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@ -450,31 +450,184 @@ public: |
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const sift_wt* currptr = img.ptr<sift_wt>(r); |
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const sift_wt* prevptr = prev.ptr<sift_wt>(r); |
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const sift_wt* nextptr = next.ptr<sift_wt>(r); |
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int c = SIFT_IMG_BORDER; |
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for( int c = SIFT_IMG_BORDER; c < cols-SIFT_IMG_BORDER; c++) |
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#if CV_SIMD && !(DoG_TYPE_SHORT) |
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const int vecsize = v_float32::nlanes; |
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for( ; c <= cols-SIFT_IMG_BORDER - vecsize; c += vecsize) |
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{ |
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v_float32 val = vx_load(&currptr[c]); |
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v_float32 _00,_01,_02; |
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v_float32 _10, _12; |
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v_float32 _20,_21,_22; |
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v_float32 vmin,vmax; |
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v_float32 cond = v_abs(val) > vx_setall_f32((float)threshold); |
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if (!v_check_any(cond)) |
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{ |
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continue; |
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} |
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_00 = vx_load(&currptr[c-step-1]); _01 = vx_load(&currptr[c-step]); _02 = vx_load(&currptr[c-step+1]); |
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_10 = vx_load(&currptr[c -1]); _12 = vx_load(&currptr[c +1]); |
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_20 = vx_load(&currptr[c+step-1]); _21 = vx_load(&currptr[c+step]); _22 = vx_load(&currptr[c+step+1]); |
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vmax = v_max(v_max(v_max(_00,_01),v_max(_02,_10)),v_max(v_max(_12,_20),v_max(_21,_22))); |
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vmin = v_min(v_min(v_min(_00,_01),v_min(_02,_10)),v_min(v_min(_12,_20),v_min(_21,_22))); |
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v_float32 condp = cond & (val > vx_setall_f32(0)) & (val >= vmax); |
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v_float32 condm = cond & (val < vx_setall_f32(0)) & (val <= vmin); |
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cond = condp | condm; |
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if (!v_check_any(cond)) |
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{ |
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continue; |
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} |
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_00 = vx_load(&prevptr[c-step-1]); _01 = vx_load(&prevptr[c-step]); _02 = vx_load(&prevptr[c-step+1]); |
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_10 = vx_load(&prevptr[c -1]); _12 = vx_load(&prevptr[c +1]); |
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_20 = vx_load(&prevptr[c+step-1]); _21 = vx_load(&prevptr[c+step]); _22 = vx_load(&prevptr[c+step+1]); |
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vmax = v_max(v_max(v_max(_00,_01),v_max(_02,_10)),v_max(v_max(_12,_20),v_max(_21,_22))); |
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vmin = v_min(v_min(v_min(_00,_01),v_min(_02,_10)),v_min(v_min(_12,_20),v_min(_21,_22))); |
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condp &= (val >= vmax); |
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condm &= (val <= vmin); |
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cond = condp | condm; |
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if (!v_check_any(cond)) |
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{ |
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continue; |
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} |
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v_float32 _11p = vx_load(&prevptr[c]); |
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v_float32 _11n = vx_load(&nextptr[c]); |
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v_float32 max_middle = v_max(_11n,_11p); |
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v_float32 min_middle = v_min(_11n,_11p); |
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_00 = vx_load(&nextptr[c-step-1]); _01 = vx_load(&nextptr[c-step]); _02 = vx_load(&nextptr[c-step+1]); |
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_10 = vx_load(&nextptr[c -1]); _12 = vx_load(&nextptr[c +1]); |
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_20 = vx_load(&nextptr[c+step-1]); _21 = vx_load(&nextptr[c+step]); _22 = vx_load(&nextptr[c+step+1]); |
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vmax = v_max(v_max(v_max(_00,_01),v_max(_02,_10)),v_max(v_max(_12,_20),v_max(_21,_22))); |
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vmin = v_min(v_min(v_min(_00,_01),v_min(_02,_10)),v_min(v_min(_12,_20),v_min(_21,_22))); |
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condp &= (val >= v_max(vmax,max_middle)); |
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condm &= (val <= v_min(vmin,min_middle)); |
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cond = condp | condm; |
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if (!v_check_any(cond)) |
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{ |
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continue; |
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} |
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int mask = v_signmask(cond); |
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for (int k = 0; k<vecsize;k++) |
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{ |
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if ((mask & (1<<k)) == 0) |
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continue; |
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CV_TRACE_REGION("pixel_candidate_simd"); |
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KeyPoint kpt; |
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int r1 = r, c1 = c+k, layer = i; |
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if( !adjustLocalExtrema(dog_pyr, kpt, o, layer, r1, c1, |
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nOctaveLayers, (float)contrastThreshold, |
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(float)edgeThreshold, (float)sigma) ) |
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continue; |
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float scl_octv = kpt.size*0.5f/(1 << o); |
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float omax = calcOrientationHist(gauss_pyr[o*(nOctaveLayers+3) + layer], |
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Point(c1, r1), |
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cvRound(SIFT_ORI_RADIUS * scl_octv), |
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SIFT_ORI_SIG_FCTR * scl_octv, |
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hist, n); |
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float mag_thr = (float)(omax * SIFT_ORI_PEAK_RATIO); |
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for( int j = 0; j < n; j++ ) |
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{ |
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int l = j > 0 ? j - 1 : n - 1; |
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int r2 = j < n-1 ? j + 1 : 0; |
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if( hist[j] > hist[l] && hist[j] > hist[r2] && hist[j] >= mag_thr ) |
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{ |
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float bin = j + 0.5f * (hist[l]-hist[r2]) / (hist[l] - 2*hist[j] + hist[r2]); |
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bin = bin < 0 ? n + bin : bin >= n ? bin - n : bin; |
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kpt.angle = 360.f - (float)((360.f/n) * bin); |
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if(std::abs(kpt.angle - 360.f) < FLT_EPSILON) |
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kpt.angle = 0.f; |
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kpts_.push_back(kpt); |
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} |
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} |
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} |
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} |
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#endif //CV_SIMD && !(DoG_TYPE_SHORT)
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// vector loop reminder, better predictibility and less branch density
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for( ; c < cols-SIFT_IMG_BORDER; c++) |
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{ |
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sift_wt val = currptr[c]; |
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if (std::abs(val) <= threshold) |
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continue; |
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sift_wt _00,_01,_02; |
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sift_wt _10, _12; |
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sift_wt _20,_21,_22; |
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_00 = currptr[c-step-1]; _01 = currptr[c-step]; _02 = currptr[c-step+1]; |
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_10 = currptr[c -1]; _12 = currptr[c +1]; |
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_20 = currptr[c+step-1]; _21 = currptr[c+step]; _22 = currptr[c+step+1]; |
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bool calculate = false; |
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if (val > 0) |
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{ |
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sift_wt vmax = std::max(std::max(std::max(_00,_01),std::max(_02,_10)),std::max(std::max(_12,_20),std::max(_21,_22))); |
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if (val >= vmax) |
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{ |
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_00 = prevptr[c-step-1]; _01 = prevptr[c-step]; _02 = prevptr[c-step+1]; |
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_10 = prevptr[c -1]; _12 = prevptr[c +1]; |
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_20 = prevptr[c+step-1]; _21 = prevptr[c+step]; _22 = prevptr[c+step+1]; |
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vmax = std::max(std::max(std::max(_00,_01),std::max(_02,_10)),std::max(std::max(_12,_20),std::max(_21,_22))); |
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if (val >= vmax) |
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{ |
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_00 = nextptr[c-step-1]; _01 = nextptr[c-step]; _02 = nextptr[c-step+1]; |
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_10 = nextptr[c -1]; _12 = nextptr[c +1]; |
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_20 = nextptr[c+step-1]; _21 = nextptr[c+step]; _22 = nextptr[c+step+1]; |
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vmax = std::max(std::max(std::max(_00,_01),std::max(_02,_10)),std::max(std::max(_12,_20),std::max(_21,_22))); |
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if (val >= vmax) |
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{ |
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sift_wt _11p = prevptr[c], _11n = nextptr[c]; |
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calculate = (val >= std::max(_11p,_11n)); |
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} |
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} |
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} |
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} else { // val cant be zero here (first abs took care of zero), must be negative
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sift_wt vmin = std::min(std::min(std::min(_00,_01),std::min(_02,_10)),std::min(std::min(_12,_20),std::min(_21,_22))); |
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if (val <= vmin) |
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{ |
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_00 = prevptr[c-step-1]; _01 = prevptr[c-step]; _02 = prevptr[c-step+1]; |
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_10 = prevptr[c -1]; _12 = prevptr[c +1]; |
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_20 = prevptr[c+step-1]; _21 = prevptr[c+step]; _22 = prevptr[c+step+1]; |
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vmin = std::min(std::min(std::min(_00,_01),std::min(_02,_10)),std::min(std::min(_12,_20),std::min(_21,_22))); |
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if (val <= vmin) |
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{ |
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_00 = nextptr[c-step-1]; _01 = nextptr[c-step]; _02 = nextptr[c-step+1]; |
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_10 = nextptr[c -1]; _12 = nextptr[c +1]; |
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_20 = nextptr[c+step-1]; _21 = nextptr[c+step]; _22 = nextptr[c+step+1]; |
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vmin = std::min(std::min(std::min(_00,_01),std::min(_02,_10)),std::min(std::min(_12,_20),std::min(_21,_22))); |
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if (val <= vmin) |
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{ |
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sift_wt _11p = prevptr[c], _11n = nextptr[c]; |
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calculate = (val <= std::min(_11p,_11n)); |
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} |
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} |
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} |
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} |
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// find local extrema with pixel accuracy
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if( std::abs(val) > threshold && |
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((val > 0 && val >= currptr[c-1] && val >= currptr[c+1] && |
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val >= currptr[c-step-1] && val >= currptr[c-step] && val >= currptr[c-step+1] && |
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val >= currptr[c+step-1] && val >= currptr[c+step] && val >= currptr[c+step+1] && |
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val >= nextptr[c] && val >= nextptr[c-1] && val >= nextptr[c+1] && |
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val >= nextptr[c-step-1] && val >= nextptr[c-step] && val >= nextptr[c-step+1] && |
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val >= nextptr[c+step-1] && val >= nextptr[c+step] && val >= nextptr[c+step+1] && |
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val >= prevptr[c] && val >= prevptr[c-1] && val >= prevptr[c+1] && |
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val >= prevptr[c-step-1] && val >= prevptr[c-step] && val >= prevptr[c-step+1] && |
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val >= prevptr[c+step-1] && val >= prevptr[c+step] && val >= prevptr[c+step+1]) || |
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(val < 0 && val <= currptr[c-1] && val <= currptr[c+1] && |
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val <= currptr[c-step-1] && val <= currptr[c-step] && val <= currptr[c-step+1] && |
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val <= currptr[c+step-1] && val <= currptr[c+step] && val <= currptr[c+step+1] && |
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val <= nextptr[c] && val <= nextptr[c-1] && val <= nextptr[c+1] && |
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val <= nextptr[c-step-1] && val <= nextptr[c-step] && val <= nextptr[c-step+1] && |
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val <= nextptr[c+step-1] && val <= nextptr[c+step] && val <= nextptr[c+step+1] && |
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val <= prevptr[c] && val <= prevptr[c-1] && val <= prevptr[c+1] && |
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val <= prevptr[c-step-1] && val <= prevptr[c-step] && val <= prevptr[c-step+1] && |
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val <= prevptr[c+step-1] && val <= prevptr[c+step] && val <= prevptr[c+step+1]))) |
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if (calculate) |
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{ |
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CV_TRACE_REGION("pixel_candidate"); |
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