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Merge changes from trunk.

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This commit is contained in:
castano 2009-03-18 04:04:09 +00:00
parent 9311ca532f
commit 2d64660714
17 changed files with 403 additions and 189 deletions
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8
branches/2.0/ChangeLog
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@ -1,9 +1,13 @@
NVIDIA Texture Tools version 2.0.6
* Fix dll version checking.
* Detect CUDA 2.1 correctly.
* Detect CUDA 2.1 and future CUDA versions correctly.
* Print CUDA detection message in nvcompress.
* Select the fastest CUDA device.
* Compile squish with -fPIC. Fixes issue 74.
* Merge changes from trunk to fix warnings under gcc 4.3.2.
* Fix warnings under gcc 4.3.2.
* Fix nvzoom option typo by Frank Richter. Fixes issue 81.
* Do not use CUDA to compress small mipmaps. Fixes issue 76.
* Compute mipmaps of semi-transparent images correctly.
NVIDIA Texture Tools version 2.0.5
* Fix error in single color compressor. Fixes issue 66.

4
branches/2.0/src/nvcore/Containers.h
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@ -824,13 +824,13 @@ namespace nv
}
/// Number of entries in the hash.
int size()
int size() const
{
return entry_count;
}
/// Number of entries in the hash.
int count()
int count() const
{
return size();
}

6
branches/2.0/src/nvcore/Debug.cpp
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@ -136,7 +136,11 @@ namespace
#if defined(HAVE_EXECINFO_H) // NV_OS_LINUX
static bool nvHasStackTrace() {
#if NV_OS_DARWIN
return backtrace != NULL;
#else
return true;
#endif
}
static void nvPrintStackTrace(void * trace[], int size, int start=0) {
@ -401,7 +405,7 @@ namespace
{
void * trace[64];
int size = backtrace(trace, 64);
nvPrintStackTrace(trace, size, 3);
nvPrintStackTrace(trace, size, 2);
}
# endif

2
branches/2.0/src/nvcore/DefsVcWin32.h
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@ -72,8 +72,6 @@ typedef uint32 uint;
#pragma warning(disable : 4711) // function selected for automatic inlining
#pragma warning(disable : 4725) // Pentium fdiv bug
#pragma warning(disable : 4345) // behavior change: an object of POD type constructed with an initializer of the form () will be default-initialized
#pragma warning(disable : 4786) // Identifier was truncated and cannot be debugged.
#pragma warning(disable : 4675) // resolved overload was found by argument-dependent lookup

6
branches/2.0/src/nvcore/StrLib.h
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@ -137,9 +137,9 @@ namespace nv
void stripExtension();
// statics
static char separator();
static const char * fileName(const char *);
static const char * extension(const char *);
NVCORE_API static char separator();
NVCORE_API static const char * fileName(const char *);
NVCORE_API static const char * extension(const char *);
};

6
branches/2.0/src/nvimage/Filter.cpp
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@ -33,11 +33,10 @@
* http://www.dspguide.com/ch16.htm
*/
#include "Filter.h"
#include <nvcore/Containers.h> // swap
#include <nvmath/nvmath.h> // fabs
#include <nvmath/Vector.h> // Vector4
#include <nvimage/Filter.h>
#include <nvcore/Containers.h> // swap
using namespace nv;
@ -582,7 +581,6 @@ PolyphaseKernel::PolyphaseKernel(const Filter & f, uint srcLength, uint dstLengt
m_data[i * m_windowSize + j] /= total;
}
}
}
PolyphaseKernel::~PolyphaseKernel()

114
branches/2.0/src/nvimage/Filter.h
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@ -11,16 +11,16 @@ namespace nv
class Vector4;
/// Base filter class.
class Filter
class NVIMAGE_CLASS Filter
{
public:
NVIMAGE_API Filter(float width);
NVIMAGE_API virtual ~Filter();
Filter(float width);
virtual ~Filter();
NVIMAGE_API float width() const { return m_width; }
NVIMAGE_API float sampleDelta(float x, float scale) const;
NVIMAGE_API float sampleBox(float x, float scale, int samples) const;
NVIMAGE_API float sampleTriangle(float x, float scale, int samples) const;
float width() const { return m_width; }
float sampleDelta(float x, float scale) const;
float sampleBox(float x, float scale, int samples) const;
float sampleTriangle(float x, float scale, int samples) const;
virtual float evaluate(float x) const = 0;
@ -29,56 +29,56 @@ namespace nv
};
// Box filter.
class BoxFilter : public Filter
class NVIMAGE_CLASS BoxFilter : public Filter
{
public:
NVIMAGE_API BoxFilter();
NVIMAGE_API BoxFilter(float width);
NVIMAGE_API virtual float evaluate(float x) const;
BoxFilter();
BoxFilter(float width);
virtual float evaluate(float x) const;
};
// Triangle (bilinear/tent) filter.
class TriangleFilter : public Filter
class NVIMAGE_CLASS TriangleFilter : public Filter
{
public:
NVIMAGE_API TriangleFilter();
NVIMAGE_API TriangleFilter(float width);
NVIMAGE_API virtual float evaluate(float x) const;
TriangleFilter();
TriangleFilter(float width);
virtual float evaluate(float x) const;
};
// Quadratic (bell) filter.
class QuadraticFilter : public Filter
class NVIMAGE_CLASS QuadraticFilter : public Filter
{
public:
NVIMAGE_API QuadraticFilter();
NVIMAGE_API virtual float evaluate(float x) const;
QuadraticFilter();
virtual float evaluate(float x) const;
};
// Cubic filter from Thatcher Ulrich.
class CubicFilter : public Filter
class NVIMAGE_CLASS CubicFilter : public Filter
{
public:
NVIMAGE_API CubicFilter();
NVIMAGE_API virtual float evaluate(float x) const;
CubicFilter();
virtual float evaluate(float x) const;
};
// Cubic b-spline filter from Paul Heckbert.
class BSplineFilter : public Filter
class NVIMAGE_CLASS BSplineFilter : public Filter
{
public:
NVIMAGE_API BSplineFilter();
NVIMAGE_API virtual float evaluate(float x) const;
BSplineFilter();
virtual float evaluate(float x) const;
};
/// Mitchell & Netravali's two-param cubic
/// @see "Reconstruction Filters in Computer Graphics", SIGGRAPH 88
class MitchellFilter : public Filter
class NVIMAGE_CLASS MitchellFilter : public Filter
{
public:
NVIMAGE_API MitchellFilter();
NVIMAGE_API virtual float evaluate(float x) const;
MitchellFilter();
virtual float evaluate(float x) const;
NVIMAGE_API void setParameters(float a, float b);
void setParameters(float b, float c);
private:
float p0, p2, p3;
@ -86,29 +86,29 @@ namespace nv
};
// Lanczos3 filter.
class LanczosFilter : public Filter
class NVIMAGE_CLASS LanczosFilter : public Filter
{
public:
NVIMAGE_API LanczosFilter();
NVIMAGE_API virtual float evaluate(float x) const;
LanczosFilter();
virtual float evaluate(float x) const;
};
// Sinc filter.
class SincFilter : public Filter
class NVIMAGE_CLASS SincFilter : public Filter
{
public:
NVIMAGE_API SincFilter(float w);
NVIMAGE_API virtual float evaluate(float x) const;
SincFilter(float w);
virtual float evaluate(float x) const;
};
// Kaiser filter.
class KaiserFilter : public Filter
class NVIMAGE_CLASS KaiserFilter : public Filter
{
public:
NVIMAGE_API KaiserFilter(float w);
NVIMAGE_API virtual float evaluate(float x) const;
KaiserFilter(float w);
virtual float evaluate(float x) const;
NVIMAGE_API void setParameters(float a, float stretch);
void setParameters(float a, float stretch);
private:
float alpha;
@ -118,12 +118,12 @@ namespace nv
/// A 1D kernel. Used to precompute filter weights.
class Kernel1
class NVIMAGE_CLASS Kernel1
{
NV_FORBID_COPY(Kernel1);
public:
NVIMAGE_API Kernel1(const Filter & f, int iscale, int samples = 32);
NVIMAGE_API ~Kernel1();
Kernel1(const Filter & f, int iscale, int samples = 32);
~Kernel1();
float valueAt(uint x) const {
nvDebugCheck(x < (uint)m_windowSize);
@ -138,7 +138,7 @@ namespace nv
return m_width;
}
NVIMAGE_API void debugPrint();
void debugPrint();
private:
int m_windowSize;
@ -148,15 +148,15 @@ namespace nv
/// A 2D kernel.
class Kernel2
class NVIMAGE_CLASS Kernel2
{
public:
NVIMAGE_API Kernel2(uint width);
NVIMAGE_API Kernel2(const Kernel2 & k);
NVIMAGE_API ~Kernel2();
Kernel2(uint width);
Kernel2(const Kernel2 & k);
~Kernel2();
NVIMAGE_API void normalize();
NVIMAGE_API void transpose();
void normalize();
void transpose();
float valueAt(uint x, uint y) const {
return m_data[y * m_windowSize + x];
@ -166,12 +166,12 @@ namespace nv
return m_windowSize;
}
NVIMAGE_API void initLaplacian();
NVIMAGE_API void initEdgeDetection();
NVIMAGE_API void initSobel();
NVIMAGE_API void initPrewitt();
void initLaplacian();
void initEdgeDetection();
void initSobel();
void initPrewitt();
NVIMAGE_API void initBlendedSobel(const Vector4 & scale);
void initBlendedSobel(const Vector4 & scale);
private:
const uint m_windowSize;
@ -180,12 +180,12 @@ namespace nv
/// A 1D polyphase kernel
class PolyphaseKernel
class NVIMAGE_CLASS PolyphaseKernel
{
NV_FORBID_COPY(PolyphaseKernel);
public:
NVIMAGE_API PolyphaseKernel(const Filter & f, uint srcLength, uint dstLength, int samples = 32);
NVIMAGE_API ~PolyphaseKernel();
PolyphaseKernel(const Filter & f, uint srcLength, uint dstLength, int samples = 32);
~PolyphaseKernel();
int windowSize() const {
return m_windowSize;
@ -205,7 +205,7 @@ namespace nv
return m_data[column * m_windowSize + x];
}
NVIMAGE_API void debugPrint() const;
void debugPrint() const;
private:
int m_windowSize;

171
branches/2.0/src/nvimage/FloatImage.cpp
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@ -1,16 +1,18 @@
// This code is in the public domain -- castanyo@yahoo.es
#include <nvcore/Containers.h>
#include <nvcore/Ptr.h>
#include <nvmath/Color.h>
#include "FloatImage.h"
#include "Filter.h"
#include "Image.h"
#include <nvmath/Color.h>
#include <nvmath/Matrix.h>
#include <nvcore/Containers.h>
#include <nvcore/Ptr.h>
#include <math.h>
using namespace nv;
namespace
@ -140,7 +142,8 @@ Image * FloatImage::createImageGammaCorrect(float gamma/*= 2.2f*/) const
/// Allocate a 2d float image of the given format and the given extents.
void FloatImage::allocate(uint c, uint w, uint h)
{
nvCheck(m_mem == NULL);
free();
m_width = w;
m_height = h;
m_componentNum = c;
@ -151,7 +154,6 @@ void FloatImage::allocate(uint c, uint w, uint h)
/// Free the image, but don't clear the members.
void FloatImage::free()
{
nvCheck(m_mem != NULL);
nv::mem::free( reinterpret_cast<void *>(m_mem) );
m_mem = NULL;
}
@ -549,6 +551,15 @@ FloatImage * FloatImage::downSample(const Filter & filter, WrapMode wm) const
return resize(filter, w, h, wm);
}
/// Downsample applying a 1D kernel separately in each dimension.
FloatImage * FloatImage::downSample(const Filter & filter, WrapMode wm, uint alpha) const
{
const uint w = max(1, m_width / 2);
const uint h = max(1, m_height / 2);
return resize(filter, w, h, wm, alpha);
}
/// Downsample applying a 1D kernel separately in each dimension.
FloatImage * FloatImage::resize(const Filter & filter, uint w, uint h, WrapMode wm) const
@ -620,10 +631,56 @@ FloatImage * FloatImage::resize(const Filter & filter, uint w, uint h, WrapMode
return dst_image.release();
}
/// Downsample applying a 1D kernel separately in each dimension.
FloatImage * FloatImage::resize(const Filter & filter, uint w, uint h, WrapMode wm, uint alpha) const
{
nvCheck(alpha < m_componentNum);
AutoPtr<FloatImage> tmp_image( new FloatImage() );
AutoPtr<FloatImage> dst_image( new FloatImage() );
PolyphaseKernel xkernel(filter, m_width, w, 32);
PolyphaseKernel ykernel(filter, m_height, h, 32);
{
tmp_image->allocate(m_componentNum, w, m_height);
dst_image->allocate(m_componentNum, w, h);
Array<float> tmp_column(h);
tmp_column.resize(h);
for (uint c = 0; c < m_componentNum; c++)
{
float * tmp_channel = tmp_image->channel(c);
for (uint y = 0; y < m_height; y++) {
this->applyKernelHorizontal(xkernel, y, c, alpha, wm, tmp_channel + y * w);
}
}
// Process all channels before applying vertical kernel to make sure alpha has been computed.
for (uint c = 0; c < m_componentNum; c++)
{
float * dst_channel = dst_image->channel(c);
for (uint x = 0; x < w; x++) {
tmp_image->applyKernelVertical(ykernel, x, c, alpha, wm, tmp_column.unsecureBuffer());
for (uint y = 0; y < h; y++) {
dst_channel[y * w + x] = tmp_column[y];
}
}
}
}
return dst_image.release();
}
/// Apply 2D kernel at the given coordinates and return result.
float FloatImage::applyKernel(const Kernel2 * k, int x, int y, int c, WrapMode wm) const
float FloatImage::applyKernel(const Kernel2 * k, int x, int y, uint c, WrapMode wm) const
{
nvDebugCheck(k != NULL);
@ -652,7 +709,7 @@ float FloatImage::applyKernel(const Kernel2 * k, int x, int y, int c, WrapMode w
/// Apply 1D vertical kernel at the given coordinates and return result.
float FloatImage::applyKernelVertical(const Kernel1 * k, int x, int y, int c, WrapMode wm) const
float FloatImage::applyKernelVertical(const Kernel1 * k, int x, int y, uint c, WrapMode wm) const
{
nvDebugCheck(k != NULL);
@ -674,7 +731,7 @@ float FloatImage::applyKernelVertical(const Kernel1 * k, int x, int y, int c, Wr
}
/// Apply 1D horizontal kernel at the given coordinates and return result.
float FloatImage::applyKernelHorizontal(const Kernel1 * k, int x, int y, int c, WrapMode wm) const
float FloatImage::applyKernelHorizontal(const Kernel1 * k, int x, int y, uint c, WrapMode wm) const
{
nvDebugCheck(k != NULL);
@ -697,7 +754,7 @@ float FloatImage::applyKernelHorizontal(const Kernel1 * k, int x, int y, int c,
/// Apply 1D vertical kernel at the given coordinates and return result.
void FloatImage::applyKernelVertical(const PolyphaseKernel & k, int x, int c, WrapMode wm, float * output) const
void FloatImage::applyKernelVertical(const PolyphaseKernel & k, int x, uint c, WrapMode wm, float * __restrict output) const
{
const uint length = k.length();
const float scale = float(length) / float(m_height);
@ -729,7 +786,7 @@ void FloatImage::applyKernelVertical(const PolyphaseKernel & k, int x, int c, Wr
}
/// Apply 1D horizontal kernel at the given coordinates and return result.
void FloatImage::applyKernelHorizontal(const PolyphaseKernel & k, int y, int c, WrapMode wm, float * output) const
void FloatImage::applyKernelHorizontal(const PolyphaseKernel & k, int y, uint c, WrapMode wm, float * __restrict output) const
{
const uint length = k.length();
const float scale = float(length) / float(m_width);
@ -760,3 +817,93 @@ void FloatImage::applyKernelHorizontal(const PolyphaseKernel & k, int y, int c,
}
}
/// Apply 1D vertical kernel at the given coordinates and return result.
void FloatImage::applyKernelVertical(const PolyphaseKernel & k, int x, uint c, uint a, WrapMode wm, float * __restrict output) const
{
const uint length = k.length();
const float scale = float(length) / float(m_height);
const float iscale = 1.0f / scale;
const float width = k.width();
const int windowSize = k.windowSize();
const float * channel = this->channel(c);
const float * alpha = this->channel(a);
for (uint i = 0; i < length; i++)
{
const float center = (0.5f + i) * iscale;
const int left = (int)floorf(center - width);
const int right = (int)ceilf(center + width);
nvCheck(right - left <= windowSize);
float norm = 0;
float sum = 0;
for (int j = 0; j < windowSize; ++j)
{
const int idx = this->index(x, j+left, wm);
float w = k.valueAt(i, j) * (alpha[idx] + (1.0f / 256.0f));
norm += w;
sum += w * channel[idx];
}
output[i] = sum / norm;
}
}
/// Apply 1D horizontal kernel at the given coordinates and return result.
void FloatImage::applyKernelHorizontal(const PolyphaseKernel & k, int y, uint c, uint a, WrapMode wm, float * __restrict output) const
{
const uint length = k.length();
const float scale = float(length) / float(m_width);
const float iscale = 1.0f / scale;
const float width = k.width();
const int windowSize = k.windowSize();
const float * channel = this->channel(c);
const float * alpha = this->channel(a);
for (uint i = 0; i < length; i++)
{
const float center = (0.5f + i) * iscale;
const int left = (int)floorf(center - width);
const int right = (int)ceilf(center + width);
nvDebugCheck(right - left <= windowSize);
float norm = 0.0f;
float sum = 0;
for (int j = 0; j < windowSize; ++j)
{
const int idx = this->index(left + j, y, wm);
float w = k.valueAt(i, j) * (alpha[idx] + (1.0f / 256.0f));
norm += w;
sum += w * channel[idx];
}
output[i] = sum / norm;
}
}
FloatImage* FloatImage::clone() const
{
FloatImage* copy = new FloatImage();
copy->m_width = m_width;
copy->m_height = m_height;
copy->m_componentNum = m_componentNum;
copy->m_count = m_count;
if(m_mem)
{
copy->allocate(m_componentNum, m_width, m_height);
memcpy(copy->m_mem, m_mem, m_count * sizeof(float));
}
return copy;
}

33
branches/2.0/src/nvimage/FloatImage.h
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@ -3,12 +3,20 @@
#ifndef NV_IMAGE_FLOATIMAGE_H
#define NV_IMAGE_FLOATIMAGE_H
#include <nvimage/nvimage.h>
#include <nvmath/Vector.h>
#include <nvcore/Debug.h>
#include <nvcore/Containers.h> // clamp
#include <nvimage/nvimage.h>
#include <stdlib.h> // abs
namespace nv
{
class Vector4;
class Matrix;
class Image;
class Filter;
class Kernel1;
@ -60,20 +68,22 @@ public:
NVIMAGE_API void toGamma(uint base_component, uint num, float gamma = 2.2f);
NVIMAGE_API void exponentiate(uint base_component, uint num, float power);
NVIMAGE_API FloatImage * fastDownSample() const;
NVIMAGE_API FloatImage * downSample(const Filter & filter, WrapMode wm) const;
NVIMAGE_API FloatImage * downSample(const Filter & filter, WrapMode wm, uint alpha) const;
NVIMAGE_API FloatImage * resize(const Filter & filter, uint w, uint h, WrapMode wm) const;
//NVIMAGE_API FloatImage * downSample(const Kernel1 & filter, WrapMode wm) const;
//NVIMAGE_API FloatImage * downSample(const Kernel1 & filter, uint w, uint h, WrapMode wm) const;
NVIMAGE_API FloatImage * resize(const Filter & filter, uint w, uint h, WrapMode wm, uint alpha) const;
//@}
NVIMAGE_API float applyKernel(const Kernel2 * k, int x, int y, int c, WrapMode wm) const;
NVIMAGE_API float applyKernelVertical(const Kernel1 * k, int x, int y, int c, WrapMode wm) const;
NVIMAGE_API float applyKernelHorizontal(const Kernel1 * k, int x, int y, int c, WrapMode wm) const;
NVIMAGE_API void applyKernelVertical(const PolyphaseKernel & k, int x, int c, WrapMode wm, float * output) const;
NVIMAGE_API void applyKernelHorizontal(const PolyphaseKernel & k, int y, int c, WrapMode wm, float * output) const;
NVIMAGE_API float applyKernel(const Kernel2 * k, int x, int y, uint c, WrapMode wm) const;
NVIMAGE_API float applyKernelVertical(const Kernel1 * k, int x, int y, uint c, WrapMode wm) const;
NVIMAGE_API float applyKernelHorizontal(const Kernel1 * k, int x, int y, uint c, WrapMode wm) const;
NVIMAGE_API void applyKernelVertical(const PolyphaseKernel & k, int x, uint c, WrapMode wm, float * output) const;
NVIMAGE_API void applyKernelHorizontal(const PolyphaseKernel & k, int y, uint c, WrapMode wm, float * output) const;
NVIMAGE_API void applyKernelVertical(const PolyphaseKernel & k, int x, uint c, uint a, WrapMode wm, float * output) const;
NVIMAGE_API void applyKernelHorizontal(const PolyphaseKernel & k, int y, uint c, uint a, WrapMode wm, float * output) const;
uint width() const { return m_width; }
@ -109,6 +119,9 @@ public:
float sampleLinearMirror(float x, float y, int c) const;
//@}
FloatImage* clone() const;
public:
uint index(uint x, uint y) const;
@ -234,7 +247,7 @@ inline uint FloatImage::indexMirror(int x, int y) const
}
if (m_height == 1) y = 0;
y = abs(y);
while (y >= m_height) {
y = abs(m_height + m_height - y - 2);

9
branches/2.0/src/nvimage/NormalMap.cpp
View File

@ -21,15 +21,16 @@
// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
// OTHER DEALINGS IN THE SOFTWARE.
#include <nvcore/Ptr.h>
#include <nvmath/Color.h>
#include <nvimage/NormalMap.h>
#include <nvimage/Filter.h>
#include <nvimage/FloatImage.h>
#include <nvimage/Image.h>
#include <nvmath/Color.h>
#include <nvcore/Ptr.h>
using namespace nv;
// Create normal map using the given kernels.

2
branches/2.0/src/nvimage/PsdFile.h
View File

@ -39,7 +39,7 @@ namespace nv
bool isSupported() const
{
if (version != 1) {
printf("*** bad version number %u\n", version);
nvDebug("*** bad version number %u\n", version);
return false;
}
if (channel_count > 4) {

155
branches/2.0/src/nvimage/Quantize.cpp
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@ -12,11 +12,14 @@ http://www.efg2.com/Lab/Library/ImageProcessing/DHALF.TXT
@@ This code needs to be reviewed, I'm not sure it's correct.
*/
#include <nvimage/Quantize.h>
#include <nvimage/Image.h>
#include <nvimage/PixelFormat.h>
#include <nvmath/Color.h>
#include <nvimage/Image.h>
#include <nvimage/Quantize.h>
#include <nvimage/PixelFormat.h>
#include <nvcore/Containers.h> // swap
using namespace nv;
@ -133,17 +136,17 @@ void nv::Quantize::Truncate(Image * image, uint rsize, uint gsize, uint bsize, u
Color32 pixel = image->pixel(x, y);
// Convert to our desired size, and reconstruct.
pixel.r = PixelFormat::convert(pixel.r, 8, rsize);
pixel.r = PixelFormat::convert(pixel.r, rsize, 8);
pixel.g = PixelFormat::convert(pixel.g, 8, gsize);
pixel.g = PixelFormat::convert(pixel.g, gsize, 8);
pixel.b = PixelFormat::convert(pixel.b, 8, bsize);
pixel.b = PixelFormat::convert(pixel.b, bsize, 8);
pixel.a = PixelFormat::convert(pixel.a, 8, asize);
pixel.a = PixelFormat::convert(pixel.a, asize, 8);
pixel.r = PixelFormat::convert(pixel.r, 8, rsize);
pixel.r = PixelFormat::convert(pixel.r, rsize, 8);
pixel.g = PixelFormat::convert(pixel.g, 8, gsize);
pixel.g = PixelFormat::convert(pixel.g, gsize, 8);
pixel.b = PixelFormat::convert(pixel.b, 8, bsize);
pixel.b = PixelFormat::convert(pixel.b, bsize, 8);
pixel.a = PixelFormat::convert(pixel.a, 8, asize);
pixel.a = PixelFormat::convert(pixel.a, asize, 8);
// Store color.
image->pixel(x, y) = pixel;
@ -152,65 +155,65 @@ void nv::Quantize::Truncate(Image * image, uint rsize, uint gsize, uint bsize, u
}
// Error diffusion. Floyd Steinberg.
void nv::Quantize::FloydSteinberg(Image * image, uint rsize, uint gsize, uint bsize, uint asize)
{
nvCheck(image != NULL);
const uint w = image->width();
const uint h = image->height();
Vector4 * row0 = new Vector4[w+2];
Vector4 * row1 = new Vector4[w+2];
memset(row0, 0, sizeof(Vector4)*(w+2));
memset(row1, 0, sizeof(Vector4)*(w+2));
for (uint y = 0; y < h; y++) {
for (uint x = 0; x < w; x++) {
Color32 pixel = image->pixel(x, y);
// Add error.
pixel.r = clamp(int(pixel.r) + int(row0[1+x].x()), 0, 255);
pixel.g = clamp(int(pixel.g) + int(row0[1+x].y()), 0, 255);
pixel.b = clamp(int(pixel.b) + int(row0[1+x].z()), 0, 255);
pixel.a = clamp(int(pixel.a) + int(row0[1+x].w()), 0, 255);
int r = pixel.r;
int g = pixel.g;
int b = pixel.b;
int a = pixel.a;
// Convert to our desired size, and reconstruct.
r = PixelFormat::convert(r, 8, rsize);
r = PixelFormat::convert(r, rsize, 8);
g = PixelFormat::convert(g, 8, gsize);
g = PixelFormat::convert(g, gsize, 8);
b = PixelFormat::convert(b, 8, bsize);
b = PixelFormat::convert(b, bsize, 8);
a = PixelFormat::convert(a, 8, asize);
a = PixelFormat::convert(a, asize, 8);
// Store color.
image->pixel(x, y) = Color32(r, g, b, a);
// Compute new error.
Vector4 diff(float(int(pixel.r) - r), float(int(pixel.g) - g), float(int(pixel.b) - b), float(int(pixel.a) - a));
// Propagate new error.
row0[1+x+1] += 7.0f / 16.0f * diff;
row1[1+x-1] += 3.0f / 16.0f * diff;
row1[1+x+0] += 5.0f / 16.0f * diff;
row1[1+x+1] += 1.0f / 16.0f * diff;
}
swap(row0, row1);
memset(row1, 0, sizeof(Vector4)*(w+2));
}
delete [] row0;
delete [] row1;
}
// Error diffusion. Floyd Steinberg.
void nv::Quantize::FloydSteinberg(Image * image, uint rsize, uint gsize, uint bsize, uint asize)
{
nvCheck(image != NULL);
const uint w = image->width();
const uint h = image->height();
Vector4 * row0 = new Vector4[w+2];
Vector4 * row1 = new Vector4[w+2];
memset(row0, 0, sizeof(Vector4)*(w+2));
memset(row1, 0, sizeof(Vector4)*(w+2));
for (uint y = 0; y < h; y++) {
for (uint x = 0; x < w; x++) {
Color32 pixel = image->pixel(x, y);
// Add error.
pixel.r = clamp(int(pixel.r) + int(row0[1+x].x()), 0, 255);
pixel.g = clamp(int(pixel.g) + int(row0[1+x].y()), 0, 255);
pixel.b = clamp(int(pixel.b) + int(row0[1+x].z()), 0, 255);
pixel.a = clamp(int(pixel.a) + int(row0[1+x].w()), 0, 255);
int r = pixel.r;
int g = pixel.g;
int b = pixel.b;
int a = pixel.a;
// Convert to our desired size, and reconstruct.
r = PixelFormat::convert(r, 8, rsize);
r = PixelFormat::convert(r, rsize, 8);
g = PixelFormat::convert(g, 8, gsize);
g = PixelFormat::convert(g, gsize, 8);
b = PixelFormat::convert(b, 8, bsize);
b = PixelFormat::convert(b, bsize, 8);
a = PixelFormat::convert(a, 8, asize);
a = PixelFormat::convert(a, asize, 8);
// Store color.
image->pixel(x, y) = Color32(r, g, b, a);
// Compute new error.
Vector4 diff(float(int(pixel.r) - r), float(int(pixel.g) - g), float(int(pixel.b) - b), float(int(pixel.a) - a));
// Propagate new error.
row0[1+x+1] += 7.0f / 16.0f * diff;
row1[1+x-1] += 3.0f / 16.0f * diff;
row1[1+x+0] += 5.0f / 16.0f * diff;
row1[1+x+1] += 1.0f / 16.0f * diff;
}
swap(row0, row1);
memset(row1, 0, sizeof(Vector4)*(w+2));
}
delete [] row0;
delete [] row1;
}

3
branches/2.0/src/nvimage/Quantize.h
View File

@ -3,6 +3,9 @@
#ifndef NV_IMAGE_QUANTIZE_H
#define NV_IMAGE_QUANTIZE_H
#include <nvimage/nvimage.h>
namespace nv
{
class Image;

35
branches/2.0/src/nvmath/nvmath.h
View File

@ -48,19 +48,37 @@
#define IS_NEGATIVE_FLOAT(x) (IR(x)&SIGN_BITMASK)
*/
inline float sqrt_assert(const float f)
inline double sqrt_assert(const double f)
{
nvDebugCheck(f >= 0.0f);
return sqrt(f);
}
inline float sqrtf_assert(const float f)
{
nvDebugCheck(f >= 0.0f);
return sqrtf(f);
}
inline float acos_assert(const float f)
inline double acos_assert(const double f)
{
nvDebugCheck(f >= -1.0f && f <= 1.0f);
return acos(f);
}
inline float acosf_assert(const float f)
{
nvDebugCheck(f >= -1.0f && f <= 1.0f);
return acosf(f);
}
inline float asin_assert(const float f)
inline double asin_assert(const double f)
{
nvDebugCheck(f >= -1.0f && f <= 1.0f);
return asin(f);
}
inline float asinf_assert(const float f)
{
nvDebugCheck(f >= -1.0f && f <= 1.0f);
return asinf(f);
@ -68,11 +86,11 @@ inline float asin_assert(const float f)
// Replace default functions with asserting ones.
#define sqrt sqrt_assert
#define sqrtf sqrt_assert
#define sqrtf sqrtf_assert
#define acos acos_assert
#define acosf acos_assert
#define acosf acosf_assert
#define asin asin_assert
#define asinf asin_assert
#define asinf asinf_assert
#if NV_OS_WIN32
#include <float.h>
@ -136,6 +154,11 @@ inline float lerp(float f0, float f1, float t)
return f0 * s + f1 * t;
}
inline float square(float f)
{
return f * f;
}
} // nv
#endif // NV_MATH_H

9
branches/2.0/src/nvtt/Compressor.cpp
View File

@ -697,6 +697,7 @@ bool Compressor::Private::compressMipmap(const Mipmap & mipmap, const InputOptio
SlowCompressor slow;
slow.setImage(image, inputOptions.alphaMode);
const bool useCuda = cudaEnabled && image->width() * image->height() >= 512;
if (compressionOptions.format == Format_RGBA || compressionOptions.format == Format_RGB)
{
@ -725,7 +726,7 @@ bool Compressor::Private::compressMipmap(const Mipmap & mipmap, const InputOptio
}
else
{
if (cudaEnabled)
if (useCuda)
{
nvDebugCheck(cudaSupported);
cuda->setImage(image, inputOptions.alphaMode);
@ -745,7 +746,7 @@ bool Compressor::Private::compressMipmap(const Mipmap & mipmap, const InputOptio
}
else
{
if (cudaEnabled)
if (useCuda)
{
nvDebugCheck(cudaSupported);
/*cuda*/slow.compressDXT1a(compressionOptions, outputOptions);
@ -764,7 +765,7 @@ bool Compressor::Private::compressMipmap(const Mipmap & mipmap, const InputOptio
}
else
{
if (cudaEnabled)
if (useCuda)
{
nvDebugCheck(cudaSupported);
cuda->setImage(image, inputOptions.alphaMode);
@ -784,7 +785,7 @@ bool Compressor::Private::compressMipmap(const Mipmap & mipmap, const InputOptio
}
else
{
if (cudaEnabled)
if (useCuda)
{
nvDebugCheck(cudaSupported);
cuda->setImage(image, inputOptions.alphaMode);

2
branches/2.0/src/nvtt/cuda/CudaMath.h
View File

@ -148,7 +148,7 @@ inline __device__ bool singleColor(const float3 * colors)
bool sameColor = false;
for (int i = 0; i < 16; i++)
{
sameColor &= (colors[idx] == colors[0]);
sameColor &= (colors[i] == colors[0]);
}
return sameColor;
#else

27
branches/2.0/src/nvtt/cuda/CudaUtils.cpp
View File

@ -26,12 +26,14 @@
#include "CudaUtils.h"
#if defined HAVE_CUDA
#include <cuda_runtime.h>
#include <cuda.h>
#include <cuda_runtime_api.h>
#endif
using namespace nv;
using namespace cuda;
/* @@ Move this to win32 utils or somewhere else.
#if NV_OS_WIN32
#define WINDOWS_LEAN_AND_MEAN
@ -68,10 +70,12 @@ static bool isWow32()
}
#endif
*/
static bool isCudaDriverAvailable(uint version)
static bool isCudaDriverAvailable(int version)
{
#if defined HAVE_CUDA
#if NV_OS_WIN32
Library nvcuda("nvcuda.dll");
#else
@ -95,7 +99,21 @@ static bool isCudaDriverAvailable(uint version)
if (address == NULL) return false;
}
return true;
if (version >= 2020)
{
typedef CUresult (CUDAAPI * PFCU_DRIVERGETVERSION)(int * version);
PFCU_DRIVERGETVERSION driverGetVersion = (PFCU_DRIVERGETVERSION)nvcuda.bindSymbol("cuDriverGetVersion");
if (driverGetVersion == NULL) return false;
int driverVersion;
if (driverGetVersion(&driverVersion) != CUDA_SUCCESS) return false;
return driverVersion >= version;
}
#endif // HAVE_CUDA
return false;
}
@ -154,7 +172,7 @@ int nv::cuda::deviceCount()
int nv::cuda::getFastestDevice()
{
int max_gflops_device = 0;
#if defined HAVE_CUDA
#if defined HAVE_CUDA
int max_gflops = 0;
const int device_count = deviceCount();
@ -180,6 +198,7 @@ int nv::cuda::getFastestDevice()
return max_gflops_device;
}
/// Activate the given devices.
bool nv::cuda::setDevice(int i)
{