static bool
circular_shift_ (ImageBuf &dst, const ImageBuf &src,
int xshift, int yshift, int zshift,
ROI dstroi, ROI roi, int nthreads)
{
if (nthreads != 1 && roi.npixels() >= 1000) {
// Possible multiple thread case -- recurse via parallel_image
ImageBufAlgo::parallel_image (
boost::bind(circular_shift_<DSTTYPE,SRCTYPE>,
boost::ref(dst), boost::cref(src),
xshift, yshift, zshift,
dstroi, _1 /*roi*/, 1 /*nthreads*/),
roi, nthreads);
return true;
}
// Serial case
int width = dstroi.width(), height = dstroi.height(), depth = dstroi.depth();
ImageBuf::ConstIterator<SRCTYPE,DSTTYPE> s (src, roi);
ImageBuf::Iterator<DSTTYPE,DSTTYPE> d (dst);
for ( ; ! s.done(); ++s) {
int dx = s.x() + xshift; OIIO::wrap_periodic (dx, dstroi.xbegin, width);
int dy = s.y() + yshift; OIIO::wrap_periodic (dy, dstroi.ybegin, height);
int dz = s.z() + zshift; OIIO::wrap_periodic (dz, dstroi.zbegin, depth);
d.pos (dx, dy, dz);
if (! d.exists())
continue;
for (int c = roi.chbegin; c < roi.chend; ++c)
d[c] = s[c];
}
return true;
}
static bool
transpose_ (ImageBuf &dst, const ImageBuf &src,
ROI roi, int nthreads)
{
if (nthreads != 1 && roi.npixels() >= 1000) {
// Possible multiple thread case -- recurse via parallel_image
ImageBufAlgo::parallel_image (
boost::bind(transpose_<DSTTYPE,SRCTYPE>,
boost::ref(dst), boost::cref(src),
_1 /*roi*/, 1 /*nthreads*/),
roi, nthreads);
return true;
}
// Serial case
ImageBuf::ConstIterator<SRCTYPE,DSTTYPE> s (src, roi);
ImageBuf::Iterator<DSTTYPE,DSTTYPE> d (dst);
for ( ; ! s.done(); ++s) {
d.pos (s.y(), s.x(), s.z());
if (! d.exists())
continue;
for (int c = roi.chbegin; c < roi.chend; ++c)
d[c] = s[c];
}
return true;
}
inline void
compare_value (ImageBuf::ConstIterator<BUFT,float> &a, int chan,
float aval, float bval, ImageBufAlgo::CompareResults &result,
float &maxval, double &batcherror, double &batch_sqrerror,
bool &failed, bool &warned, float failthresh, float warnthresh)
{
maxval = std::max (maxval, std::max (aval, bval));
double f = fabs (aval - bval);
batcherror += f;
batch_sqrerror += f*f;
if (f > result.maxerror) {
result.maxerror = f;
result.maxx = a.x();
result.maxy = a.y();
result.maxz = a.z();
result.maxc = chan;
}
if (! warned && f > warnthresh) {
++result.nwarn;
warned = true;
}
if (! failed && f > failthresh) {
++result.nfail;
failed = true;
}
}
inline void
compare_value (ImageBuf::ConstIterator<BUFT,float> &a, int chan,
float aval, float bval, ImageBufAlgo::CompareResults &result,
float &maxval, double &batcherror, double &batch_sqrerror,
bool &failed, bool &warned, float failthresh, float warnthresh)
{
if (!isfinite(aval) || !isfinite(bval)) {
if (isnan(aval) == isnan(bval) && isinf(aval) == isinf(bval))
return; // NaN may match NaN, Inf may match Inf
if (isfinite(result.maxerror)) {
// non-finite errors trump finite ones
result.maxerror = std::numeric_limits<float>::infinity();
result.maxx = a.x();
result.maxy = a.y();
result.maxz = a.z();
result.maxc = chan;
return;
}
}
maxval = std::max (maxval, std::max (aval, bval));
double f = fabs (aval - bval);
batcherror += f;
batch_sqrerror += f*f;
// We use the awkward '!(a<=threshold)' construct so that we have
// failures when f is a NaN (since all comparisons involving NaN will
// return false).
if (!(f <= result.maxerror)) {
result.maxerror = f;
result.maxx = a.x();
result.maxy = a.y();
result.maxz = a.z();
result.maxc = chan;
}
if (! warned && !(f <= warnthresh)) {
++result.nwarn;
warned = true;
}
if (! failed && !(f <= failthresh)) {
++result.nfail;
failed = true;
}
}
static inline void
copy_pixels_ (const ImageBuf &buf, int xbegin, int xend,
int ybegin, int yend, D *r)
{
int w = (xend-xbegin);
for (ImageBuf::ConstIterator<S,D> p (buf, xbegin, xend, ybegin, yend);
p.valid(); ++p) {
imagesize_t offset = ((p.y()-ybegin)*w + (p.x()-xbegin)) * buf.nchannels();
for (int c = 0; c < buf.nchannels(); ++c)
r[offset+c] = p[c];
}
}
static bool
convolve_ (ImageBuf &dst, const ImageBuf &src, const ImageBuf &kernel,
bool normalize, ROI roi, int nthreads)
{
if (nthreads != 1 && roi.npixels() >= 1000) {
// Lots of pixels and request for multi threads? Parallelize.
ImageBufAlgo::parallel_image (
boost::bind(convolve_<DSTTYPE,SRCTYPE>, boost::ref(dst),
boost::cref(src), boost::cref(kernel), normalize,
_1 /*roi*/, 1 /*nthreads*/),
roi, nthreads);
return true;
}
// Serial case
float scale = 1.0f;
if (normalize) {
scale = 0.0f;
for (ImageBuf::ConstIterator<float> k (kernel); ! k.done(); ++k)
scale += k[0];
scale = 1.0f / scale;
}
float *sum = ALLOCA (float, roi.chend);
ROI kroi = get_roi (kernel.spec());
ImageBuf::Iterator<DSTTYPE> d (dst, roi);
ImageBuf::ConstIterator<SRCTYPE> s (src, roi, ImageBuf::WrapClamp);
for ( ; ! d.done(); ++d) {
for (int c = roi.chbegin; c < roi.chend; ++c)
sum[c] = 0.0f;
for (ImageBuf::ConstIterator<float> k (kernel, kroi); !k.done(); ++k) {
float kval = k[0];
s.pos (d.x() + k.x(), d.y() + k.y(), d.z() + k.z());
for (int c = roi.chbegin; c < roi.chend; ++c)
sum[c] += kval * s[c];
}
for (int c = roi.chbegin; c < roi.chend; ++c)
d[c] = scale * sum[c];
}
return true;
}
static bool
transpose_ (ImageBuf &dst, const ImageBuf &src,
ROI roi, int nthreads)
{
ImageBufAlgo::parallel_image (roi, nthreads, [&](ROI roi){
ImageBuf::ConstIterator<SRCTYPE,DSTTYPE> s (src, roi);
ImageBuf::Iterator<DSTTYPE,DSTTYPE> d (dst);
for ( ; ! s.done(); ++s) {
d.pos (s.y(), s.x(), s.z());
if (! d.exists())
continue;
for (int c = roi.chbegin; c < roi.chend; ++c)
d[c] = s[c];
}
});
return true;
}
static inline void
get_pixel_channels_ (const ImageBuf &buf, int xbegin, int xend,
int ybegin, int yend, int zbegin, int zend,
int chbegin, int chend, D *r,
stride_t xstride, stride_t ystride, stride_t zstride)
{
int w = (xend-xbegin), h = (yend-ybegin);
int nchans = chend - chbegin;
ImageSpec::auto_stride (xstride, ystride, zstride, sizeof(D), nchans, w, h);
for (ImageBuf::ConstIterator<S,D> p (buf, xbegin, xend, ybegin, yend, zbegin, zend);
!p.done(); ++p) {
imagesize_t offset = (p.z()-zbegin)*zstride + (p.y()-ybegin)*ystride
+ (p.x()-xbegin)*xstride;
D *rc = (D *)((char *)r + offset);
for (int c = 0; c < nchans; ++c)
rc[c] = p[c+chbegin];
}
}
// DEPRECATED version
bool
ImageBufAlgo::add (ImageBuf &dst, const ImageBuf &A, const ImageBuf &B,
int options)
{
// Sanity checks
// dst must be distinct from A and B
if ((const void *)&A == (const void *)&dst ||
(const void *)&B == (const void *)&dst) {
dst.error ("destination image must be distinct from source");
return false;
}
// all three images must have the same number of channels
if (A.spec().nchannels != B.spec().nchannels) {
dst.error ("channel number mismatch: %d vs. %d",
A.spec().nchannels, B.spec().nchannels);
return false;
}
// If dst has not already been allocated, set it to the right size,
// make it unconditinally float
if (! dst.pixels_valid()) {
ImageSpec dstspec = A.spec();
dstspec.set_format (TypeDesc::TypeFloat);
dst.alloc (dstspec);
}
// Clear dst pixels if instructed to do so
if (options & ADD_CLEAR_DST) {
zero (dst);
}
ASSERT (A.spec().format == TypeDesc::FLOAT &&
B.spec().format == TypeDesc::FLOAT &&
dst.spec().format == TypeDesc::FLOAT);
ImageBuf::ConstIterator<float,float> a (A);
ImageBuf::ConstIterator<float,float> b (B);
ImageBuf::Iterator<float> d (dst);
int nchannels = A.nchannels();
// Loop over all pixels in A
for ( ; a.valid(); ++a) {
// Point the iterators for B and dst to the corresponding pixel
if (options & ADD_RETAIN_WINDOWS) {
b.pos (a.x(), a.y());
} else {
// ADD_ALIGN_WINDOWS: make B line up with A
b.pos (a.x()-A.xbegin()+B.xbegin(), a.y()-A.ybegin()+B.ybegin());
}
d.pos (a.x(), b.y());
if (! b.valid() || ! d.valid())
continue; // Skip pixels that don't align
// Add the pixel
for (int c = 0; c < nchannels; ++c)
d[c] = a[c] + b[c];
}
return true;
}
void
IvImage::pixel_transform(bool srgb_to_linear, int color_mode, int select_channel)
{
/// This table obeys the following function:
///
/// unsigned char srgb2linear(unsigned char x)
/// {
/// float x_f = x/255.0;
/// float x_l = 0.0;
/// if (x_f <= 0.04045)
/// x_l = x_f/12.92;
/// else
/// x_l = powf((x_f+0.055)/1.055,2.4);
/// return (unsigned char)(x_l * 255 + 0.5)
/// }
///
/// It's used to transform from sRGB color space to linear color space.
static const unsigned char srgb_to_linear_lut[256] = {
0, 0, 0, 0, 0, 0, 0, 1,
1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 2, 2, 2, 2, 2, 2,
2, 2, 3, 3, 3, 3, 3, 3,
4, 4, 4, 4, 4, 5, 5, 5,
5, 6, 6, 6, 6, 7, 7, 7,
8, 8, 8, 8, 9, 9, 9, 10,
10, 10, 11, 11, 12, 12, 12, 13,
13, 13, 14, 14, 15, 15, 16, 16,
17, 17, 17, 18, 18, 19, 19, 20,
20, 21, 22, 22, 23, 23, 24, 24,
25, 25, 26, 27, 27, 28, 29, 29,
30, 30, 31, 32, 32, 33, 34, 35,
35, 36, 37, 37, 38, 39, 40, 41,
41, 42, 43, 44, 45, 45, 46, 47,
48, 49, 50, 51, 51, 52, 53, 54,
55, 56, 57, 58, 59, 60, 61, 62,
63, 64, 65, 66, 67, 68, 69, 70,
71, 72, 73, 74, 76, 77, 78, 79,
80, 81, 82, 84, 85, 86, 87, 88,
90, 91, 92, 93, 95, 96, 97, 99,
100, 101, 103, 104, 105, 107, 108, 109,
111, 112, 114, 115, 116, 118, 119, 121,
122, 124, 125, 127, 128, 130, 131, 133,
134, 136, 138, 139, 141, 142, 144, 146,
147, 149, 151, 152, 154, 156, 157, 159,
161, 163, 164, 166, 168, 170, 171, 173,
175, 177, 179, 181, 183, 184, 186, 188,
190, 192, 194, 196, 198, 200, 202, 204,
206, 208, 210, 212, 214, 216, 218, 220,
222, 224, 226, 229, 231, 233, 235, 237,
239, 242, 244, 246, 248, 250, 253, 255
};
unsigned char correction_table[256];
int total_channels = spec().nchannels;
int color_channels = spec().nchannels;
int max_channels = m_corrected_image.nchannels();
// FIXME: Now with the iterator and data proxy in place, it should be
// trivial to apply the transformations to any kind of data, not just
// UINT8.
if (spec().format != TypeDesc::UINT8 || ! m_corrected_image.localpixels()) {
return;
}
if (color_channels > 3) {
color_channels = 3;
} else if (color_channels == 2) {
color_channels = 1;
}
// This image is Luminance or Luminance + Alpha, and we are asked to show
// luminance.
if (color_channels == 1 && color_mode == 3) {
color_mode = 0; // Just copy as usual.
}
// Happy path:
if (! srgb_to_linear && color_mode <= 1 && m_gamma == 1.0 && m_exposure == 0.0) {
ImageBuf::ConstIterator<unsigned char, unsigned char> src (*this);
ImageBuf::Iterator<unsigned char, unsigned char> dst (m_corrected_image);
for ( ; src.valid (); ++src) {
dst.pos (src.x(), src.y());
for (int i = 0; i < max_channels; i++)
dst[i] = src[i];
}
return;
}
// fill the correction_table
if (gamma() == 1.0 && exposure() == 0.0) {
for (int pixelvalue = 0; pixelvalue < 256; ++pixelvalue) {
correction_table[pixelvalue] = pixelvalue;
}
} else {
float inv_gamma = 1.0/gamma();
float gain = powf (2.0f, exposure());
for (int pixelvalue = 0; pixelvalue < 256; ++pixelvalue) {
float pv_f = converter (pixelvalue);
pv_f = clamp (calc_exposure (pv_f, gain, inv_gamma),
0.0f, 1.0f);
correction_table[pixelvalue] = (unsigned char) (pv_f*255 + 0.5);
}
}
ImageBuf::ConstIterator<unsigned char, unsigned char> src (*this);
ImageBuf::Iterator<unsigned char, unsigned char> dst (m_corrected_image);
for ( ; src.valid(); ++src) {
dst.pos (src.x(), src.y());
if (color_mode == 0 || color_mode == 1) {
// RGBA, RGB modes.
int ch = 0;
for (ch = 0; ch < color_channels; ch++) {
if (srgb_to_linear)
dst[ch] = correction_table[srgb_to_linear_lut[src[ch]]];
else
dst[ch] = correction_table[src[ch]];
}
for (; ch < max_channels; ch++) {
dst[ch] = src[ch];
}
} else if (color_mode == 3) {
// Convert RGB to luminance, (Rec. 709 luma coefficients).
float luminance;
if (srgb_to_linear) {
luminance = converter (srgb_to_linear_lut[src[0]])*0.2126f +
converter (srgb_to_linear_lut[src[1]])*0.7152f +
converter (srgb_to_linear_lut[src[2]])*0.0722f;
} else {
luminance = converter (src[0])*0.2126f +
converter (src[1])*0.7152f +
converter (src[2])*0.0722f;
}
unsigned char val = (unsigned char) (clamp (luminance, 0.0f, 1.0f) * 255.0 + 0.5);
val = correction_table[val];
dst[0] = val;
dst[1] = val;
dst[2] = val;
// Handle the rest of the channels
for (int ch = 3; ch < total_channels; ++ch) {
dst[ch] = src[ch];
}
} else { // Single channel, heatmap.
unsigned char v = 0;
if (select_channel < color_channels) {
if (srgb_to_linear)
v = correction_table[srgb_to_linear_lut[src[select_channel]]];
else
v = correction_table[src[select_channel]];
} else if (select_channel < total_channels) {
v = src[select_channel];
}
int ch = 0;
for (; ch < color_channels; ++ch) {
dst[ch] = v;
}
for (; ch < max_channels; ++ch) {
dst[ch] = src[ch];
}
}
}
}
static bool
resize_ (ImageBuf &dst, const ImageBuf &src,
Filter2D *filter, ROI roi, int nthreads)
{
if (nthreads != 1 && roi.npixels() >= 1000) {
// Lots of pixels and request for multi threads? Parallelize.
ImageBufAlgo::parallel_image (
boost::bind(resize_<DSTTYPE,SRCTYPE>, boost::ref(dst),
boost::cref(src), filter,
_1 /*roi*/, 1 /*nthreads*/),
roi, nthreads);
return true;
}
// Serial case
const ImageSpec &srcspec (src.spec());
const ImageSpec &dstspec (dst.spec());
int nchannels = dstspec.nchannels;
// Local copies of the source image window, converted to float
float srcfx = srcspec.full_x;
float srcfy = srcspec.full_y;
float srcfw = srcspec.full_width;
float srcfh = srcspec.full_height;
// Ratios of dst/src size. Values larger than 1 indicate that we
// are maximizing (enlarging the image), and thus want to smoothly
// interpolate. Values less than 1 indicate that we are minimizing
// (shrinking the image), and thus want to properly filter out the
// high frequencies.
float xratio = float(dstspec.full_width) / srcfw; // 2 upsize, 0.5 downsize
float yratio = float(dstspec.full_height) / srcfh;
float dstfx = dstspec.full_x;
float dstfy = dstspec.full_y;
float dstfw = dstspec.full_width;
float dstfh = dstspec.full_height;
float dstpixelwidth = 1.0f / dstfw;
float dstpixelheight = 1.0f / dstfh;
float *pel = ALLOCA (float, nchannels);
float filterrad = filter->width() / 2.0f;
// radi,radj is the filter radius, as an integer, in source pixels. We
// will filter the source over [x-radi, x+radi] X [y-radj,y+radj].
int radi = (int) ceilf (filterrad/xratio);
int radj = (int) ceilf (filterrad/yratio);
int xtaps = 2*radi + 1;
int ytaps = 2*radj + 1;
bool separable = filter->separable();
float *xfiltval = NULL, *yfiltval = NULL;
if (separable) {
// Allocate temp space to cache the filter weights
xfiltval = ALLOCA (float, xtaps);
yfiltval = ALLOCA (float, ytaps);
}
#if 0
std::cerr << "Resizing " << srcspec.full_width << "x" << srcspec.full_height
<< " to " << dstspec.full_width << "x" << dstspec.full_height << "\n";
std::cerr << "ratios = " << xratio << ", " << yratio << "\n";
std::cerr << "examining src filter support radius of " << radi << " x " << radj << " pixels\n";
std::cerr << "dst range " << roi << "\n";
std::cerr << "separable filter\n";
#endif
// We're going to loop over all output pixels we're interested in.
//
// (s,t) = NDC space coordinates of the output sample we are computing.
// This is the "sample point".
// (src_xf, src_xf) = source pixel space float coordinates of the
// sample we're computing. We want to compute the weighted sum
// of all the source image pixels that fall under the filter when
// centered at that location.
// (src_x, src_y) = image space integer coordinates of the floor,
// i.e., the closest pixel in the source image.
// src_xf_frac and src_yf_frac are the position within that pixel
// of our sample.
ImageBuf::Iterator<DSTTYPE> out (dst, roi);
for (int y = roi.ybegin; y < roi.yend; ++y) {
float t = (y-dstfy+0.5f)*dstpixelheight;
float src_yf = srcfy + t * srcfh;
int src_y;
float src_yf_frac = floorfrac (src_yf, &src_y);
// If using separable filters, our vertical set of filter tap
// weights will be the same for the whole scanline we're on. Just
// compute and normalize them once.
float totalweight_y = 0.0f;
if (separable) {
for (int j = 0; j < ytaps; ++j) {
float w = filter->yfilt (yratio * (j-radj-(src_yf_frac-0.5f)));
yfiltval[j] = w;
totalweight_y += w;
}
for (int i = 0; i <= ytaps; ++i)
yfiltval[i] /= totalweight_y;
}
for (int x = roi.xbegin; x < roi.xend; ++x) {
float s = (x-dstfx+0.5f)*dstpixelwidth;
float src_xf = srcfx + s * srcfw;
int src_x;
float src_xf_frac = floorfrac (src_xf, &src_x);
for (int c = 0; c < nchannels; ++c)
pel[c] = 0.0f;
if (separable) {
// Cache and normalize the horizontal filter tap weights
// just once for this (x,y) position, reuse for all vertical
// taps.
float totalweight_x = 0.0f;
for (int i = 0; i < xtaps; ++i) {
float w = filter->xfilt (xratio * (i-radi-(src_xf_frac-0.5f)));
xfiltval[i] = w;
totalweight_x += w;
}
if (totalweight_x != 0.0f) {
for (int i = 0; i < xtaps; ++i) // normalize x filter
xfiltval[i] /= totalweight_x; // weights
ImageBuf::ConstIterator<SRCTYPE> srcpel (src, src_x-radi, src_x+radi+1,
src_y-radj, src_y+radj+1,
0, 1, ImageBuf::WrapClamp);
for (int j = -radj; j <= radj; ++j) {
float wy = yfiltval[j+radj];
if (wy == 0.0f) {
// 0 weight for this y tap -- move to next line
srcpel.pos (srcpel.x(), srcpel.y()+1, srcpel.z());
continue;
}
for (int i = 0; i < xtaps; ++i, ++srcpel) {
float w = wy * xfiltval[i];
for (int c = 0; c < nchannels; ++c)
pel[c] += w * srcpel[c];
}
}
}
// Copy the pixel value (already normalized) to the output.
DASSERT (out.x() == x && out.y() == y);
if (totalweight_y == 0.0f) {
// zero it out
for (int c = 0; c < nchannels; ++c)
out[c] = 0.0f;
} else {
for (int c = 0; c < nchannels; ++c)
out[c] = pel[c];
}
} else {
// Non-separable
float totalweight = 0.0f;
ImageBuf::ConstIterator<SRCTYPE> srcpel (src, src_x-radi, src_x+radi+1,
src_y-radi, src_y+radi+1,
0, 1, ImageBuf::WrapClamp);
for (int j = -radj; j <= radj; ++j) {
for (int i = -radi; i <= radi; ++i, ++srcpel) {
float w = (*filter)(xratio * (i-(src_xf_frac-0.5f)),
yratio * (j-(src_yf_frac-0.5f)));
totalweight += w;
if (w == 0.0f)
continue;
DASSERT (! srcpel.done());
for (int c = 0; c < nchannels; ++c)
pel[c] += w * srcpel[c];
}
}
DASSERT (srcpel.done());
// Rescale pel to normalize the filter and write it to the
// output image.
DASSERT (out.x() == x && out.y() == y);
if (totalweight == 0.0f) {
// zero it out
for (int c = 0; c < nchannels; ++c)
out[c] = 0.0f;
} else {
for (int c = 0; c < nchannels; ++c)
out[c] = pel[c] / totalweight;
}
}
++out;
}
}
return true;
}