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function FastSeparableFilteredNoiseDemo(filtertype, rectSize, kwidth, scale, syncToVBL, dontclear, validate)
% FastSeparableFilteredNoiseDemo([filtertype=1][, rectSize=128][, kwidth=5][, scale=1][, syncToVBL=1][, dontclear=0][, validate=0])
%
% Demonstrates how to generate, filter and draw noise patches on-the-fly
% in a fast way by use of GLSL fragment shaders.
% Use it to benchmark your system by varying the load. If you like this demo
% then also have a look at FastMaskedNoiseDemo that shows how to
% efficiently draw a masked stimulus by use of alpha-blending.
%
% filtertype = Type of filter to apply, see switch statement below for
% supported filters. Zero selects no filtering, 1 is Gaussian blur.
%
% rectSize = Size of the generated random noise image: rectSize by rectSize
% pixels. This is also the size of the Psychtoolbox noise
% texture.
%
% kwidth = For filters which support a varying kernel size, the kernel
% size. Will create a kwidth x kwidth convolution kernel.
%
% scale = Scalefactor to apply to texture during drawing: E.g. if you'd set
% scale = 2, then each noise pixel would be replicated to draw an image
% that is twice the width and height of the input noise image. In this
% demo, a nearest neighbour filter is applied, i.e., pixels are just
% replicated, not bilinearly filtered -- Important to preserve statistical
% independence of the random pixel values!
%
% syncToVBL = 1=Synchronize bufferswaps to retrace. 0=Swap immediately when
% drawing is finished. Value zero is useful for benchmarking the whole
% system, because your measured framerate will not be limited by the
% monitor refresh rate -- Gives you a feeling of how much headroom is left
% in your loop.
%
% dontclear = If set to 1 then the backbuffer is not automatically cleared
% to background color after a flip. Can save up to 1 millisecond on old
% graphics hardware.
%
% Example results on a Intel Pentium-4 3.2 Ghz machine with a NVidia
% GeForce 7800 GTX graphics card, running under M$-Windows XP SP3:
%
% Two patches, 256 by 256 noise pixels each, scaled by any factor between 1
% and 5 yields a redraw rate of 100 Hz.
%
% One patch, 256 by 256 noise pixels, scaled by any factor between 1
% and 5 yields a redraw rate of 196 Hz.
%
% Two patches, 128 by 128 noise pixels each, scaled by any factor between 1
% and 5 yields a redraw rate of 360 - 380 Hz.
%
% One patch, 128 by 128 noise pixels, scaled by any factor between 1
% and 5 yields a redraw rate of 670 Hz.
% Abort script if it isn't executed on Psychtoolbox-3:
AssertOpenGL;
% Assign default values for all unspecified input parameters:
numRects = 1;
if nargin < 1 || isempty(filtertype)
filtertype = 1; % Gaussian blur by default.
end
if nargin < 2 || isempty(rectSize)
rectSize = 128; % Default patch size is 128 by 128 noisels.
end
if nargin < 3 || isempty(kwidth)
kwidth = 5; % Kernel width is 5 x 5 by default.
end
if nargin < 4 || isempty(scale)
scale = 1; % Don't up- or downscale patch by default.
end
if nargin < 5 || isempty(syncToVBL)
syncToVBL = 1; % Synchronize to vertical retrace by default.
end
if syncToVBL > 0
asyncflag = 0;
else
asyncflag = 2;
end
if nargin < 6 || isempty(dontclear)
dontclear = 0; % Clear backbuffer to background color by default after each bufferswap.
end
if dontclear > 0
% A value of 2 will prevent any change to the backbuffer after a
% bufferswap. In that case it is your responsibility to take care of
% that, but you'll might save up to 1 millisecond.
dontclear = 2;
end
if nargin < 7 || isempty(validate)
validate = 0;
end
try
% Find screen with maximal index:
screenid = max(Screen('Screens'));
% Initialize OpenGL. We need it for the image processing:
InitializeMatlabOpenGL;
% Open fullscreen onscreen window on that screen. Background color is
% gray, double buffering is enabled. Return a 'win'dowhandle and a
% rectangle 'winRect' which defines the size of the window:
[win, winRect] = Screen('OpenWindow', screenid, 128);
% Build a separable filter kernel:
stddev = kwidth / 3;
stddev=30;
switch(filtertype)
case 0
kernel = [];
case 1
% Standard 2D gauss kernel:
kernel = fspecial('gaussian', kwidth, stddev);
% Same kernel split up into two 1D kernels:
kernel1 = fspecial('gaussian', [kwidth, 1], stddev);
kernel2 = fspecial('gaussian', [1, kwidth], stddev);
case 2
kernel = fspecial('prewitt');
end
stype = 2;
channels = 1;
if filtertype > 0
% Build shaders from kernels:
shader1 = EXPCreateStatic2DConvolutionShader(kernel1, channels, 1, stype, 1);
shader2 = EXPCreateStatic2DConvolutionShader(kernel2, channels, 1, stype, 1);
end
% Create a floating-point precision FBO for intermediate result of first filter pass:
[convolvefbo, convolvetex] = moglCreateFBO(rectSize, rectSize, 1, 4);
% Sync us to the GPU so our timing benchmarks are ok:
glFinish;
% Compute destination rectangle locations for the random noise patches:
% 'objRect' is a rectangle of the size 'rectSize' by 'rectSize' pixels of
% our Matlab noise image matrix:
objRect = SetRect(0,0, rectSize, rectSize);
% dstRect = CenterRect(objRect, winRect);
dstRect = objRect;
% Init framecounter to zero and take initial timestamp:
count = 0;
glFinish;
tstart = GetSecs;
endtime = tstart + 15;
% Run noise image drawing loop for 20 seconds.
while GetSecs < endtime
% Generate and draw 'numRects' noise images:
for i=1:numRects
% Compute noiseimg noise image matrix with Matlab:
% Normally distributed noise with mean 128 and stddev. 50, each
% pixel computed independently:
if (count==0 || validate < 2) noiseimg=(50*randn(rectSize, rectSize) + 128); end
% Validation enabled?
if validate == 1
% Cast it to uint8 so GPU and CPU get exactly the same
% input data:
noiseimg=uint8(noiseimg);
end
% Convert it to a texture 'tex':
tex=Screen('MakeTexture', win, noiseimg);
intex=Screen('GetOpenGLTexture', win, tex);
cotex=Screen('SetOpenGLTexture', win, [], convolvetex, GL.TEXTURE_RECTANGLE_EXT);
if validate == 1
glFinish;
tic
end
% Pass 1: Blit texture into our FBO, apply first kernel:
%moglChooseFBO(convolvefbo);
moglChooseFBO(0);
glUseProgram(shader1);
%moglBlitTexture(intex, [], [], [], [], 0, GL.CLAMP_TO_BORDER);
Screen('DrawTexture', win, tex, [], dstRect, [], 0);
% Pass 2: Blit intermediate result into framebuffer, apply
% second kernel:
%moglChooseFBO(0);
%glUseProgram(shader2);
%Screen('DrawTexture', win, cotex, [], dstRect, [], 0);
%moglBlitTexture(convolvetex, [], [], [], [], 0, GL.CLAMP_TO_BORDER);
% Done. Disable shader:
glUseProgram(0);
if validate == 1
glFinish;
gpu = toc
end
if validate == 1
% Compute same convolution on CPU:
noiseimg = single(noiseimg);
tic
ref = conv2(noiseimg, single(kernel1), 'same');
%ref = conv2(single(ref), single(kernel2), 'same');
%ref = conv2(noiseimg, (kernel), 'same');
cpu = toc
ref = uint8(0.5 + ref);
end
% After drawing, we can discard the noise texture.
Screen('Close', tex);
end
% Done with drawing the noise patches to the backbuffer: Initiate
% buffer-swap. If 'asyncflag' is zero, buffer swap will be
% synchronized to vertical retrace. If 'asyncflag' is 2, bufferswap
% will happen immediately -- Only useful for benchmarking!
Screen('Flip', win, 0, dontclear, asyncflag);
if validate == 1
gpu = Screen('GetImage', win, dstRect);
difference = gpu(:,:,1) - ref;
difference = difference(length(kernel):end-length(kernel), length(kernel):end-length(kernel));
maxdiff = max(max(difference))
end
% Increase our frame counter:
count = count + 1;
end
% We're done: Output average framerate:
glFinish;
telapsed = GetSecs - tstart
updaterate = count / telapsed
% Disable shader: Standard fixed-function pipeline is activated.
glUseProgram(0);
% Delete our FBO and its associated color buffer texture:
moglDeleteFBO(convolvefbo);
if validate == 1
imagesc(difference);
figure;
imagesc(noiseimg);
end
Screen('Close');
% Done. Close Screen, release all ressouces:
sca;
catch
% Our usual error handler: Close screen and then...
sca;
% ... rethrow the error.
psychrethrow(psychlasterror);
end
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