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Subject: Re: [boost] GIL io_new review
From: Mateusz Loskot (mateusz_at_[hidden])
Date: 2010-12-09 08:32:13

On 09/12/10 12:43, Domagoj Saric wrote:
> "Mateusz Loskot" <mateusz_at_[hidden]> wrote in message
>> I'd be interested in making similar tests myself. I have
>> access to georeferenced raster datasets as large as 90K x 45K pixels.
>> I also have extensive experience with GDAL (
>> library which I have used to process such datasets with success
>> However, I'm still missing specification of operations to be performed.
>> Can we describe Phil's use case in form of reproducible steps,
>> so we can pprogram this use case using with various toolkits/libraries?
>> As the datasets I have are not public data, I could use the True
>> Marble Imagery so the results are comparable.
>> What you think?
> I'm all for it...actually I think we should skip any intermediate
> 'editing' operations (as these will only obfuscate the test and the
> results) and just test something simple, like chopping up a huge TIFF
> into small PNGs...

Good idea.

1. Which raster are we taking from the True Marble Imagery?

2. To keep things simpler, let's cut the raster to even tiles.
For example, tiles of 200x200 pixels
This will give us constant number of 11664 tiles for 21600x21600 raster.

3. No form of parallelism of the cutting procedure is assumed, right?

4. Cutting TIFF to PNG involves compression. If we are interested in
raster access, RIO, I/O speed, perhaps we could stick to TIFF as output
format as well. What you think?

Speaking of the GDAL, I will write a chopper in C++ so we can compare
the same technology.
In the meantime, the library provides Python bindings and script
dedicated to raster tiling:
The Python should not impose a significant overhead being useful
for some quick prototyping.
If anyone would be interested in taking part in this benchmark,
GDAL for Windows is available through Cygwin-like installer:
For Unix, it's trivial to build:

Best regards,

Mateusz Loskot,
Charter Member of OSGeo,
Member of ACCU,

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