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_image.cpp
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1972 lines (1699 loc) · 54.9 KB
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/* -*- mode: c++; c-basic-offset: 4 -*- */
/* Python API mandates Python.h is included *first* */
#include "Python.h"
#include <string>
#include <iostream>
#include <fstream>
#include <cmath>
#include <cstdio>
#include "numpy/arrayobject.h"
#include "agg_color_rgba.h"
#include "agg_conv_transform.h"
#include "agg_image_accessors.h"
#include "agg_path_storage.h"
#include "agg_pixfmt_rgb.h"
#include "agg_pixfmt_rgba.h"
#include "agg_rasterizer_scanline_aa.h"
#include "agg_renderer_scanline.h"
#include "agg_rendering_buffer.h"
#include "agg_scanline_bin.h"
#include "agg_scanline_bin.h"
#include "agg_scanline_u.h"
#include "agg_span_allocator.h"
#include "agg_span_image_filter_rgb.h"
#include "agg_span_image_filter_rgba.h"
#include "agg_span_interpolator_linear.h"
#include "agg_rasterizer_sl_clip.h"
#include "util/agg_color_conv_rgb8.h"
#include "_image.h"
#include "mplutils.h"
typedef agg::pixfmt_rgba32_pre pixfmt;
typedef agg::renderer_base<pixfmt> renderer_base;
typedef agg::span_interpolator_linear<> interpolator_type;
typedef agg::rasterizer_scanline_aa<agg::rasterizer_sl_clip_dbl> rasterizer;
Image::Image() :
bufferIn(NULL), rbufIn(NULL), colsIn(0), rowsIn(0),
bufferOut(NULL), rbufOut(NULL), colsOut(0), rowsOut(0), BPP(4),
interpolation(BILINEAR), aspect(ASPECT_FREE), bg(1, 1, 1, 0), resample(true)
{
_VERBOSE("Image::Image");
}
Image::~Image()
{
_VERBOSE("Image::~Image");
delete [] bufferIn;
bufferIn = NULL;
delete rbufIn;
rbufIn = NULL;
delete rbufOut;
rbufOut = NULL;
delete [] bufferOut;
bufferOut = NULL;
}
int
Image::setattr(const char * name, const Py::Object & value)
{
_VERBOSE("Image::setattr");
__dict__[name] = value;
return 0;
}
Py::Object
Image::getattr(const char * name)
{
_VERBOSE("Image::getattro");
if (__dict__.hasKey(name)) return __dict__[name];
else return getattr_default(name);
}
char Image::apply_rotation__doc__[] =
"apply_rotation(angle)\n"
"\n"
"Apply the rotation (degrees) to image"
;
Py::Object
Image::apply_rotation(const Py::Tuple& args)
{
_VERBOSE("Image::apply_rotation");
args.verify_length(1);
double r = Py::Float(args[0]);
agg::trans_affine M = agg::trans_affine_rotation(r * agg::pi / 180.0);
srcMatrix *= M;
imageMatrix *= M;
return Py::Object();
}
char Image::flipud_out__doc__[] =
"flipud()\n"
"\n"
"Flip the output image upside down"
;
char Image::flipud_in__doc__[] =
"flipud()\n"
"\n"
"Flip the input image upside down"
;
Py::Object
Image::flipud_in(const Py::Tuple& args)
{
_VERBOSE("Image::flipud_in");
args.verify_length(0);
int stride = rbufIn->stride();
rbufIn->attach(bufferIn, colsIn, rowsIn, -stride);
return Py::Object();
}
char Image::set_bg__doc__[] =
"set_bg(r,g,b,a)\n"
"\n"
"Set the background color"
;
Py::Object
Image::set_bg(const Py::Tuple& args)
{
_VERBOSE("Image::set_bg");
args.verify_length(4);
bg.r = Py::Float(args[0]);
bg.g = Py::Float(args[1]);
bg.b = Py::Float(args[2]);
bg.a = Py::Float(args[3]);
return Py::Object();
}
char Image::apply_scaling__doc__[] =
"apply_scaling(sx, sy)\n"
"\n"
"Apply the scale factors sx, sy to the transform matrix"
;
Py::Object
Image::apply_scaling(const Py::Tuple& args)
{
_VERBOSE("Image::apply_scaling");
args.verify_length(2);
double sx = Py::Float(args[0]);
double sy = Py::Float(args[1]);
//printf("applying scaling %1.2f, %1.2f\n", sx, sy);
agg::trans_affine M = agg::trans_affine_scaling(sx, sy);
srcMatrix *= M;
imageMatrix *= M;
return Py::Object();
}
char Image::apply_translation__doc__[] =
"apply_translation(tx, ty)\n"
"\n"
"Apply the translation tx, ty to the transform matrix"
;
Py::Object
Image::apply_translation(const Py::Tuple& args)
{
_VERBOSE("Image::apply_translation");
args.verify_length(2);
double tx = Py::Float(args[0]);
double ty = Py::Float(args[1]);
//printf("applying translation %1.2f, %1.2f\n", tx, ty);
agg::trans_affine M = agg::trans_affine_translation(tx, ty);
srcMatrix *= M;
imageMatrix *= M;
return Py::Object();
}
char Image::as_rgba_str__doc__[] =
"numrows, numcols, s = as_rgba_str()"
"\n"
"Call this function after resize to get the data as string\n"
"The string is a numrows by numcols x 4 (RGBA) unsigned char buffer\n"
;
Py::Object
Image::as_rgba_str(const Py::Tuple& args, const Py::Dict& kwargs)
{
_VERBOSE("Image::as_rgba_str");
args.verify_length(0);
std::pair<agg::int8u*, bool> bufpair = _get_output_buffer();
Py::Object ret = Py::asObject(Py_BuildValue("lls#", rowsOut, colsOut,
bufpair.first, colsOut * rowsOut * 4));
if (bufpair.second) delete [] bufpair.first;
return ret;
}
char Image::color_conv__doc__[] =
"numrows, numcols, buffer = color_conv(format)"
"\n"
"format 0(BGRA) or 1(ARGB)\n"
"Convert image to format and return in a writable buffer\n"
;
Py::Object
Image::color_conv(const Py::Tuple& args)
{
_VERBOSE("Image::color_conv");
args.verify_length(1);
int format = Py::Int(args[0]);
int row_len = colsOut * 4;
PyObject* py_buffer = PyBuffer_New(row_len * rowsOut);
if (py_buffer == NULL)
throw Py::MemoryError("Image::color_conv could not allocate memory");
void* buf;
Py_ssize_t buffer_len;
int ret = PyObject_AsWriteBuffer(py_buffer, &buf, &buffer_len);
if (ret != 0)
throw Py::MemoryError("Image::color_conv could not allocate memory");
agg::rendering_buffer rtmp;
rtmp.attach(reinterpret_cast<unsigned char*>(buf), colsOut, rowsOut,
row_len);
switch (format)
{
case 0:
agg::color_conv(&rtmp, rbufOut, agg::color_conv_rgba32_to_bgra32());
break;
case 1:
agg::color_conv(&rtmp, rbufOut, agg::color_conv_rgba32_to_argb32());
break;
default:
throw Py::ValueError("Image::color_conv unknown format");
}
PyObject* o = Py_BuildValue("llN", rowsOut, colsOut, py_buffer);
return Py::asObject(o);
}
char Image::buffer_rgba__doc__[] =
"buffer = buffer_rgba()"
"\n"
"Return the image buffer as rgba32\n"
;
Py::Object
Image::buffer_rgba(const Py::Tuple& args)
{
//"Return the image object as rgba";
_VERBOSE("RendererAgg::buffer_rgba");
args.verify_length(0);
int row_len = colsOut * 4;
PyObject* o = Py_BuildValue("lls#", rowsOut, colsOut,
rbufOut, row_len * rowsOut);
return Py::asObject(o);
}
char Image::reset_matrix__doc__[] =
"reset_matrix()"
"\n"
"Reset the transformation matrix"
;
Py::Object
Image::reset_matrix(const Py::Tuple& args)
{
_VERBOSE("Image::reset_matrix");
args.verify_length(0);
srcMatrix.reset();
imageMatrix.reset();
return Py::Object();
}
char Image::get_matrix__doc__[] =
"(m11,m21,m12,m22,m13,m23) = get_matrix()\n"
"\n"
"Get the affine transformation matrix\n"
" /m11,m12,m13\\\n"
" /m21,m22,m23|\n"
" \\ 0 , 0 , 1 /"
;
Py::Object
Image::get_matrix(const Py::Tuple& args)
{
_VERBOSE("Image::get_matrix");
args.verify_length(0);
double m[6];
srcMatrix.store_to(m);
Py::Tuple ret(6);
for (int i = 0;i < 6;i++)
{
ret[i] = Py::Float(m[i]);
}
return ret;
}
char Image::resize__doc__[] =
"resize(width, height, norm=1, radius=4.0)\n"
"\n"
"Resize the image to width, height using interpolation\n"
"norm and radius are optional args for some of the filters and must be\n"
"passed as kwargs\n"
;
Py::Object
Image::resize(const Py::Tuple& args, const Py::Dict& kwargs)
{
_VERBOSE("Image::resize");
args.verify_length(2);
int norm = 1;
if (kwargs.hasKey("norm"))
{
norm = Py::Int(kwargs["norm"]);
}
double radius = 4.0;
if (kwargs.hasKey("radius"))
{
radius = Py::Float(kwargs["radius"]);
}
if (bufferIn == NULL)
{
throw Py::RuntimeError("You must first load the image");
}
int numcols = Py::Int(args[0]);
int numrows = Py::Int(args[1]);
colsOut = numcols;
rowsOut = numrows;
size_t NUMBYTES(numrows * numcols * BPP);
delete [] bufferOut;
bufferOut = new agg::int8u[NUMBYTES];
if (bufferOut == NULL) //todo: also handle allocation throw
{
throw Py::MemoryError("Image::resize could not allocate memory");
}
delete rbufOut;
rbufOut = new agg::rendering_buffer;
rbufOut->attach(bufferOut, numcols, numrows, numcols * BPP);
// init the output rendering/rasterizing stuff
pixfmt pixf(*rbufOut);
renderer_base rb(pixf);
rb.clear(bg);
rasterizer ras;
agg::scanline_u8 sl;
ras.clip_box(0, 0, numcols, numrows);
//srcMatrix *= resizingMatrix;
//imageMatrix *= resizingMatrix;
imageMatrix.invert();
interpolator_type interpolator(imageMatrix);
typedef agg::span_allocator<agg::rgba8> span_alloc_type;
span_alloc_type sa;
agg::rgba8 background(agg::rgba8(int(255*bg.r),
int(255*bg.g),
int(255*bg.b),
int(255*bg.a)));
// the image path
agg::path_storage path;
agg::rendering_buffer rbufPad;
double x0, y0, x1, y1;
x0 = 0.0;
x1 = colsIn;
y0 = 0.0;
y1 = rowsIn;
path.move_to(x0, y0);
path.line_to(x1, y0);
path.line_to(x1, y1);
path.line_to(x0, y1);
path.close_polygon();
agg::conv_transform<agg::path_storage> imageBox(path, srcMatrix);
ras.add_path(imageBox);
typedef agg::wrap_mode_reflect reflect_type;
typedef agg::image_accessor_wrap<pixfmt, reflect_type, reflect_type> img_accessor_type;
pixfmt pixfmtin(*rbufIn);
img_accessor_type ia(pixfmtin);
switch (interpolation)
{
case NEAREST:
{
typedef agg::span_image_filter_rgba_nn<img_accessor_type, interpolator_type> span_gen_type;
typedef agg::renderer_scanline_aa<renderer_base, span_alloc_type, span_gen_type> renderer_type;
span_gen_type sg(ia, interpolator);
renderer_type ri(rb, sa, sg);
agg::render_scanlines(ras, sl, ri);
}
break;
case HANNING:
case HAMMING:
case HERMITE:
{
agg::image_filter_lut filter;
switch (interpolation)
{
case HANNING:
filter.calculate(agg::image_filter_hanning(), norm);
break;
case HAMMING:
filter.calculate(agg::image_filter_hamming(), norm);
break;
case HERMITE:
filter.calculate(agg::image_filter_hermite(), norm);
break;
}
if (resample)
{
typedef agg::span_image_resample_rgba_affine<img_accessor_type> span_gen_type;
typedef agg::renderer_scanline_aa<renderer_base, span_alloc_type, span_gen_type> renderer_type;
span_gen_type sg(ia, interpolator, filter);
renderer_type ri(rb, sa, sg);
agg::render_scanlines(ras, sl, ri);
}
else
{
typedef agg::span_image_filter_rgba_2x2<img_accessor_type, interpolator_type> span_gen_type;
typedef agg::renderer_scanline_aa<renderer_base, span_alloc_type, span_gen_type> renderer_type;
span_gen_type sg(ia, interpolator, filter);
renderer_type ri(rb, sa, sg);
agg::render_scanlines(ras, sl, ri);
}
}
break;
case BILINEAR:
case BICUBIC:
case SPLINE16:
case SPLINE36:
case KAISER:
case QUADRIC:
case CATROM:
case GAUSSIAN:
case BESSEL:
case MITCHELL:
case SINC:
case LANCZOS:
case BLACKMAN:
{
agg::image_filter_lut filter;
switch (interpolation)
{
case BILINEAR:
filter.calculate(agg::image_filter_bilinear(), norm);
break;
case BICUBIC:
filter.calculate(agg::image_filter_bicubic(), norm);
break;
case SPLINE16:
filter.calculate(agg::image_filter_spline16(), norm);
break;
case SPLINE36:
filter.calculate(agg::image_filter_spline36(), norm);
break;
case KAISER:
filter.calculate(agg::image_filter_kaiser(), norm);
break;
case QUADRIC:
filter.calculate(agg::image_filter_quadric(), norm);
break;
case CATROM:
filter.calculate(agg::image_filter_catrom(), norm);
break;
case GAUSSIAN:
filter.calculate(agg::image_filter_gaussian(), norm);
break;
case BESSEL:
filter.calculate(agg::image_filter_bessel(), norm);
break;
case MITCHELL:
filter.calculate(agg::image_filter_mitchell(), norm);
break;
case SINC:
filter.calculate(agg::image_filter_sinc(radius), norm);
break;
case LANCZOS:
filter.calculate(agg::image_filter_lanczos(radius), norm);
break;
case BLACKMAN:
filter.calculate(agg::image_filter_blackman(radius), norm);
break;
}
if (resample)
{
typedef agg::span_image_resample_rgba_affine<img_accessor_type> span_gen_type;
typedef agg::renderer_scanline_aa<renderer_base, span_alloc_type, span_gen_type> renderer_type;
span_gen_type sg(ia, interpolator, filter);
renderer_type ri(rb, sa, sg);
agg::render_scanlines(ras, sl, ri);
}
else
{
typedef agg::span_image_filter_rgba<img_accessor_type, interpolator_type> span_gen_type;
typedef agg::renderer_scanline_aa<renderer_base, span_alloc_type, span_gen_type> renderer_type;
span_gen_type sg(ia, interpolator, filter);
renderer_type ri(rb, sa, sg);
agg::render_scanlines(ras, sl, ri);
}
}
break;
}
return Py::Object();
}
char Image::get_interpolation__doc__[] =
"get_interpolation()\n"
"\n"
"Get the interpolation scheme to one of the module constants, "
"one of image.NEAREST, image.BILINEAR, etc..."
;
Py::Object
Image::get_interpolation(const Py::Tuple& args)
{
_VERBOSE("Image::get_interpolation");
args.verify_length(0);
return Py::Int((int)interpolation);
}
char Image::get_aspect__doc__[] =
"get_aspect()\n"
"\n"
"Get the aspect constraint constants"
;
Py::Object
Image::get_aspect(const Py::Tuple& args)
{
_VERBOSE("Image::get_aspect");
args.verify_length(0);
return Py::Int((int)aspect);
}
char Image::get_size__doc__[] =
"numrows, numcols = get_size()\n"
"\n"
"Get the number or rows and columns of the input image"
;
Py::Object
Image::get_size(const Py::Tuple& args)
{
_VERBOSE("Image::get_size");
args.verify_length(0);
Py::Tuple ret(2);
ret[0] = Py::Int((long)rowsIn);
ret[1] = Py::Int((long)colsIn);
return ret;
}
char Image::get_resample__doc__[] =
"get_resample()\n"
"\n"
"Get the resample flag."
;
Py::Object
Image::get_resample(const Py::Tuple& args)
{
_VERBOSE("Image::get_resample");
args.verify_length(0);
return Py::Int((int)resample);
}
char Image::get_size_out__doc__[] =
"numrows, numcols = get_size()\n"
"\n"
"Get the number or rows and columns of the output image"
;
Py::Object
Image::get_size_out(const Py::Tuple& args)
{
_VERBOSE("Image::get_size_out");
args.verify_length(0);
Py::Tuple ret(2);
ret[0] = Py::Int((long)rowsOut);
ret[1] = Py::Int((long)colsOut);
return ret;
}
//get the output buffer, flipped if necessary. The second element of
//the pair is a bool that indicates whether you need to free the
//memory
std::pair<agg::int8u*, bool>
Image::_get_output_buffer()
{
_VERBOSE("Image::_get_output_buffer");
std::pair<agg::int8u*, bool> ret;
bool flipy = rbufOut->stride() < 0;
if (flipy)
{
agg::int8u* buffer = new agg::int8u[rowsOut*colsOut*4];
agg::rendering_buffer rb;
rb.attach(buffer, colsOut, rowsOut, colsOut*4);
rb.copy_from(*rbufOut);
ret.first = buffer;
ret.second = true;
}
else
{
ret.first = bufferOut;
ret.second = false;
}
return ret;
}
char Image::set_interpolation__doc__[] =
"set_interpolation(scheme)\n"
"\n"
"Set the interpolation scheme to one of the module constants, "
"eg, image.NEAREST, image.BILINEAR, etc..."
;
Py::Object
Image::set_interpolation(const Py::Tuple& args)
{
_VERBOSE("Image::set_interpolation");
args.verify_length(1);
size_t method = (long)Py::Int(args[0]);
interpolation = (unsigned)method;
return Py::Object();
}
char Image::set_resample__doc__[] =
"set_resample(boolean)\n"
"\n"
"Set the resample flag."
;
Py::Object
Image::set_resample(const Py::Tuple& args)
{
_VERBOSE("Image::set_resample");
args.verify_length(1);
int flag = Py::Int(args[0]);
resample = (bool)flag;
return Py::Object();
}
char Image::set_aspect__doc__[] =
"set_aspect(scheme)\n"
"\n"
"Set the aspect ration to one of the image module constant."
"eg, one of image.ASPECT_PRESERVE, image.ASPECT_FREE"
;
Py::Object
Image::set_aspect(const Py::Tuple& args)
{
_VERBOSE("Image::set_aspect");
args.verify_length(1);
size_t method = (long)Py::Int(args[0]);
aspect = (unsigned)method;
return Py::Object();
}
void
Image::init_type()
{
_VERBOSE("Image::init_type");
behaviors().name("Image");
behaviors().doc("Image");
behaviors().supportGetattr();
behaviors().supportSetattr();
add_varargs_method("apply_rotation", &Image::apply_rotation, Image::apply_rotation__doc__);
add_varargs_method("apply_scaling", &Image::apply_scaling, Image::apply_scaling__doc__);
add_varargs_method("apply_translation", &Image::apply_translation, Image::apply_translation__doc__);
add_keyword_method("as_rgba_str", &Image::as_rgba_str, Image::as_rgba_str__doc__);
add_varargs_method("color_conv", &Image::color_conv, Image::color_conv__doc__);
add_varargs_method("buffer_rgba", &Image::buffer_rgba, Image::buffer_rgba__doc__);
add_varargs_method("get_aspect", &Image::get_aspect, Image::get_aspect__doc__);
add_varargs_method("get_interpolation", &Image::get_interpolation, Image::get_interpolation__doc__);
add_varargs_method("get_resample", &Image::get_resample, Image::get_resample__doc__);
add_varargs_method("get_size", &Image::get_size, Image::get_size__doc__);
add_varargs_method("get_size_out", &Image::get_size_out, Image::get_size_out__doc__);
add_varargs_method("reset_matrix", &Image::reset_matrix, Image::reset_matrix__doc__);
add_varargs_method("get_matrix", &Image::get_matrix, Image::get_matrix__doc__);
add_keyword_method("resize", &Image::resize, Image::resize__doc__);
add_varargs_method("set_interpolation", &Image::set_interpolation, Image::set_interpolation__doc__);
add_varargs_method("set_resample", &Image::set_resample, Image::set_resample__doc__);
add_varargs_method("set_aspect", &Image::set_aspect, Image::set_aspect__doc__);
add_varargs_method("set_bg", &Image::set_bg, Image::set_bg__doc__);
add_varargs_method("flipud_out", &Image::flipud_out, Image::flipud_out__doc__);
add_varargs_method("flipud_in", &Image::flipud_in, Image::flipud_in__doc__);
}
char _image_module_from_images__doc__[] =
"from_images(numrows, numcols, seq)\n"
"\n"
"return an image instance with numrows, numcols from a seq of image\n"
"instances using alpha blending. seq is a list of (Image, ox, oy)"
;
Py::Object
_image_module::from_images(const Py::Tuple& args)
{
_VERBOSE("_image_module::from_images");
args.verify_length(3);
size_t numrows = (long)Py::Int(args[0]);
size_t numcols = (long)Py::Int(args[1]);
if (numrows >= 32768 || numcols >= 32768)
{
throw Py::RuntimeError("numrows and numcols must both be less than 32768");
}
Py::SeqBase<Py::Object> tups = args[2];
size_t N = tups.length();
if (N == 0)
{
throw Py::RuntimeError("Empty list of images");
}
Py::Tuple tup;
size_t ox(0), oy(0), thisx(0), thisy(0);
//copy image 0 output buffer into return images output buffer
Image* imo = new Image;
imo->rowsOut = numrows;
imo->colsOut = numcols;
size_t NUMBYTES(numrows * numcols * imo->BPP);
imo->bufferOut = new agg::int8u[NUMBYTES];
if (imo->bufferOut == NULL) //todo: also handle allocation throw
{
throw Py::MemoryError("_image_module::from_images could not allocate memory");
}
delete imo->rbufOut;
imo->rbufOut = new agg::rendering_buffer;
imo->rbufOut->attach(imo->bufferOut, imo->colsOut, imo->rowsOut, imo->colsOut * imo->BPP);
pixfmt pixf(*imo->rbufOut);
renderer_base rb(pixf);
rb.clear(agg::rgba(1, 1, 1, 1));
for (size_t imnum = 0; imnum < N; imnum++)
{
tup = Py::Tuple(tups[imnum]);
Image* thisim = static_cast<Image*>(tup[0].ptr());
ox = (long)Py::Int(tup[1]);
oy = (long)Py::Int(tup[2]);
bool isflip = (thisim->rbufOut->stride()) < 0;
//std::cout << "from images " << isflip << "; stride=" << thisim->rbufOut->stride() << std::endl;
size_t ind = 0;
for (size_t j = 0; j < thisim->rowsOut; j++)
{
for (size_t i = 0; i < thisim->colsOut; i++)
{
thisx = i + ox;
if (isflip)
{
thisy = thisim->rowsOut - j + oy;
}
else
{
thisy = j + oy;
}
if (thisx >= numcols || thisy >= numrows)
{
ind += 4;
continue;
}
pixfmt::color_type p;
p.r = *(thisim->bufferOut + ind++);
p.g = *(thisim->bufferOut + ind++);
p.b = *(thisim->bufferOut + ind++);
p.a = *(thisim->bufferOut + ind++);
pixf.blend_pixel(thisx, thisy, p, 255);
}
}
}
return Py::asObject(imo);
}
char _image_module_fromarray__doc__[] =
"fromarray(A, isoutput)\n"
"\n"
"Load the image from a numpy array\n"
"By default this function fills the input buffer, which can subsequently\n"
"be resampled using resize. If isoutput=1, fill the output buffer.\n"
"This is used to support raw pixel images w/o resampling"
;
Py::Object
_image_module::fromarray(const Py::Tuple& args)
{
_VERBOSE("_image_module::fromarray");
args.verify_length(2);
Py::Object x = args[0];
int isoutput = Py::Int(args[1]);
PyArrayObject *A = (PyArrayObject *) PyArray_FromObject(x.ptr(), PyArray_DOUBLE, 2, 3);
if (A == NULL)
{
throw Py::ValueError("Array must be rank 2 or 3 of doubles");
}
Py::Object A_obj((PyObject *)A, true);
Image* imo = new Image;
imo->rowsIn = A->dimensions[0];
imo->colsIn = A->dimensions[1];
size_t NUMBYTES(imo->colsIn * imo->rowsIn * imo->BPP);
agg::int8u *buffer = new agg::int8u[NUMBYTES];
if (buffer == NULL) //todo: also handle allocation throw
{
throw Py::MemoryError("_image_module::fromarray could not allocate memory");
}
if (isoutput)
{
// make the output buffer point to the input buffer
imo->rowsOut = imo->rowsIn;
imo->colsOut = imo->colsIn;
imo->rbufOut = new agg::rendering_buffer;
imo->bufferOut = buffer;
imo->rbufOut->attach(imo->bufferOut, imo->colsOut, imo->rowsOut, imo->colsOut * imo->BPP);
}
else
{
imo->bufferIn = buffer;
imo->rbufIn = new agg::rendering_buffer;
imo->rbufIn->attach(buffer, imo->colsIn, imo->rowsIn, imo->colsIn*imo->BPP);
}
if (A->nd == 2) //assume luminance for now;
{
agg::int8u gray;
for (size_t rownum = 0; rownum < imo->rowsIn; rownum++)
{
for (size_t colnum = 0; colnum < imo->colsIn; colnum++)
{
double val = *(double *)(A->data + rownum * A->strides[0] + colnum * A->strides[1]);
gray = int(255 * val);
*buffer++ = gray; // red
*buffer++ = gray; // green
*buffer++ = gray; // blue
*buffer++ = 255; // alpha
}
}
}
else if (A->nd == 3) // assume RGB
{
if (A->dimensions[2] != 3 && A->dimensions[2] != 4)
{
throw Py::ValueError(Printf("3rd dimension must be length 3 (RGB) or 4 (RGBA); found %d", A->dimensions[2]).str());
}
int rgba = A->dimensions[2] == 4;
double r, g, b, alpha;
size_t offset = 0;
for (size_t rownum = 0; rownum < imo->rowsIn; rownum++)
{
for (size_t colnum = 0; colnum < imo->colsIn; colnum++)
{
offset = rownum * A->strides[0] + colnum * A->strides[1];
r = *(double *)(A->data + offset);
g = *(double *)(A->data + offset + A->strides[2]);
b = *(double *)(A->data + offset + 2 * A->strides[2]);
if (rgba)
{
alpha = *(double *)(A->data + offset + 3 * A->strides[2]);
}
else
{
alpha = 1.0;
}
*buffer++ = int(255 * r); // red
*buffer++ = int(255 * g); // green
*buffer++ = int(255 * b); // blue
*buffer++ = int(255 * alpha); // alpha
}
}
}
else // error
{
throw Py::ValueError("Illegal array rank; must be rank; must 2 or 3");
}
buffer -= NUMBYTES;
return Py::asObject(imo);
}
char _image_module_fromarray2__doc__[] =
"fromarray2(A, isoutput)\n"
"\n"
"Load the image from a numpy array\n"
"By default this function fills the input buffer, which can subsequently\n"
"be resampled using resize. If isoutput=1, fill the output buffer.\n"
"This is used to support raw pixel images w/o resampling"
;
Py::Object
_image_module::fromarray2(const Py::Tuple& args)
{
_VERBOSE("_image_module::fromarray2");
args.verify_length(2);
Py::Object x = args[0];
int isoutput = Py::Int(args[1]);
PyArrayObject *A = (PyArrayObject *) PyArray_ContiguousFromObject(x.ptr(), PyArray_DOUBLE, 2, 3);
if (A == NULL)
{
throw Py::ValueError("Array must be rank 2 or 3 of doubles");
}
Py::Object A_obj((PyObject*)A, true);
Image* imo = new Image;
imo->rowsIn = A->dimensions[0];
imo->colsIn = A->dimensions[1];
size_t NUMBYTES(imo->colsIn * imo->rowsIn * imo->BPP);
agg::int8u *buffer = new agg::int8u[NUMBYTES];
if (buffer == NULL) //todo: also handle allocation throw
{
throw Py::MemoryError("_image_module::fromarray could not allocate memory");
}
if (isoutput)
{
// make the output buffer point to the input buffer
imo->rowsOut = imo->rowsIn;