328 lines
13 KiB
Markdown
328 lines
13 KiB
Markdown
<refmeta>
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<refentrytitle>How libvips works</refentrytitle>
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<manvolnum>3</manvolnum>
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<refmiscinfo>libvips</refmiscinfo>
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</refmeta>
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<refnamediv>
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<refname>Internals</refname>
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<refpurpose>A high-level technical overview of libvips's evaluation system</refpurpose>
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</refnamediv>
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Compared to most image processing libraries, VIPS needs little RAM and runs
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quickly, especially on machines with more than one CPU. VIPS achieves this
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improvement by only keeping the pixels currently being processed in RAM
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and by having an efficient, threaded image IO system. This page explains
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how these features are implemented.
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# Images
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VIPS images have three dimensions: width, height and bands. Bands usually
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(though not always) represent colour. These three dimensions can be any
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size up to 2 ** 31 elements. Every band element in an image has to have the
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same format. A format is an 8-, 16- or 32-bit int, signed or unsigned, 32-
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or 64-bit float, and 64- or 128-bit complex.
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# Regions
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An image can be very large, much larger than the available memory, so you
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can't just access pixels with a pointer \*.
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Instead, you read pixels from an image with a region. This is a rectangular
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sub-area of an image. In C, the API looks like:
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```c
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VipsImage *image = vips_image_new_from_file( filename, NULL );
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VipsRegion *region = vips_region_new( image );
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// ask for a 100x100 pixel region at 0x0 (top left)
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VipsRect r = { left: 0, top: 0, width: 100, height: 100 };
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if( vips_region_prepare( region, &r ) )
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vips_error( ... );
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// get a pointer to the pixel at x, y, where x, y must
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// be within the region
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// as long as you stay within the valid area for the region,
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// you can address pixels with regular pointer arithmetic
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// compile with -DDEBUG and the macro will check bounds for you
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// add VIPS_REGION_LSKIP() to move down a line
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VipsPel *pixel = VIPS_REGION_ADDR( region, x, y );
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// you can call vips_region_prepare() many times
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// everything in libvips is a GObject ... when you're done,
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// just free with
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g_object_unref( region );
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```
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The action that `vips_region_prepare()` takes varies with the type of
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image. If the image is a file on disc, for example, then VIPS will arrange
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for a section of the file to be read in.
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(\* there is an image access mode where you can just use a pointer, but
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it's rarely used)
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# Partial images
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A partial image is one where, instead of storing a value for each pixel, VIPS
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stores a function which can make any rectangular area of pixels on demand.
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If you use `vips_region_prepare()` on a region created on a partial image,
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VIPS will allocate enough memory to hold the pixels you asked for and use
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the stored function to calculate values for just those pixels \*.
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The stored function comes in three parts: a start function, a generate
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function and a stop function. The start function creates a state, the
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generate function uses the state plus a requested area to calculate pixel
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values and the stop function frees the state again. Breaking the stored
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function into three parts is good for SMP scaling: resource allocation and
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synchronisation mostly happens in start functions, so generate functions
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can run without having to talk to each other.
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VIPS makes a set of guarantees about parallelism that make this simple to
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program. Start and stop functions are mutually exclusive and a state is
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never used by more than one generate. In other words, a start / generate /
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generate / stop sequence works like a thread.
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![](Sequence.png)
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(\* in fact VIPS keeps a cache of calculated pixel buffers and will return
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a pointer to a previously-calculated buffer if it can)
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# Operations
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VIPS operations read input images and write output images, performing some
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transformation on the pixels. When an operation writes to an image the
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action it takes depends upon the image type. For example, if the image is a
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file on disc then VIPS will start a data sink to stream pixels to the file,
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or if the image is a partial one then it will just attach start / generate /
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stop functions.
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Like most threaded image processing systems, all VIPS operations have to
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be free of side-effects. In other words, operations cannot modify images,
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they can only create new images. This could result in a lot of copying if
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an operation is only making a small change to a large image so VIPS has a
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set of mechanisms to copy image areas by just adjusting pointers. Most of
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the time no actual copying is necessary and you can perform operations on
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large images at low cost.
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# Run-time code generation
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VIPS uses [Orc](http://code.entropywave.com/orc/), a run-time compiler, to
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generate code for some operations. For example, to compute a convolution
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on an 8-bit image, VIPS will examine the convolution matrix and the source
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image and generate a tiny program to calculate the convolution. This program
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is then "compiled" to the vector instruction set for your CPU, for example
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SSE3 on most x86 processors.
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Run-time vector code generation typically speeds operations up by a factor
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of three or four.
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# Joining operations together
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The region create / prepare / prepare / free calls you use to get pixels
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from an image are an exact parallel to the start / generate / generate /
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stop calls that images use to create pixels. In fact, they are the same:
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a region on a partial image holds the state created by that image for the
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generate function that will fill the region with pixels.
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![](Combine.png)
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VIPS joins image processing operations together by linking the output of one
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operation (the start / generate / stop sequence) to the input of the next
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(the region it uses to get pixels for processing). This link is a single
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function call, and very fast. Additionally, because of the the split between
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allocation and processing, once a pipeline of operations has been set up,
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VIPS is able to run without allocating and freeing memory.
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This graph (generated by `vipsprofile`, the vips profiler) shows memory use
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over time for a vips pipeline running on a large image. The bottom trace
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shows total memory, the upper traces show threads calculating useful results
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(green), threads blocked on synchronisation (red) and memory allocations
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(white ticks).
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![](Memtrace.png)
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Because the intermediate image is just a small region in memory, a pipeline
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of operations running together needs very little RAM. In fact, intermediates
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are small enough that they can fit in L2 cache on most machines, so an
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entire pipeline can run without touching main memory. And finally, because
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each thread runs a very cheap copy of just the writeable state of the
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entire pipeline, threads can run with few locks. VIPS needs just four lock
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operations per output tile, regardless of the pipeline length or complexity.
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# Data sources
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VIPS has data sources which can supply pixels for processing from a variety
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of sources. VIPS can stream images from files in VIPS native format, from
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tiled TIFF files, from binary PPM/PGM/PBM/PFM, from Radiance (HDR) files,
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from FITS images and from tiled OpenEXR images. VIPS will automatically
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unpack other formats to temporary disc files for you but this can
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obviously generate a lot of disc traffic. It also has a special
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sequential mode for streaming operations on non-random-access
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formats. Another section in these docs explains [how libvips opens a
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file](How-it-opens-files.html). One
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of the sources uses the [ImageMagick](http://www.imagemagick.org) (or
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optionally [GraphicsMagick](http://www.graphicsmagick.org)) library, so
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VIPS can read any image format that these libraries can read.
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VIPS images are held on disc as a 64-byte header containing basic image
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information like width, height, bands and format, then the image data as
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a single large block of pixels, left-to-right and top-to-bottom, then an
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XML extension block holding all the image metadata, such as ICC profiles
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and EXIF blocks.
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When reading from a large VIPS image (or any other format with the same
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structure on disc, such as binary PPM), VIPS keeps a set of small rolling
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windows into the file, some small number of scanlines in size. As pixels
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are demanded by different threads VIPS will move these windows up and down
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the file. As a result, VIPS can process images much larger than RAM, even
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on 32-bit machines.
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# Data sinks
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In a demand-driven system, something has to do the demanding. VIPS has a
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variety of data sinks that you can use to pull image data though a pipeline
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in various situations. There are sinks that will build a complete image
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in memory, sinks to draw to a display, sinks to loop over an image (useful
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for statistical operations, for example) and sinks to stream an image to disc.
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The disc sink looks something like this:
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![](Sink.png)
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The sink keeps two buffers\*, each as wide as the image. It starts threads
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as rapidly as it can up to the concurrency limit, filling each buffer with
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tiles\*\* of calculated pixels, each thread calculating one tile at once. A
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separate background thread watches each buffer and, as soon as the last tile
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in a buffer finishes, writes that complete set of scanlines to disc using
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whatever image write library is appropriate. VIPS can write with libjpeg,
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libtiff, libpng and others. It then wipes the buffer and repositions it
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further down the image, ready for the next set of tiles to stream in.
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These features in combination mean that, once a pipeline of image processing
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operations has been built, VIPS can run almost lock-free. This is very
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important for SMP scaling: you don't want the synchronization overhead to
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scale with either the number of threads or the complexity of the pipeline
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of operations being performed. As a result, VIPS scales almost linearly
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with increasing numbers of threads:
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![](Vips-smp.png)
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Number of CPUs is on the horizontal axis, speedup is on the vertical
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axis. Taken from the [[Benchmarks]] page.
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(\* there can actually be more than one, it allocate enough buffers to
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ensure that there are at least two tiles for every thread)
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(\*\* tiles can be any shape and size, VIPS has a tile hint system that
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operations use to tell sinks what tile geometry they prefer)
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# Operation cache
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Because VIPS operations are free of side-effects\*, you can cache them. Every
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time you call an operation, VIPS searches the cache for a previous call to
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the same operation with the same arguments. If it finds a match, you get
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the previous result again. This can give a huge speedup.
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By default, VIPS caches the last 1,000 operation calls. You can also control
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the cache size by memory use or by files opened.
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(\* Some vips operations DO have side effects, for example,
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`vips_draw_circle()` will draw a circle on an image. These operations emit an
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"invalidate" signal on the image they are called on and this signal makes
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all downstream operations and caches drop their contents.)
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# Operation database and APIs
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VIPS has around 300 image processing operations written in this style. Each
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operation is a GObject class. You can use the standard GObject calls to walk
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the class hierarchy and discover operations, and libvips adds a small amount
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of extra introspection metadata to handle things like optional arguments.
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The [C API](using-from-c.html) is a set of simple wrappers which create
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class instances for you. The [C++ API](using-from-cpp.html) is a little
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fancier and adds things like automatic object lifetime management. The
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[command-line interface](using-cli.html) uses introspection to run any vips
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operation in the class hierarchy.
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The [Python API](using-from-python.html) is built on top of
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gobject-introspection. It is written in Python, so as long as you can get
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gobject-introspection working, you should be able to use vips. It supports
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python2 and python3 and works on Linux, OS X and Windows.
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# Snip
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The VIPS GUI, nip2, has its own scripting language called Snip. Snip is a
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lazy, higher-order, purely functional, object oriented language. Almost all
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of nip2's menus are implemented in it, and nip2 workspaces are Snip programs.
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VIPS operations listed in the operation database appear as Snip functions. For
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example, `abs` can be used from Snip as:
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```
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// absolute value of image b
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a = vips_call "abs" [b] [];
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```
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However, `abs` won't work on anything except the primitive vips image type. It
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can't be used on any class, or list or number. Definitions in `_stdenv.dev`
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wrap each VIPS operation as a higher level Snip operation. For example:
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```
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abs x
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= oo_unary_function abs_op x, is_class x
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= vips_call "abs" [x] [], is_image x
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= abs_cmplx x, is_complex x
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= abs_num x, is_real x
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= abs_list x, is_real_list x
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= abs_list (map abs_list x), is_matrix x
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= error (_ "bad arguments to " ++ "abs")
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{
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abs_op = Operator "abs" abs Operator_type.COMPOUND false;
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abs_list l = (sum (map square l)) ** 0.5;
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abs_num n
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= n, n >= 0
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= -n;
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abs_cmplx c = ((re c)**2 + (im c)**2) ** 0.5;
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}
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```
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This defines the behaviour of `abs` for the base Snip types (number, list,
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matrix, image and so on), then classes will use that to define operator
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behaviour on higher-level objects.
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Now you can use:
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```
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// absolute value of anything
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a = abs b;
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```
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and you ought to get sane behaviour for any object, including things like
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the `Matrix` class.
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You can write Snip classes which present functions to the user as menu
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items. For example, `Math.def` has this:
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```
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Math_arithmetic_item = class
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Menupullright "_Arithmetic" "basic arithmetic for objects" {
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Absolute_value_item = class
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Menuaction "A_bsolute Value" "absolute value of x" {
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action x = map_unary abs x;
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}
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}
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```
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Now the user can select an object and click `Math / Abs` to find the absolute
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value of that object.
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