#include "wx/filefn.h"
#include "wx/wfstream.h"
-
-#if wxUSE_XPM
- #include "wx/xpmdecod.h"
-#endif
+#include "wx/xpmdecod.h"
// For memcpy
#include <string.h>
#endif // wxUSE_FILE/wxUSE_FFILE
#endif // HAS_FILE_STREAMS
+#if wxUSE_VARIANT
+IMPLEMENT_VARIANT_OBJECT_EXPORTED(wxImage,WXDLLEXPORT)
+#endif
+
//-----------------------------------------------------------------------------
// wxImage
//-----------------------------------------------------------------------------
}
#endif // wxUSE_STREAMS
-wxImage::wxImage( const char** xpmData )
+wxImage::wxImage(const char* const* xpmData)
{
Create(xpmData);
}
-wxImage::wxImage( char** xpmData )
-{
- Create((const char**) xpmData);
-}
-
-bool wxImage::Create( const char** xpmData )
+bool wxImage::Create(const char* const* xpmData)
{
#if wxUSE_XPM
UnRef();
wxCHECK_MSG( (old_height > 0) && (old_width > 0), image,
wxT("invalid old image size") );
- // If the image's new width and height are the same as the original, no need to waste time or CPU cycles
- if(old_width == width && old_height == height)
+ // If the image's new width and height are the same as the original, no
+ // need to waste time or CPU cycles
+ if ( old_width == width && old_height == height )
return *this;
- // Scale the image (...or more appropriately, resample the image) using either the high-quality or normal method as specified
- if(quality == wxIMAGE_QUALITY_HIGH)
+ // Scale the image (...or more appropriately, resample the image) using
+ // either the high-quality or normal method as specified
+ if ( quality == wxIMAGE_QUALITY_HIGH )
{
// We need to check whether we are downsampling or upsampling the image
- if(width < old_width && height < old_height)
+ if ( width < old_width && height < old_height )
{
// Downsample the image using the box averaging method for best results
image = ResampleBox(width, height);
}
else
{
- // For upsampling or other random/wierd image dimensions we'll use a bicubic b-spline scaling method
+ // For upsampling or other random/wierd image dimensions we'll use
+ // a bicubic b-spline scaling method
image = ResampleBicubic(width, height);
}
}
unsigned char *source_alpha = 0 ;
unsigned char *target_alpha = 0 ;
- if (M_IMGDATA->m_hasMask)
- {
- image.SetMaskColour( M_IMGDATA->m_maskRed,
- M_IMGDATA->m_maskGreen,
- M_IMGDATA->m_maskBlue );
- }
- else
+ if ( !M_IMGDATA->m_hasMask )
{
source_alpha = M_IMGDATA->m_alpha ;
if ( source_alpha )
}
}
+ // If the original image has a mask, apply the mask to the new image
+ if (M_IMGDATA->m_hasMask)
+ {
+ image.SetMaskColour( M_IMGDATA->m_maskRed,
+ M_IMGDATA->m_maskGreen,
+ M_IMGDATA->m_maskBlue );
+ }
+
// In case this is a cursor, make sure the hotspot is scaled accordingly:
if ( HasOption(wxIMAGE_OPTION_CUR_HOTSPOT_X) )
image.SetOption(wxIMAGE_OPTION_CUR_HOTSPOT_X,
wxImage wxImage::ResampleBox(int width, int height) const
{
- // This function implements a simple pre-blur/box averaging method for downsampling that gives reasonably smooth results
- // To scale the image down we will need to gather a grid of pixels of the size of the scale factor in each direction
- // and then do an averaging of the pixels.
+ // This function implements a simple pre-blur/box averaging method for
+ // downsampling that gives reasonably smooth results To scale the image
+ // down we will need to gather a grid of pixels of the size of the scale
+ // factor in each direction and then do an averaging of the pixels.
wxImage ret_image(width, height, false);
- double scale_factor_x = double(M_IMGDATA->m_width) / width;
- double scale_factor_y = double(M_IMGDATA->m_height) / height;
+ const double scale_factor_x = double(M_IMGDATA->m_width) / width;
+ const double scale_factor_y = double(M_IMGDATA->m_height) / height;
+
+ const int scale_factor_x_2 = (int)(scale_factor_x / 2);
+ const int scale_factor_y_2 = (int)(scale_factor_y / 2);
// If we want good-looking results we need to pre-blur the image a bit first
wxImage src_image(*this);
- src_image = src_image.BlurHorizontal(scale_factor_x / 2);
- src_image = src_image.BlurVertical(scale_factor_y / 2);
+ src_image = src_image.BlurHorizontal(scale_factor_x_2);
+ src_image = src_image.BlurVertical(scale_factor_y_2);
unsigned char* src_data = src_image.GetData();
unsigned char* src_alpha = src_image.GetAlpha();
unsigned char* dst_data = ret_image.GetData();
unsigned char* dst_alpha = NULL;
- if(src_alpha)
+ if ( src_alpha )
{
ret_image.SetAlpha();
dst_alpha = ret_image.GetAlpha();
}
- int x, y, i, j;
- int averaged_pixels, src_pixel_index, src_x, src_y;
+ int averaged_pixels, src_pixel_index;
double sum_r, sum_g, sum_b, sum_a;
- for(y = 0; y < height; y++) // Destination image - Y direction
+ for ( int y = 0; y < height; y++ ) // Destination image - Y direction
{
// Source pixel in the Y direction
- src_y = y * scale_factor_y;
+ int src_y = (int)(y * scale_factor_y);
- for(x = 0; x < width; x++) // Destination image - X direction
+ for ( int x = 0; x < width; x++ ) // Destination image - X direction
{
// Source pixel in the X direction
- src_x = x * scale_factor_x;
+ int src_x = (int)(x * scale_factor_x);
// Box of pixels to average
averaged_pixels = 0;
sum_r = sum_g = sum_b = sum_a = 0.0;
- for(j = src_y - scale_factor_y / 2 + 1; j <= int(src_y + scale_factor_y / 2); j++) // Y direction
+ for ( int j = int(src_y - scale_factor_y/2.0 + 1);
+ j <= int(src_y + scale_factor_y_2);
+ j++ )
{
// We don't care to average pixels that don't exist (edges)
- if(j < 0 || j > M_IMGDATA->m_height)
+ if ( j < 0 || j > M_IMGDATA->m_height )
continue;
- for(i = src_x - scale_factor_x / 2 + 1; i <= int(src_x + scale_factor_x / 2); i++) // X direction
+ for ( int i = int(src_x - scale_factor_x/2.0 + 1);
+ i <= src_x + scale_factor_x_2;
+ i++ )
{
// Don't average edge pixels
- if(i < 0 || i > M_IMGDATA->m_width)
+ if ( i < 0 || i > M_IMGDATA->m_width )
continue;
// Calculate the actual index in our source pixels
sum_r += src_data[src_pixel_index * 3 + 0];
sum_g += src_data[src_pixel_index * 3 + 1];
sum_b += src_data[src_pixel_index * 3 + 2];
- if(src_alpha)
+ if ( src_alpha )
sum_a += src_alpha[src_pixel_index];
averaged_pixels++;
}
// Calculate the average from the sum and number of averaged pixels
- dst_data[0] = int(sum_r / averaged_pixels);
- dst_data[1] = int(sum_g / averaged_pixels);
- dst_data[2] = int(sum_b / averaged_pixels);
+ dst_data[0] = (unsigned char)(sum_r / averaged_pixels);
+ dst_data[1] = (unsigned char)(sum_g / averaged_pixels);
+ dst_data[2] = (unsigned char)(sum_b / averaged_pixels);
dst_data += 3;
- if(src_alpha)
- *dst_alpha++ = sum_a / averaged_pixels;
+ if ( src_alpha )
+ *dst_alpha++ = (unsigned char)(sum_a / averaged_pixels);
}
}
return ret_image;
}
-// The following two local functions are for the B-spline weighting of the bicubic sampling algorithm
+// The following two local functions are for the B-spline weighting of the
+// bicubic sampling algorithm
static inline double spline_cube(double value)
{
return value <= 0.0 ? 0.0 : value * value * value;
static inline double spline_weight(double value)
{
- return (spline_cube(value + 2) - 4 * spline_cube(value + 1) + 6 * spline_cube(value) - 4 * spline_cube(value - 1)) / 6;
+ return (spline_cube(value + 2) -
+ 4 * spline_cube(value + 1) +
+ 6 * spline_cube(value) -
+ 4 * spline_cube(value - 1)) / 6;
}
// This is the bicubic resampling algorithm
wxImage wxImage::ResampleBicubic(int width, int height) const
{
- // This function implements a Bicubic B-Spline algorithm for resampling. This method is certainly a little slower than wxImage's default
- // pixel replication method, however for most reasonably sized images not being upsampled too much on a fairly average CPU this
- // difference is hardly noticeable and the results are far more pleasing to look at.
+ // This function implements a Bicubic B-Spline algorithm for resampling.
+ // This method is certainly a little slower than wxImage's default pixel
+ // replication method, however for most reasonably sized images not being
+ // upsampled too much on a fairly average CPU this difference is hardly
+ // noticeable and the results are far more pleasing to look at.
//
- // This particular bicubic algorithm does pixel weighting according to a B-Spline that basically implements a Gaussian bell-like
- // weighting kernel. Because of this method the results may appear a bit blurry when upsampling by large factors. This is basically
- // because a slight gaussian blur is being performed to get the smooth look of the upsampled image.
+ // This particular bicubic algorithm does pixel weighting according to a
+ // B-Spline that basically implements a Gaussian bell-like weighting
+ // kernel. Because of this method the results may appear a bit blurry when
+ // upsampling by large factors. This is basically because a slight
+ // gaussian blur is being performed to get the smooth look of the upsampled
+ // image.
// Edge pixels: 3-4 possible solutions
- // - (Wrap/tile) Wrap the image, take the color value from the opposite side of the image.
- // - (Mirror) Duplicate edge pixels, so that pixel at coordinate (2, n), where n is nonpositive, will have the value of (2, 1).
- // - (Ignore) Simply ignore the edge pixels and apply the kernel only to pixels which do have all neighbours.
- // - (Clamp) Choose the nearest pixel along the border. This takes the border pixels and extends them out to infinity.
+ // - (Wrap/tile) Wrap the image, take the color value from the opposite
+ // side of the image.
+ // - (Mirror) Duplicate edge pixels, so that pixel at coordinate (2, n),
+ // where n is nonpositive, will have the value of (2, 1).
+ // - (Ignore) Simply ignore the edge pixels and apply the kernel only to
+ // pixels which do have all neighbours.
+ // - (Clamp) Choose the nearest pixel along the border. This takes the
+ // border pixels and extends them out to infinity.
//
- // NOTE: below the y_offset and x_offset variables are being set for edge pixels using the "Mirror" method mentioned above
+ // NOTE: below the y_offset and x_offset variables are being set for edge
+ // pixels using the "Mirror" method mentioned above
wxImage ret_image;
unsigned char* dst_data = ret_image.GetData();
unsigned char* dst_alpha = NULL;
- if(src_alpha)
+ if ( src_alpha )
{
ret_image.SetAlpha();
dst_alpha = ret_image.GetAlpha();
}
- int k, i;
- double srcpixx, srcpixy, dx, dy;
- int dstx, dsty;
- double sum_r = 0, sum_g = 0, sum_b = 0, sum_a = 0; // Sums for each color channel
- int x_offset = 0, y_offset = 0;
- double pixel_weight;
- long src_pixel_index;
-
- for(dsty = 0; dsty < height; dsty++)
+ for ( int dsty = 0; dsty < height; dsty++ )
{
// We need to calculate the source pixel to interpolate from - Y-axis
- srcpixy = double(dsty) * M_IMGDATA->m_height / height;
- dy = srcpixy - (int)srcpixy;
+ double srcpixy = dsty * M_IMGDATA->m_height / height;
+ double dy = srcpixy - (int)srcpixy;
- for(dstx = 0; dstx < width; dstx++)
+ for ( int dstx = 0; dstx < width; dstx++ )
{
// X-axis of pixel to interpolate from
- srcpixx = double(dstx) * M_IMGDATA->m_width / width;
- dx = srcpixx - (int)srcpixx;
+ double srcpixx = dstx * M_IMGDATA->m_width / width;
+ double dx = srcpixx - (int)srcpixx;
- // Clear all the RGBA sum values
- sum_r = sum_g = sum_b = sum_a = 0;
+ // Sums for each color channel
+ double sum_r = 0, sum_g = 0, sum_b = 0, sum_a = 0;
// Here we actually determine the RGBA values for the destination pixel
- for(k = -1; k <= 2; k++)
+ for ( int k = -1; k <= 2; k++ )
{
// Y offset
- y_offset = srcpixy + double(k) < 0.0 ? 0 : (srcpixy + double(k) >= M_IMGDATA->m_height ? M_IMGDATA->m_height - 1 : srcpixy + k);
+ int y_offset = srcpixy + k < 0.0
+ ? 0
+ : srcpixy + k >= M_IMGDATA->m_height
+ ? M_IMGDATA->m_height - 1
+ : (int)(srcpixy + k);
// Loop across the X axis
- for(i = -1; i <= 2; i++)
+ for ( int i = -1; i <= 2; i++ )
{
// X offset
- x_offset = srcpixx + double(i) < 0.0 ? 0 : (srcpixx + double(i) >= M_IMGDATA->m_width ? M_IMGDATA->m_width - 1 : srcpixx + i);
-
- // Calculate the exact position where the source data should be pulled from based on the x_offset and y_offset
- src_pixel_index = (y_offset * M_IMGDATA->m_width) + x_offset;
-
- // Calculate the weight for the specified pixel according to the bicubic b-spline kernel we're using for interpolation
- pixel_weight = spline_weight(double(i) - dx) * spline_weight(double(k) - dy);
-
- // Create a sum of all velues for each color channel adjusted for the pixel's calculated weight
- sum_r += double(src_data[src_pixel_index * 3 + 0]) * pixel_weight;
- sum_g += double(src_data[src_pixel_index * 3 + 1]) * pixel_weight;
- sum_b += double(src_data[src_pixel_index * 3 + 2]) * pixel_weight;
- if(src_alpha)
- sum_a += double(src_alpha[src_pixel_index]) * pixel_weight;
+ int x_offset = srcpixx + i < 0.0
+ ? 0
+ : srcpixx + i >= M_IMGDATA->m_width
+ ? M_IMGDATA->m_width - 1
+ : (int)(srcpixx + i);
+
+ // Calculate the exact position where the source data
+ // should be pulled from based on the x_offset and y_offset
+ int src_pixel_index = y_offset*M_IMGDATA->m_width + x_offset;
+
+ // Calculate the weight for the specified pixel according
+ // to the bicubic b-spline kernel we're using for
+ // interpolation
+ double
+ pixel_weight = spline_weight(i - dx)*spline_weight(k - dy);
+
+ // Create a sum of all velues for each color channel
+ // adjusted for the pixel's calculated weight
+ sum_r += src_data[src_pixel_index * 3 + 0] * pixel_weight;
+ sum_g += src_data[src_pixel_index * 3 + 1] * pixel_weight;
+ sum_b += src_data[src_pixel_index * 3 + 2] * pixel_weight;
+ if ( src_alpha )
+ sum_a += src_alpha[src_pixel_index] * pixel_weight;
}
}
- // Put the data into the destination image. The summed values are of double data type and are rounded here for accuracy
- dst_data[0] = int(sum_r + 0.5);
- dst_data[1] = int(sum_g + 0.5);
- dst_data[2] = int(sum_b + 0.5);
+ // Put the data into the destination image. The summed values are
+ // of double data type and are rounded here for accuracy
+ dst_data[0] = (unsigned char)(sum_r + 0.5);
+ dst_data[1] = (unsigned char)(sum_g + 0.5);
+ dst_data[2] = (unsigned char)(sum_b + 0.5);
dst_data += 3;
- if(src_alpha)
- *dst_alpha++ = sum_a;
+ if ( src_alpha )
+ *dst_alpha++ = (unsigned char)sum_a;
}
}
unsigned char* dst_alpha = NULL;
// Check for a mask or alpha
- if(M_IMGDATA->m_hasMask)
- ret_image.SetMaskColour(M_IMGDATA->m_maskRed, M_IMGDATA->m_maskGreen, M_IMGDATA->m_maskBlue);
+ if ( M_IMGDATA->m_hasMask )
+ {
+ ret_image.SetMaskColour(M_IMGDATA->m_maskRed,
+ M_IMGDATA->m_maskGreen,
+ M_IMGDATA->m_maskBlue);
+ }
else
- if(src_alpha)
+ {
+ if ( src_alpha )
{
ret_image.SetAlpha();
dst_alpha = ret_image.GetAlpha();
}
+ }
- // Variables used in the blurring algorithm
- int x, y;
- int kernel_x;
- long sum_r, sum_g, sum_b, sum_a;
- long pixel_idx;
+ // number of pixels we average over
+ const int blurArea = blurRadius*2 + 1;
- // Horizontal blurring algorithm - average all pixels in the specified blur radius in the X or horizontal direction
- for(y = 0; y < M_IMGDATA->m_height; y++)
+ // Horizontal blurring algorithm - average all pixels in the specified blur
+ // radius in the X or horizontal direction
+ for ( int y = 0; y < M_IMGDATA->m_height; y++ )
{
- sum_r = sum_g = sum_b = sum_a = 0;
+ // Variables used in the blurring algorithm
+ long sum_r = 0,
+ sum_g = 0,
+ sum_b = 0,
+ sum_a = 0;
+
+ long pixel_idx;
+ const unsigned char *src;
+ unsigned char *dst;
- // Calculate the average of all pixels in the blur radius for the first pixel of the row
- for(kernel_x = -blurRadius; kernel_x <= blurRadius; kernel_x++)
+ // Calculate the average of all pixels in the blur radius for the first
+ // pixel of the row
+ for ( int kernel_x = -blurRadius; kernel_x <= blurRadius; kernel_x++ )
{
- // To deal with the pixels at the start of a row so it's not grabbing GOK values from memory at negative indices of the image's data or grabbing from the previous row
- if(kernel_x < 0)
+ // To deal with the pixels at the start of a row so it's not
+ // grabbing GOK values from memory at negative indices of the
+ // image's data or grabbing from the previous row
+ if ( kernel_x < 0 )
pixel_idx = y * M_IMGDATA->m_width;
else
pixel_idx = kernel_x + y * M_IMGDATA->m_width;
- sum_r += src_data[pixel_idx * 3 + 0];
- sum_g += src_data[pixel_idx * 3 + 1];
- sum_b += src_data[pixel_idx * 3 + 2];
- sum_a += src_alpha ? src_alpha[pixel_idx] : 0;
+ src = src_data + pixel_idx*3;
+ sum_r += src[0];
+ sum_g += src[1];
+ sum_b += src[2];
+ if ( src_alpha )
+ sum_a += src_alpha[pixel_idx];
}
- dst_data[y * M_IMGDATA->m_width * 3 + 0] = sum_r / (blurRadius * 2 + 1);
- dst_data[y * M_IMGDATA->m_width * 3 + 1] = sum_g / (blurRadius * 2 + 1);
- dst_data[y * M_IMGDATA->m_width * 3 + 2] = sum_b / (blurRadius * 2 + 1);
- if(src_alpha)
- dst_alpha[y * M_IMGDATA->m_width] = sum_a / (blurRadius * 2 + 1);
-
- // Now average the values of the rest of the pixels by just moving the blur radius box along the row
- for(x = 1; x < M_IMGDATA->m_width; x++)
+
+ dst = dst_data + y * M_IMGDATA->m_width*3;
+ dst[0] = (unsigned char)(sum_r / blurArea);
+ dst[1] = (unsigned char)(sum_g / blurArea);
+ dst[2] = (unsigned char)(sum_b / blurArea);
+ if ( src_alpha )
+ dst_alpha[y * M_IMGDATA->m_width] = (unsigned char)(sum_a / blurArea);
+
+ // Now average the values of the rest of the pixels by just moving the
+ // blur radius box along the row
+ for ( int x = 1; x < M_IMGDATA->m_width; x++ )
{
- // Take care of edge pixels on the left edge by essentially duplicating the edge pixel
- if(x - blurRadius - 1 < 0)
+ // Take care of edge pixels on the left edge by essentially
+ // duplicating the edge pixel
+ if ( x - blurRadius - 1 < 0 )
pixel_idx = y * M_IMGDATA->m_width;
else
pixel_idx = (x - blurRadius - 1) + y * M_IMGDATA->m_width;
- // Subtract the value of the pixel at the left side of the blur radius box
- sum_r -= src_data[pixel_idx * 3 + 0];
- sum_g -= src_data[pixel_idx * 3 + 1];
- sum_b -= src_data[pixel_idx * 3 + 2];
- sum_a -= src_alpha ? src_alpha[pixel_idx] : 0;
+ // Subtract the value of the pixel at the left side of the blur
+ // radius box
+ src = src_data + pixel_idx*3;
+ sum_r -= src[0];
+ sum_g -= src[1];
+ sum_b -= src[2];
+ if ( src_alpha )
+ sum_a -= src_alpha[pixel_idx];
// Take care of edge pixels on the right edge
- if(x + blurRadius > M_IMGDATA->m_width - 1)
+ if ( x + blurRadius > M_IMGDATA->m_width - 1 )
pixel_idx = M_IMGDATA->m_width - 1 + y * M_IMGDATA->m_width;
else
pixel_idx = x + blurRadius + y * M_IMGDATA->m_width;
// Add the value of the pixel being added to the end of our box
- sum_r += src_data[pixel_idx * 3 + 0];
- sum_g += src_data[pixel_idx * 3 + 1];
- sum_b += src_data[pixel_idx * 3 + 2];
- sum_a += src_alpha ? src_alpha[pixel_idx] : 0;
+ src = src_data + pixel_idx*3;
+ sum_r += src[0];
+ sum_g += src[1];
+ sum_b += src[2];
+ if ( src_alpha )
+ sum_a += src_alpha[pixel_idx];
// Save off the averaged data
- dst_data[x * 3 + y * M_IMGDATA->m_width * 3 + 0] = sum_r / (blurRadius * 2 + 1);
- dst_data[x * 3 + y * M_IMGDATA->m_width * 3 + 1] = sum_g / (blurRadius * 2 + 1);
- dst_data[x * 3 + y * M_IMGDATA->m_width * 3 + 2] = sum_b / (blurRadius * 2 + 1);
- if(src_alpha)
- dst_alpha[x + y * M_IMGDATA->m_width] = sum_a / (blurRadius * 2 + 1);
+ dst = dst_data + x*3 + y*M_IMGDATA->m_width*3;
+ dst[0] = (unsigned char)(sum_r / blurArea);
+ dst[1] = (unsigned char)(sum_g / blurArea);
+ dst[2] = (unsigned char)(sum_b / blurArea);
+ if ( src_alpha )
+ dst_alpha[x + y * M_IMGDATA->m_width] = (unsigned char)(sum_a / blurArea);
}
}
unsigned char* dst_alpha = NULL;
// Check for a mask or alpha
- if(M_IMGDATA->m_hasMask)
- ret_image.SetMaskColour(M_IMGDATA->m_maskRed, M_IMGDATA->m_maskGreen, M_IMGDATA->m_maskBlue);
+ if ( M_IMGDATA->m_hasMask )
+ {
+ ret_image.SetMaskColour(M_IMGDATA->m_maskRed,
+ M_IMGDATA->m_maskGreen,
+ M_IMGDATA->m_maskBlue);
+ }
else
- if(src_alpha)
+ {
+ if ( src_alpha )
{
ret_image.SetAlpha();
dst_alpha = ret_image.GetAlpha();
}
+ }
- // Variables used in the blurring algorithm
- int x, y;
- int kernel_y;
- long sum_r, sum_g, sum_b, sum_a;
- long pixel_idx;
+ // number of pixels we average over
+ const int blurArea = blurRadius*2 + 1;
- // Vertical blurring algorithm - same as horizontal but switched the opposite direction
- for(x = 0; x < M_IMGDATA->m_width; x++)
+ // Vertical blurring algorithm - same as horizontal but switched the
+ // opposite direction
+ for ( int x = 0; x < M_IMGDATA->m_width; x++ )
{
- sum_r = sum_g = sum_b = sum_a = 0;
+ // Variables used in the blurring algorithm
+ long sum_r = 0,
+ sum_g = 0,
+ sum_b = 0,
+ sum_a = 0;
+
+ long pixel_idx;
+ const unsigned char *src;
+ unsigned char *dst;
- // Calculate the average of all pixels in our blur radius box for the first pixel of the column
- for(kernel_y = -blurRadius; kernel_y <= blurRadius; kernel_y++)
+ // Calculate the average of all pixels in our blur radius box for the
+ // first pixel of the column
+ for ( int kernel_y = -blurRadius; kernel_y <= blurRadius; kernel_y++ )
{
- // To deal with the pixels at the start of a column so it's not grabbing GOK values from memory at negative indices of the image's data or grabbing from the previous column
- if(kernel_y < 0)
+ // To deal with the pixels at the start of a column so it's not
+ // grabbing GOK values from memory at negative indices of the
+ // image's data or grabbing from the previous column
+ if ( kernel_y < 0 )
pixel_idx = x;
else
pixel_idx = x + kernel_y * M_IMGDATA->m_width;
- sum_r += src_data[pixel_idx * 3 + 0];
- sum_g += src_data[pixel_idx * 3 + 1];
- sum_b += src_data[pixel_idx * 3 + 2];
- sum_a += src_alpha ? src_alpha[pixel_idx] : 0;
+ src = src_data + pixel_idx*3;
+ sum_r += src[0];
+ sum_g += src[1];
+ sum_b += src[2];
+ if ( src_alpha )
+ sum_a += src_alpha[pixel_idx];
}
- dst_data[x * 3 + 0] = sum_r / (blurRadius * 2 + 1);
- dst_data[x * 3 + 1] = sum_g / (blurRadius * 2 + 1);
- dst_data[x * 3 + 2] = sum_b / (blurRadius * 2 + 1);
- if(src_alpha)
- dst_alpha[x] = sum_a / (blurRadius * 2 + 1);
-
- // Now average the values of the rest of the pixels by just moving the box along the column from top to bottom
- for(y = 1; y < M_IMGDATA->m_height; y++)
+
+ dst = dst_data + x*3;
+ dst[0] = (unsigned char)(sum_r / blurArea);
+ dst[1] = (unsigned char)(sum_g / blurArea);
+ dst[2] = (unsigned char)(sum_b / blurArea);
+ if ( src_alpha )
+ dst_alpha[x] = (unsigned char)(sum_a / blurArea);
+
+ // Now average the values of the rest of the pixels by just moving the
+ // box along the column from top to bottom
+ for ( int y = 1; y < M_IMGDATA->m_height; y++ )
{
- // Take care of pixels that would be beyond the top edge by duplicating the top edge pixel for the column
- if(y - blurRadius - 1 < 0)
+ // Take care of pixels that would be beyond the top edge by
+ // duplicating the top edge pixel for the column
+ if ( y - blurRadius - 1 < 0 )
pixel_idx = x;
else
pixel_idx = x + (y - blurRadius - 1) * M_IMGDATA->m_width;
// Subtract the value of the pixel at the top of our blur radius box
- sum_r -= src_data[pixel_idx * 3 + 0];
- sum_g -= src_data[pixel_idx * 3 + 1];
- sum_b -= src_data[pixel_idx * 3 + 2];
- sum_a -= src_alpha ? src_alpha[pixel_idx] : 0;
-
- // Take care of the pixels that would be beyond the bottom edge of the image similar to the top edge
- if(y + blurRadius > M_IMGDATA->m_height - 1)
+ src = src_data + pixel_idx*3;
+ sum_r -= src[0];
+ sum_g -= src[1];
+ sum_b -= src[2];
+ if ( src_alpha )
+ sum_a -= src_alpha[pixel_idx];
+
+ // Take care of the pixels that would be beyond the bottom edge of
+ // the image similar to the top edge
+ if ( y + blurRadius > M_IMGDATA->m_height - 1 )
pixel_idx = x + (M_IMGDATA->m_height - 1) * M_IMGDATA->m_width;
else
pixel_idx = x + (blurRadius + y) * M_IMGDATA->m_width;
// Add the value of the pixel being added to the end of our box
- sum_r += src_data[pixel_idx * 3 + 0];
- sum_g += src_data[pixel_idx * 3 + 1];
- sum_b += src_data[pixel_idx * 3 + 2];
- sum_a += src_alpha ? src_alpha[pixel_idx] : 0;
+ src = src_data + pixel_idx*3;
+ sum_r += src[0];
+ sum_g += src[1];
+ sum_b += src[2];
+ if ( src_alpha )
+ sum_a += src_alpha[pixel_idx];
// Save off the averaged data
- dst_data[(x + y * M_IMGDATA->m_width) * 3 + 0] = sum_r / (blurRadius * 2 + 1);
- dst_data[(x + y * M_IMGDATA->m_width) * 3 + 1] = sum_g / (blurRadius * 2 + 1);
- dst_data[(x + y * M_IMGDATA->m_width) * 3 + 2] = sum_b / (blurRadius * 2 + 1);
- if(src_alpha)
- dst_alpha[x + y * M_IMGDATA->m_width] = sum_a / (blurRadius * 2 + 1);
+ dst = dst_data + (x + y * M_IMGDATA->m_width) * 3;
+ dst[0] = (unsigned char)(sum_r / blurArea);
+ dst[1] = (unsigned char)(sum_g / blurArea);
+ dst[2] = (unsigned char)(sum_b / blurArea);
+ if ( src_alpha )
+ dst_alpha[x + y * M_IMGDATA->m_width] = (unsigned char)(sum_a / blurArea);
}
}
{
for (int i = 0; i < width; i+=3)
{
- if ((source_data[i] != r) &&
- (source_data[i+1] != g) &&
+ if ((source_data[i] != r) ||
+ (source_data[i+1] != g) ||
(source_data[i+2] != b))
{
memcpy( target_data+i, source_data+i, 3 );
return M_IMGDATA->m_data[pos+2];
}
-bool wxImage::Ok() const
+bool wxImage::IsOk() const
{
// image of 0 width or height can't be considered ok - at least because it
// causes crashes in ConvertToBitmap() if we don't catch it in time
projects / wxWidgets.git / blobdiff