C++函数优化

Question

我有一个函数，如下所示，它被调用了很多次，这使得我的程序运行缓慢。有什么方法可以优化它吗？例如使用SIMD指令或其他技术。getray()函数用于从预先计算的查找表中检索给定的向量3查询。在Visual-studio-2013下编译，目标配置为x64机器。

顺便说一句，多次调用此函数的for循环已经通过使用OpenMP进行了优化。

非常感谢。

bool warpPlanarHomography(
const Eigen::Matrix3d& H_camera2_camera1
, const cv::Mat& image1
, const cv::Mat& image2
, FisheyeCameraUnified& cam1
, FisheyeCameraUnified& cam2
, const Eigen::Vector2i& patchCenter
, const int patchSize
, Eigen::Matrix<unsigned char, 7, 7>& patch1)
{
const int patchSize_2 = 3;
for (int v = 0; v < patchSize; ++v) // row
{
    for (int u = 0; u < patchSize; ++u)
    {
        Eigen::Vector2i p1 = Eigen::Vector2i(u - patchSize_2, v - patchSize_2).cast<int>() + patchCenter;

        if (p1(0, 0) < 0 || p1(1, 0) < 0 || p1(0, 0) >= image1.cols || p1(1, 0) >= image1.rows) return false;

        Eigen::Vector3d ray1;
        cam1.getRay(p1(1, 0), p1(0, 0), ray1);
        Eigen::Vector2d p2;
        if (!cam2.project(H_camera2_camera1 * ray1, p2))
        {
            return false;
        }
        if (p2.x() < 0.0 || p2.x() >= image2.cols - 1 ||
            p2.y() < 0.0 || p2.y() >= image2.rows - 1)
        {
            return false;
        }
        getInterpolatedPixel(image2, p2, &patch1(v, u));
    }
}
return true;
}

，其中的项目函数如下所示

bool FisheyeCameraUnified::project(const Eigen::Vector3d& ray, Eigen::Vector2d& pt)
{
    double fx, fy, cx, cy, xi;
    fx = m_K(0, 0);
    fy = m_K(1, 1);
    cx = m_K(0, 2);
    cy = m_K(1, 2);
    xi = m_xi;

    double d = ray.norm();
    double rz = 1.0 / (ray(2) + xi * d);

    // Project the scene point to the normalized plane.
    Eigen::Vector2d m_d(ray(0) * rz, ray(1) * rz);

    // Apply the projection matrix.
    pt(0) = fx * m_d(0) + cx;
    pt(1) = fy * m_d(1) + cy;
    return true;
}

和getInterpolatedPixel()函数如下

void getInterpolatedPixel(const cv::Mat& image, const Eigen::Vector2d& coords, unsigned char* pixel)
{
    int ix = static_cast<int>(coords.x());
    int iy = static_cast<int>(coords.y());
    double dx = coords.x() - ix;
    double dy = coords.y() - iy;
    double dxdy = dx * dy;

    const double w00 = 1.0 - dx - dy + dxdy;
    const double w01 = dx - dxdy;
    const double w10 = dy - dxdy;
    const double w11 = dxdy;

    const unsigned char* p00 = image.data + iy * image.step.p[0] + ix * image.channels();
    const unsigned char* p01 = p00 + image.channels();
    const unsigned char* p10 = p00 + image.step.p[0];
    const unsigned char* p11 = p10 + image.channels();

    for (int i = 0; i < image.channels(); ++i)
    {
        double value = w11 * p11[i] + w10 * p10[i] + w01 * p01[i] + w00 * p00[i];
        pixel[i] = cv::saturate_cast<unsigned char>(value);
    }
}

Answer 1

1. 衡量哪里是瓶颈，并尝试首先优化那个地方，
2. 你能用float代替double
3. what是m_K(0, 0)，m_K(1, 1)...如果图像只能有特定数量的通道(1，3，4是典型的numbers)
4. call for (int i = 0; i < image.channels(); ++i) image.channels()只有一次，以后使用存储值)，您能用numbers)
5. callfor (int i = 0; i < image.channels(); ++i)image.channels()替换它吗？
6. 尝试将inline修改器添加到小函数

中

Answer 2

除了其他更广泛关注的答案之外，还应该考虑这一点。

因为getInterpolatedPixel是在一个紧密的循环中使用的，所以我把重点放在了减少函数调用上：

void getInterpolatedPixel(const cv::Mat& image, const Eigen::Vector2d& coords, unsigned char* pixel)
{
    //save two function calls here
    double dx = coords.x();
    double dy = coords.y();
    int ix = static_cast<int>(dx);
    int iy = static_cast<int>(dy);
    dx -= ix;
    dy -= iy;
    //make this const
    const double dxdy = dx * dy;

    const double w00 = 1.0 - dx - dy + dxdy;
    const double w01 = dx - dxdy;
    const double w10 = dy - dxdy;
    const double w11 = dxdy;

    //cache image.channels()
    const int channels = image.channels();

    const unsigned char* p00 = image.data + iy * image.step.p[0] + ix * channels;
    const unsigned char* p01 = p00 + channels;
    const unsigned char* p10 = p00 + image.step.p[0];
    const unsigned char* p11 = p10 + channels;

    for (int i = 0; i < channels; ++i)
    {
        double value = w11 * p11[i] + w10 * p10[i] + w01 * p01[i] + w00 * p00[i];
        pixel[i] = cv::saturate_cast<unsigned char>(value);
    }
}