#include vector#include cstringnamespace CAROTENE_NS bool isMatchTemplateSupportedAVICCV_8U &tmplSize return isSupportedConfiguration && tmplSizewidth

以下是使用NEON和OpenMP对程序进行优化的示例代码：

#include #include #include <omp.h> #include <arm_neon.h>

namespace CAROTENE_NS {

bool isMatchTemplateSupported(AVICCV_8U &tmplSize) { return isSupportedConfiguration() && tmplSize.width >= 8 && (tmplSize.width * tmplSize.height) <= 256; }

void matchTemplate(const Size2D &srcSize, const u8 * srcBase, ptrdiff_t srcStride, const Size2D &tmplSize, const u8 * tmplBase, ptrdiff_t tmplStride, f32 * dstBase, ptrdiff_t dstStride, bool normalize) { internal::assertSupportedConfiguration(isMatchTemplateSupported(tmplSize));

const size_t tmplW = tmplSize.width;
const size_t tmplH = tmplSize.height;
const size_t dstW  = srcSize.width  - tmplSize.width  + 1;
const size_t dstH  = srcSize.height - tmplSize.height + 1;

// Calculate the number of threads to use
int numThreads = omp_get_max_threads();

// Initialize the vector for storing temporary results
std::vector<std::vector<f32>> threadResults(numThreads, std::vector<f32>(dstW));

// Template correlation part
#pragma omp parallel for schedule(dynamic)
for (int r = 0; r < dstH; ++r) {
    // Get the thread ID
    int threadID = omp_get_thread_num();

    // Get the temporary result vector for this thread
    std::vector<f32>& result = threadResults[threadID];

    const size_t tmplroiw = tmplW & ~7u;
    const size_t dstride = dstStride >> 2;

    f32 *corr = dstBase + r * dstride;
    const u8  *imgrrow = srcBase + r * srcStride;

    int c = 0;
    for (; c < dstW; ++c) {
        u32 dot = 0;
        uint32x4_t vdot = vmovq_n_u32(0);
        const u8  *img = imgrrow;
        const u8 *tmpl = tmplBase;

        for (size_t i = 0; i < tmplH; ++i, tmpl += tmplStride, img += srcStride) {
            size_t j = 0;
            for (; j < tmplroiw; j += 8) {
                uint8x8_t vtmpl = vld1_u8(tmpl + j);
                uint8x8_t vimg = vld1_u8(img + j + c);
                uint16x8_t vd = vmull_u8(vtmpl, vimg);
                vdot = vpadalq_u16(vdot, vd);
            }
            for (; j < tmplW; ++j)
                dot += tmpl[j] * img[j + c];
        }
        u32 wdot[2];
        vst1_u32(wdot, vpadd_u32(vget_low_u32(vdot), vget_high_u32(vdot)));
        dot += wdot[0] + wdot[1];
        result[c] = (f32)dot;
    }

    // Copy the temporary result vector to the final result array
    memcpy(corr, result.data(), dstW * sizeof(f32));
}

if (normalize) {
    f32 tn = std::sqrt((f32)normL2(tmplSize, tmplBase, tmplStride));

    size_t iw = srcSize.width + 1;
    size_t ih = srcSize.height + 1;
    std::vector<f64> _sqsum(iw * ih);
    f64 *sqsum = &_sqsum[0];
    memset(sqsum, 0, iw * sizeof(f64));
    for (size_t i = 1; i < ih; ++i)
        sqsum[iw * i] = 0.;
    sqrIntegral(srcSize, srcBase, srcStride, sqsum + iw + 1, iw * sizeof(f64));

    #pragma omp parallel for schedule(dynamic)
    for (size_t i = 0; i < dstH; ++i) {
        f32 *result = internal::getRowPtr(dstBase, dstStride, i);
        for (size_t j = 0; j < dstW; ++j) {
            double s2 = sqsum[iw * i + j] +
                        sqsum[iw * (i + tmplSize.height) + j + tmplSize.width] -
                        sqsum[iw * (i + tmplSize.height) + j] -
                        sqsum[iw * i + j + tmplSize.width];

            result[j] /= tn * std::sqrt(s2);
        }
    }
}

}

} // namespace CAROTENE_N