" D:\raster\image.tif
D:\raster\image_translate.tif
When previewing the image with openlayers, I got nothing, just a blank basemap. The log from GeoServer told me that something in the projection went bad:
2017-06-09 13:16:47,551 INFO [geoserver.wms] -
Request: getServiceInfo
2017-06-09 13:16:47,561 WARN [lite.gridcoverage2d] - Could not reduce the grid geometry inside the valid area bounds: ReferencedEnvelope[-1.7976931348623157E308 : 1.7976931348623157E308, -85.0 : 85.0]
Grid geometry isGridGeometry2D[GeneralGridEnvelope[0..357, 0..357], PARAM_MT["Affine",
PARAMETER["num_row", 3],
PARAMETER["num_col", 3],
PARAMETER["elt_0_0", 0.7353351955307262],
PARAMETER["elt_0_2", 584219.1848475977],
PARAMETER["elt_1_1", -0.7353351955307262],
PARAMETER["elt_1_2", 383937.61122240225]]]
2017-06-09 13:16:47,566 ERROR [geoserver.ows] -
org.geoserver.platform.ServiceException: Error rendering coverage on the fast path
I then tried to use another compression strategy with GDAL, i.e. "DEFLATE":
gdal_translate -of GTiff -co COMPRESS=DEFLATE -co PREDICTOR=2 -co ZLEVEL=9 -co "BIGTIFF=YES" -a_srs "EPSG:3057" D:\raster\image.tif D:\raster\image_translate2.tif
And that worked when previewing in openlayers. Here is the GeoServer log:
2017-06-09 13:28:27,137 INFO [geoserver.wms] -
Request: getServiceInfo
2017-06-09 13:28:27,146 WARN [lite.gridcoverage2d] - Could not reduce the grid geometry inside the valid area bounds: ReferencedEnvelope[-1.7976931348623157E308 : 1.7976931348623157E308, -85.0 : 85.0]
Grid geometry isGridGeometry2D[GeneralGridEnvelope[0..357, 0..357], PARAM_MT["Affine",
PARAMETER["num_row", 3],
PARAMETER["num_col", 3],
PARAMETER["elt_0_0", 0.7353351955307262],
PARAMETER["elt_0_2", 584219.1848475977],
PARAMETER["elt_1_1", -0.7353351955307262],
PARAMETER["elt_1_2", 383937.61122240225]]]
2017-06-09 13:28:27,231 INFO [geoserver.wms] -
Request: getMap
I have also tried to perform gdal_translate using JPEG compression and no tiling, and I got also errors with the GeoServer log and the openlayers preview displayed nothing.
So my question is, what is the best strategy to compress GeoTIFF files to be used in a WMS? At the moment, seems that DEFLATE is the only one working, but the compression is not the best. Has anyone been able to successfully upload a JPEG compressed GeoTIFF to Geoserver?
If it's any help the way I do it is as follows.
First I chop the raster up into smaller tiles, size is not important, for me it's generally either 256x256, 512x512 or 1024x124.
I use a number of different programs from gdal2tiles.py to my own homegrown c# apps.
What's important is that the tiles are square.
Once I have the tiles in a folder, I then use gdaltindex
This creates a shapefile with one square for each tile, correctly georeferenced (assuming your raster was) along with the name of each tile, I usually tell gdaltindex to write absolute paths to the shapefile.
I then reference the shape as a tile layer in mapserver, I can't say if geoserver will accept a shape based tile index, but since gdal can make them and the other WMS based server available open source (mapserver) can use them, then I would be very suprised if geoserver was not able to use them.
This would work in the case of tiff greater than 2GB. GeoServer can efficiently deal with large TIFF with overviews, as long as the TIFF is below the 2GB size limit.
Using image pyramid makes the tiff load faster as it makes multiple mosaic of images at different zoom levels.
Use the following command:-
mkdir bmpyramid
gdal_retile.py -v -r bilinear -levels 4 -ps 2048 2048 -co "TILED=YES" -co "COMPRESS=JPEG" -targetDir bmpyramid bmreduced.tiff
You can check here
https://docs.geoserver.org/stable/en/user/tutorials/imagepyramid/imagepyramid.html
I am using GIMP to convert grayscale PNM-files (scanned documents) to PDF.
My goal is a small filesize. (Ideally: viewable on different devices without any problems and maybe suitable long-term preservation - PDF/A?)
So far, so good. Trying to reproduce that process with ImageMagick in a batch script doesn't give me that same small filesize as in GIMP.
GIMP (Ver. 2.8.14) workflow:
Open File
Change resolution (density) to 300x300 Pixel/in
Set threshold to 127 (=50%)
Export as OutGIMP.pdf
ImageMagick (Ver. 6.7.9-0 2012-09-16 Q16) workflow:
convert Scan.pnm -density 300x300 -threshold 50% -monochrome OutA.pdf
convert Scan.pnm -density 300x300 -threshold 50% -monochrome OutB.png
convert OutB.png OutC.pdf
Using an example File this results in:
OutGIMP.pdf: 141.195 Byte
OutA.pdf: 684.245 Byte
OutB.png: 137.246 Byte
OutC.pdf: 217.860 Byte
How can I get a PDF with ImageMagick that is at least as small as the GIMP-PDF?
Edit
Continuing the GIMP (Ver. 2.8.14) workflow from above with:
Scale to 100x100 Pixel/in while keeping the Imagesize
Export as OutGIMP_100ppi.pdf
strangely results in:
OutGIMP_100ppi.pdf: 179.123 Byte
I have many scanned document in PDF.
I use ImageMagick with Ghostscript to convert PDF to PNG in big density. I use convert -density 288 2.pdf 2.png. After that I read the pixels with PHP and find where is QR code and decode it. Because image is very big (~ 2500px), it's need very much RAM. I want, before I read pixels with PHP, to crop the image with ImageMagick and leave only that part with the QR code.
Can I detect the approximate location of QR code with ImageMagick, crop and leave only that part ?
Sample PDF
Converted PNG
Further Update
I see your discussion with Kurt about better extraction of the image from the PDF in the first place, and his recommendation was to use pdfimages. I just wanted to add that you won't find that if you do brew search pdfimages, but you actually need to use
brew install poppler
and then you get the pdfimages executable.
Updated Answer
If you change the tile size to 100x100 on the crop command and run this for the second PDF you supplied:
convert -density 288 pdf2.pdf -crop 100x100 tile%04d.png
and then use the same entropy analysis command
convert -format "%[entropy]:%X%Y:%f\n" tile*.png info: | sort -n
...
...
0.84432:+600+3100:tile0750.png
0.846019:+600+2800:tile0678.png
0.980938:+700+400:tile0103.png
0.984906:+700+500:tile0127.png
0.988808:+600+400:tile0102.png
0.998365:+600+500:tile0126.png
The last 4 listed tiles are
Likewise for the other PDF file you supplied, you get
0.863498:+1900+500:tile0139.png
0.954581:+2000+500:tile0140.png
0.974077:+1900+600:tile0163.png
0.97671:+2000+600:tile0164.png
which means these tiles
I would think that should help you pretty much approximately locate the QR code.
Original Answer
This is not all that scientific, but it may help you get started. The key, I think, is the entropy of the various areas of the image. The QR code has a lot of information encoded in a small area so it should have high entropy. So, I use ImageMagick to split the image into square 400x400 tiles like this:
convert image.png -crop 400x400 tile%03d.png
which gives me 54 tiles. Then I calculate the entropy of each of the tiles and sort them by increasing entropy, also outputting their offsets from the top left of the frame, and their name, like this:
convert -format "%[entropy]:%X%Y:%f\n" tile*.png info: | sort -n
0.00408949:+1200+2800:tile045.png
0.00473755:+1600+2800:tile046.png
0.00944815:+800+2800:tile044.png
0.0142171:+1200+3200:tile051.png
0.0143607:+1600+3200:tile052.png
0.0341039:+400+2800:tile043.png
0.0349564:+800+3200:tile050.png
0.0359226:+800+0:tile002.png
0.0549334:+800+400:tile008.png
0.0556793:+400+3200:tile049.png
0.0589632:+400+0:tile001.png
0.0649078:+1200+0:tile003.png
0.10811:+1200+400:tile009.png
0.116287:+2000+3200:tile053.png
0.120092:+800+800:tile014.png
0.12454:+0+2800:tile042.png
0.125963:+1600+0:tile004.png
0.128795:+800+1200:tile020.png
0.133506:+0+400:tile006.png
0.139894:+1600+400:tile010.png
0.143205:+2000+2800:tile047.png
0.144552:+400+2400:tile037.png
0.153143:+0+0:tile000.png
0.154167:+400+400:tile007.png
0.173786:+0+2400:tile036.png
0.17545:+400+1600:tile025.png
0.193964:+2000+400:tile011.png
0.209993:+0+3200:tile048.png
0.211954:+1200+800:tile015.png
0.215337:+400+2000:tile031.png
0.218159:+800+1600:tile026.png
0.230095:+2000+1200:tile023.png
0.237791:+2000+0:tile005.png
0.239336:+2000+1600:tile029.png
0.24275:+800+2400:tile038.png
0.244751:+0+2000:tile030.png
0.254958:+800+2000:tile032.png
0.271722:+2000+2000:tile035.png
0.275329:+0+1600:tile024.png
0.278992:+2000+800:tile017.png
0.282241:+400+1200:tile019.png
0.285228:+1200+1200:tile021.png
0.290524:+400+800:tile013.png
0.320734:+0+800:tile012.png
0.330168:+1600+2000:tile034.png
0.360795:+1200+2000:tile033.png
0.391519:+0+1200:tile018.png
0.421396:+1200+1600:tile027.png
0.421421:+2000+2400:tile041.png
0.421696:+1600+2400:tile040.png
0.486866:+1600+1600:tile028.png
0.489479:+1600+800:tile016.png
0.611449:+1600+1200:tile022.png
0.674079:+1200+2400:tile039.png
and, hey presto, the last one listed (i.e. the one with the highest entropy) tile039.png is this one.
I have drawn a rectangle around its location using this command
convert image.png -stroke red -fill none -strokewidth 3 -draw "rectangle 1200,2400 1600,2800" a.jpg
I concede there may be luck involved, but I only have one image to test my mad theories. You may need to tile twice, the second time with an x-offset and y-offset of half a tile width, so that you don't cut the QR code and split it across 2 tiles. You may need different size tiles for different size barcodes. You may need to consider the last 3-5 tiles located for your next algorithm. But I think it could form the basis of a method.
i want to shrink png or jpg on OSX. i only want to shrinkg without affecting the image quality.
like tinypng.org
is there any recommended library? i just know imagemagick. is there a way to do that natively? or another library to shrink/compress images without affecting the image quality?
my aim is to shrink the file size, for example:
logo.png >> 476 k before shrink
logo.png >> 50k after shrink
Edit: to be clear, i want to compress the size of the file, not the image resolution.
TinyPNG.org works by using image quantisation - the similar colours in the image are converted into a HSV or RGB model and then merged depending on the distance.
How does it work?
...
When you upload a PNG (Portable Network Graphics) file, similar colours in your image are combined. This technique is called “quantisation”
...
src: http://tinypng.org
An answer here outlines a method of doing so: https://stackoverflow.com/a/492230/556479.
There are also some answers on this question with refer to how you can do so on Mac OS using objective-c: How do I reduce a bitmap to a known set of RGB colours
See Wikipedia for a more in depth guide: http://en.wikipedia.org/wiki/Color_quantization
Did you have a problem using ImageMagick? It has a rich set of quantize functions such as
bool MagickQuantizeImage( MagickWand mgck_wnd,
float number_colors,
int colorspace_type,
float treedepth,
bool dither,
bool measure_error )
Here is a very thorough guide to quantization using imageMagick
My suggestion is to use http://pngnq.sourceforge.net, it will give better results than ImageMagick and for the single example given in http://tinypng.org, it also produces a very similar output. It is a tiny C implementation of the method present in the paper "Kohonen Neural Networks for Optimal Colour Quantization". That alone is much better since you are no longer relying on closed unknown implementations.
Original (57 KB), tinypng.org (16 KB), pngnq (17 KB):
Using ImageMagick, the best quantization to 256 colors I can get uses the LAB colorspace and dithering by Floyd-Steinberg:
convert input.png -quantize LAB -dither FloydSteinberg -colors 256 output.png
This produces a 16 KB png, but it contains much more visual artifacts:
I have a camera which produces photographs of 3008x2000 pixels. I use Image Magick to scale and resize the photos to be put up on my website. The size of the images I am using on the website is 602x400. I use this command to reduce the size:
convert DSC_0124.JPG -scale 20% -size 24% img1.jpg
This produces an image which is 602x400 pixels in size. But the file size will be always above 250KB. More images on a single html page means the page will be heavier and loading time will be longer. Are there any features in image magic that will help me to keep the file size as small as possible, possibly, below 100KB. But the image size should be the same, that is, 602x400px. I have achieved similar optimisation with SEAMonster tool for MS Windows. As it doean't have a commandline alternative, it wouldn't be of much help when there are hundreds of images to be converted.
Use command as Delan proposed with additional "-strip" flag to remove EXIF data, this have reduced the size of some of my images drastically. Here is a bash script for unix platforms, but you can use the second part only for individual images.
for X in *.jpg; do convert "$X" -resize 602x400 -strip -quality 86 "$X"; done
This will convert all images in the directory.
Use -quality to set the compression level:
convert DSC_0124.JPG -scale 20% -size 24% -quality [0..100] img1.jpg
You can define the maximum size of the output image at 100KB like this:
convert DSC_0124.JPG -resize 602x400! -strip -define jpeg:extent=100KB img1.jpg
If you are running your website on PHP, you might want to consider the SLIR image resizing script, it does a great job resizing to various constraints (see below) and caches the results.
Parameters:
w Maximum width
h Maximum height
c Crop ratio
q Quality
b Background fill color
p Progressive
http://shiftingpixel.com/2008/03/03/smart-image-resizer/
http://code.google.com/p/smart-lencioni-image-resizer/