测试设备: 小米11, QCOM888.
使用 NDK-r22 编译器. 使用 OpenCV 的 Mat, imread/imwrite 等基础设施,以及作为对照比较性能。
使用 C++ 模板技术: 由于确定了是 RGB 因此编译器确定通道数量为3;同时想支持 BGR,因此增加 bIdx 这一模板参数。
测试图片: W=7680, H=4320,3通道。
RGB 转 Gray 的公式是 Gray = R2Y * R + G2Y * G + B2Y * B, 其中
R2Y = 0.299;
G2Y = 0.587;
B2Y = 0.114;
template<int bIdx> void cvtcolor_bgr_to_gray(const cv::Mat& src, cv::Mat& dst) { if (src.depth() != CV_8U) { CV_Error(cv::Error::StsBadArg, "only support uchar type"); } if (src.channels() != 3) { CV_Error(cv::Error::StsBadArg, "src is not 3 channels"); } if (bIdx != 0 && bIdx != 2) { CV_Error(cv::Error::StsBadArg, "bIdx should be 0 or 2"); } const int srcw = src.cols; const int srch = src.rows; const int channels = 3; dst.create(src.size(), CV_8UC1); for (int i = 0; i < srch; i++) { for (int j = 0; j < srcw; j++) { uchar b = src.ptr(i, j)[bIdx]; uchar g = src.ptr(i, j)[1]; uchar r = src.ptr(i, j)[2-bIdx]; dst.ptr(i, j)[0] = (0.299*r + 0.587*g + 0.114*b); } } }
加速策略包括:
naive 实现和最优实现的速度差很多,同时也要注意大小核心的性能相差很多:
v4 的代码:
template<int bIdx = 0> void cvtcolor_bgr_to_gray_v4(const cv::Mat& src, cv::Mat& dst) { if (src.depth() != CV_8U) { CV_Error(cv::Error::StsBadArg, "only support uchar type"); } if (src.channels() != 3) { CV_Error(cv::Error::StsBadArg, "src is not 3 channels"); } if (bIdx != 0 && bIdx != 2) { CV_Error(cv::Error::StsBadArg, "bIdx should be 0 or 2"); } const int srcw = src.cols; const int srch = src.rows; const int channels = 3; dst.create(src.size(), CV_8UC1); const uchar* src_line = src.data; const int src_step = src.step1(); uchar* dst_line = dst.data; const int dst_step = dst.step1(); const uint8_t R2Y_fx_u8 = 77; // 0.299 * (1 >> 8) const uint8_t G2Y_fx_u8 = 150; // 0.587 * (1 >> 8) const uint8_t B2Y_fx_u8 = 29; // 0.114 * (1 >> 8) const uint16_t R2Y_fx = R2Y_fx_u8; const uint16_t G2Y_fx = G2Y_fx_u8; const uint16_t B2Y_fx = B2Y_fx_u8; const uint16_t shift = 8; const uint16_t half_fx = (1 << (shift - 1)); #if __ARM_NEON uint8x8_t v_R2Y_fx = vdup_n_u8(R2Y_fx_u8); uint8x8_t v_G2Y_fx = vdup_n_u8(G2Y_fx_u8); uint8x8_t v_B2Y_fx = vdup_n_u8(B2Y_fx_u8); uint16x8_t v_half_fx = vdupq_n_u16(half_fx); #endif // __ARM_NEON cv::parallel_for_(cv::Range(0, srch), [&](const cv::Range& range) { for (int i = range.start; i < range.end; i++) { const uchar* src_pixel = src_line; uchar* dst_pixel = dst_line; #if __ARM_NEON int nn = srcw >> 3; int remain = srcw - (nn << 3); #else int remain = srcw; #endif // __ARM_NEON #if __ARM_NEON for (int j = 0; j < nn; j++) { uint8x8x3_t v_src = vld3_u8(src_pixel); uint16x8_t v_b2p = vmull_u8(v_src.val[0], v_B2Y_fx); uint16x8_t v_g2p = vmull_u8(v_src.val[1], v_G2Y_fx); uint16x8_t v_r2p = vmull_u8(v_src.val[2], v_R2Y_fx); uint16x8_t v_gray = vaddq_u16(vaddq_u16(vaddq_u16(v_b2p, v_g2p), v_r2p), v_half_fx); uint8x8_t v_gray_u8 = vshrn_n_u16(v_gray, 8); vst1_u8(dst_pixel, v_gray_u8); src_pixel += 8*channels; dst_pixel += 8; } #endif // __ARM_NEON for (; remain >= 0; remain--) { uchar b = src_pixel[0]; uchar g = src_pixel[1]; uchar r = src_pixel[2]; //uint16_t gray = (77 * r + 151 * g + 28 * b + (1 << 7)) >> 8; uint16_t gray = (R2Y_fx * r + G2Y_fx * g + B2Y_fx * b + half_fx) >> shift; *dst_pixel++ = cv::saturate_cast<uint8_t>(gray); src_pixel += channels; } src_line += src_step; dst_line += dst_step; } }); }