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Do yourself a favour and follow Luc's advice: Buy or borrow a book which takes you into basics of object orientation and C#. This 'trial and error' method does not make much sense.
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Hi all,
I'm working with a machine vision package which uses a proprietary internal image format. Their package will convert to many common formats (jpg/bmp/png/etc) but this conversion is only done to disk and I want to do an in-memory conversion because the to-disk conversion is just plain too slow (>200ms).
Their format for 8bit color images is 3 separate planes (R,G&B) which easily combine into a 24bpp BitMap like this:
private static unsafe void CopyColorPlanes( BitmapData bmp, IntPtr _b, IntPtr _g, IntPtr _r )
{
byte* imgPtr = (byte*)bmp.Scan0;
int h = bmp.Height;
int w = bmp.Width;
int s = bmp.Stride;
byte* b = (byte*)_b;
byte* g = (byte*)_g;
byte* r = (byte*)_r;
for ( int row = 0; row < h; row++ ) {
for ( int col = 0; col < w; col++ ) {
*imgPtr++ = *b++;
*imgPtr++ = *g++;
*imgPtr++ = *r++;
}
imgPtr += ( ( s / 3 ) - w ) * 3;
}
}
This works well and is "reasonably" fast - a 1600x1200 color image conversion takes roughly 42ms on a 1.8MHz VIA C7 (the target system).
Two questions:
1) Does anyone see anything in the above method that could be tweaked (staying within "pure" C#) to make it faster? (I've already tried partitioning the source planes into halves and quarters to make them fit better in the CPU cache and while this has a small impact it's not significant and interestingly, doing columns in the outer loop runs about 10% faster on an AMD DualCore 4200 - go figger).
2) Is there some native Windows API that will do this job?
I know I probably end up crafting this in assembly but I view that as a last resort... and deadlines loom...
Subvert The Dominant Paradigm
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Give the compiler a clue and precalculate the alignment adjustment - it may or may not optimise it out of the loop.
It would be worth experimenting with a 32bpp bitmap (ARGB) instead of a 24 (RGB) - that way you can assemble it in an Int32 and save only once - depending on your cache etc it may be faster to do one 32 bit write than three 8 bit ones.
Rather than assembler, I would go to native C/C++ code first. That will probably be fast enough and a lot more maintainable.
Real men don't use instructions. They are only the manufacturers opinion on how to put the thing together.
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Ahhhh... assemble into a single uint and then store. I'll try that.
Thanks.
Subvert The Dominant Paradigm
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Ennis Ray Lynch, Jr. wrote: About as fast as C# will get. C++ is must faster.
Ther's nothing like horsepower to cover lazy programmers.
For giggles I tried this:
Parallel.For( 0, bmp.Height, row => {
byte* b = (byte*)_b + ( row * bmp.Width );
byte* g = (byte*)_g + ( row * bmp.Width );
byte* r = (byte*)_r + ( row * bmp.Width );
byte* dst = row <= 0 ? (byte*)bmp.Scan0 : (byte*)bmp.Scan0 + ( ( bmp.Width * 3 ) * row ) + ( ( bmp.Stride / 3 ) - bmp.Width ) * 3;
for ( int col = 0; col < bmp.Width; col++ ) {
*dst++ = *b++;
*dst++ = *g++;
*dst++ = *r++;
}
} );
On my dual I9 it's pretty fast (well, reallllyyyy fast). Unfortunately that's not the production target.
Subvert The Dominant Paradigm
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jkohler wrote: Unfortunately that's not the production target.
What are you targeting, Core2?
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VIA C7 @ 1.8 MHz
It does pretty well until images get large and they no longer fit in the onboard caches....
Subvert The Dominant Paradigm
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I don't know much about the architecture they use..
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One of the other replies suggested using a 32 bit destination - which means you've probably changed the 'next destination pixel' calculation - but if you're still working with 24 bit destination pixels, moving the ( ( s / 3 ) - w ) * 3 expression outside the loops may make a difference (although, the C# compiler may have already done this in an optimization step). Division is timeconsuming - and this whole expression is constant for all loop iterations.
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I just tried the 32bpp image format which on my development system gives a ~5% improvement. Unfortunately, on the target system (VIA C7) it makes little measurable difference. I expect any gain in execution speed is consumed in the increase in bitmap size (adding an additional byte per pixel to a 1600x1200 image is a significant increase in terms of CPU cache, etc.).
Moving the loop invariant outside the loop does indeed make a small difference when running in the debugger but release code? No difference at all. And interstingly the 32bpp format does not require that little calculation to be done at all.
In case you're interested, the 32bpp image version:
private static unsafe void CopyColorPlanes32( BitmapData bmp, IntPtr _b, IntPtr _g, IntPtr _r )
{
int* imgPtr = (int*)bmp.Scan0;
const int h = bmp.Height;
const int w = bmp.Width;
const int alphaValue = 0xff << 24;
byte* b = (byte*)_b;
byte* g = (byte*)_g;
byte* r = (byte*)_r;
for ( int row = 0; row < h; row++ )
for ( int col = 0; col < w; col++ )
*imgPtr++ = alphaValue | *b++ | ( *g++ << 8 ) | ( *r++ << 16 );
}
Subvert The Dominant Paradigm
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Although it propably won't give you much, you could try to optimize your for-loop in the following ways:
- Instead of having nesting the 2 for-loops - you could try to have just one
- Counting backwards
- Use != instead of <
- Use ++n instead of ++n
for( int n=(h*w)-1; n!=-1; --n)
for( int n=h*w; n!=0; --n)
Although the compiler/JIT should already have done some the above optimizations, I have seen measurable improvements doing the above in certain areas.
/Michael
Edit: Modified the for-loop as you aren't using the 'n' for indexing.
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Michael B. Hansen wrote: Although the compiler/JIT should already have done some the above optimizations, I have seen measurable improvements doing the above in certain areas.
As Have I...
And although it is ugly, you may want to look @ the target environment architecture and optimize the loop (unroll manually) to make a write equal to the available size of register, this should boost speed a Lot.!
-I have a related post.. not to toot my own horn... but TOOT.
I'd blame it on the Brain farts.. But let's be honest, it really is more like a Methane factory between my ears some days then it is anything else...
-"The conversations he was having with himself were becoming ominous."-.. On the radio...
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Have you thought of declaring a union of a int and four chars for imgPtr and allowing the compiler to effectively decided how to do the bit shifts when you assign r g and b ? Also decrementing loops are faster since they simply require a compare with 0 and loop instruction rather than loading two values comparing and then looping.
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A union.... Apparently I've forgotten the basics.
Thanks for the reminder - even if it doesn't shave any cycles it'll definitley have a higher cool factor.
As to reversing the loop - your point is taken and appreciated.
Subvert The Dominant Paradigm
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Write the loop as suggested by Michael. The processor might even have its own instructions for copying a byte from one register into a different byte in another (or even combining multiple byte copies into a single instruction). Look at the assembler for the bit shift and or solution and the union and see which is more efficient. I'm interested to hear how much faster it becomes.
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It isn't a division. It's a constant division by k , which any sane compiler (even the .NET JIT compiler, though its sanity is debatable) turns into a multiplication with approximately 0x100000000 / k (and possibly a few extra instructions for correct signed rounding) or some other constant, depending on the data size.
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I hope it also does some scaling: 0x100000000 is a mighty big factor to introduce without the matching 32 bit right shift.
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You don't need to, you can just take the upper half (edx)
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You got me there.
The last time I really looked at CPUs, registers and assembly language was a long time ago, in a galaxy far, far away (the Motorola 68k family, to be exact). And I never did get to know the Intel CPUs.
By now I've been working at the C/C++/C# level for far too long and I've clearly got soft in the head - and didn't put 2 & 2 together ("64 bit CPUs" => 64 bit registers! )
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There is that funny 64bit thing.. but.. x86 has always had a double-width mul (although it used to give almost no advantage compared to div)
You can even multiply 2 64bit numbers and get a 128bit result (in rdx:rax)
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That pesky Intel chip. Always doing things by halves!
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I've faced the exact same issue a little while ago (targeting a different processor though). IIRC the big surprise for me was that I gained a significant performance increase by swapping from the for loop you have to the while loop below (must be friendlier to the C# optimizer). Something else you might try is to manually unroll your loop to do 4 pixels at a time in the inner loop and read your source image channels 32-bits at a time. This is definitely something where you'd benefit from dropping down to native code if the performance of this step is that critical (and if p/invoke proves to be significant you can implement it using a mixed mode assembly). Usually with machine vision though converting to a packed byte format is only done as a last step for displaying/storing the results, processing is usually done in planar formats (which I really wouldn't call 'proprietary' either btw) for better performance.
private static unsafe void PlanarToPackedByteRgb32(
int width, int height,
IntPtr rSrc, IntPtr gSrc, IntPtr bSrc,
IntPtr dest, int stride)
{
var rSrcPtr = (byte*)rSrc.ToPointer();
var gSrcPtr = (byte*)gSrc.ToPointer();
var bSrcPtr = (byte*)bSrc.ToPointer();
var destPtr = (byte*)dest.ToPointer();
var destEndPtr = destPtr + stride * height;
var rowStep = 4 * width;
while (destPtr != destEndPtr)
{
var it = (uint*)destPtr;
var end = (uint*)(destPtr + rowStep);
destPtr += stride;
while (it != end)
{
*it++ =
((uint)(*rSrcPtr++) << 16) |
((uint)(*gSrcPtr++) << 8) |
((uint)(*bSrcPtr++) << 0);
}
}
}
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I wonder how fast your function is when you don't do anything within your 'for loops'
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To all,
Thank you one and all for your responses.
Of all the suggestions the one with the largest impact on speed is the one going to the 32bpp format. This reduced the conversion time from ~50ms to ~42ms but the extra 1.9Mb required for each image is not (in my particular case) a good trade off. The other suggestions resulted in 1ms or maybe 2ms improvements with no single technique showing a clear improvement.
This project involves inspecting components in trays - there may be up to 4 images per component with (so far) a max of 52 components per tray. All these images need to be available to the operator at "a touch of the screen".
With this many images (each is 1600x1200) I really just need to dust off the ol' C/ASM skills and convert to a 16bpp format - gaining 2Mb per image in the process.
Again, thanks for the suggestions.
Subvert The Dominant Paradigm
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