void ConvertColor_BGR2GRAY_BT709_simd(const cv::Mat& src, cv::Mat& dst)
{
CV_Assert(CV_8UC3 == src.type());
cv::Size sz = src.size();
dst.create(sz, CV_8UC1);
#ifdef HAVE_SSE
// __m128i ssse3_blue_indices_0 = _mm_set_epi8(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 15, 12, 9, 6, 3, 0);
// __m128i ssse3_blue_indices_1 = _mm_set_epi8(-1, -1, -1, -1, -1, 14, 11, 8, 5, 2, -1, -1, -1, -1, -1, -1);
// __m128i ssse3_blue_indices_2 = _mm_set_epi8(13, 10, 7, 4, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1);
// __m128i ssse3_green_indices_0 = _mm_set_epi8(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 13, 10, 7, 4, 1);
// __m128i ssse3_green_indices_1 = _mm_set_epi8(-1, -1, -1, -1, -1, 15, 12, 9, 6, 3, 0, -1, -1, -1, -1, -1);
// __m128i ssse3_green_indices_2 = _mm_set_epi8(14, 11, 8, 5, 2, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1);
__m128i ssse3_red_indices_0 = _mm_set_epi8(-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 14, 11, 8, 5, 2);
__m128i ssse3_red_indices_1 = _mm_set_epi8(-1, -1, -1, -1, -1, -1, 13, 10, 7, 4, 1, -1, -1, -1, -1, -1);
__m128i ssse3_red_indices_2 = _mm_set_epi8(15, 12, 9, 6, 3, 0, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1);
#endif
for (int y = 0; y < sz.height; y++)
{
const uchar *psrc = src.ptr<uchar>(y);
uchar *pdst = dst.ptr<uchar>(y);
int x = 0;
#ifdef HAVE_SSE
// Here is 16 times unrolled loop for vector processing
for (; x <= sz.width - 16; x += 16)
{
__m128i chunk0 = _mm_loadu_si128((const __m128i*)(psrc + x*3 + 16*0));
__m128i chunk1 = _mm_loadu_si128((const __m128i*)(psrc + x*3 + 16*1));
__m128i chunk2 = _mm_loadu_si128((const __m128i*)(psrc + x*3 + 16*2));
__m128i red = _mm_or_si128(_mm_or_si128(_mm_shuffle_epi8(chunk0, ssse3_red_indices_0),
_mm_shuffle_epi8(chunk1, ssse3_red_indices_1)),
_mm_shuffle_epi8(chunk2, ssse3_red_indices_2));
/* ??? */
_mm_storeu_si128((__m128i*)(pdst + x), red);
}
#endif
// Process leftover pixels
for (; x < sz.width; x++)
{
/* ??? */
}
}
// ! Remove this before writing your optimizations !
ConvertColor_BGR2GRAY_BT709_fpt(src, dst);
}
void skeletonize(const cv::Mat &input, cv::Mat &output, bool save_images)
{
TS(total);
TS(imwrite_0);
if (save_images) cv::imwrite("0-input.png", input);
TE(imwrite_0);
// Convert to grayscale my
cv::Mat gray_image_my;
ConvertColor_BGR2GRAY_BT709_fpt(input, gray_image_my);
if (save_images) cv::imwrite("1-convertcolor_my.png", gray_image_my);
// Convert to grayscale my
cv::Mat gray_image;
ConvertColor_BGR2GRAY_BT709(input, gray_image);
if (save_images) cv::imwrite("1-convertcolor.png", gray_image);
// Downscale input image
cv::Mat small_image;
cv::Size small_size(input.cols / 1.5, input.rows / 1.5);
ImageResize(gray_image, small_image, small_size);
if (save_images) cv::imwrite("2-resize.png", small_image);
// Binarization and inversion
cv::threshold(small_image, small_image, 128, 255, cv::THRESH_BINARY_INV);
if (save_images) cv::imwrite("3-threshold.png", small_image);
// Thinning
cv::Mat thinned_image;
GuoHallThinning(small_image, thinned_image);
if (save_images) cv::imwrite("4-thinning.png", thinned_image);
// Back inversion
output = 255 - thinned_image;
if (save_images) cv::imwrite("5-output.png", output);
TE(total);
}
