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Àï@ð?ü©ñÒMbP? Àÿ@ð?ü©ñÒMbP? Àÿ@ð?ü©ñÒMbP?ÐAð?ü©ñÒMbP?ÐAð?ü©ñÒMbP? ÀAð?ü©ñÒMbP? ÀAð?ü©ñÒMbP?ào@ð?ü©ñÒMbP?à@ð?ü©ñÒMbP?à@ð?ü©ñÒMbP?è‡@ð?ü©ñÒMbP?è‡@ð?ü©ñÒMbP?à@ð?ü©ñÒMbP?à@ð?ü©ñÒMbP?àÿï@ð?ü©ñÒMbP?àÿÿ@ð?ü©ñÒMbP?àÿÿ@ð?ü©ñÒMbP?èÿAð?ü©ñÒMbP?èÿAð?ü©ñÒMbP?àÿAð?ü©ñÒMbP?àÿAð?ü©ñÒMbP? Àï@ð?ü©ñÒMbP? Àÿ@ð?ü©ñÒMbP? Àÿ@ð?ü©ñÒMbP?ÐAð?ü©ñÒMbP?ÐAð?ü©ñÒMbP? ÀAð?ü©ñÒMbP? ÀAð?ü©ñÒMbP?ào@ð?ü©ñÒMbP?à@ð?ü©ñÒMbP?à@ð?ü©ñÒMbP?è‡@ð?ü©ñÒMbP?è‡@ð?ü©ñÒMbP?à@ð?ü©ñÒMbP?à@ð?ü©ñÒMbP?ào@ð?ü©ñÒMbP?àÿÿ@ð?ü©ñÒMbP?àÿÿ@ð?ü©ñÒMbP?èÿAð?ü©ñÒMbP?èÿAð?ü©ñÒMbP?àÿAð?ü©ñÒMbP?àÿAð?ü©ñÒMbP?GPGkÄGPGtIPG±ÉIPG>0JPGIËJPGˆvoid cv::fastNlMeansDenoising(cv::InputArray, cv::OutputArray, float, int, int)/Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/photo/src/denoising.cppvoid cv::fastNlMeansDenoising(cv::InputArray, cv::OutputArray, const std::vector &, int, int, int)!_src.empty()fastNlMeansDenoisinghn == 1 || hn == cnUnsupported depth! Only CV_8U is supported for NORM_L2Unsupported depth! Only CV_8U and CV_16U are supported for NORM_L1Unsupported norm type! Only NORM_L2 and NORM_L1 are supportedvoid cv::fastNlMeansDenoisingColored(cv::InputArray, cv::OutputArray, float, float, int, int)Type of input image should be CV_8UC3 or CV_8UC4!fastNlMeansDenoisingColoredvoid cv::fastNlMeansDenoisingMulti(cv::InputArrayOfArrays, cv::OutputArray, int, int, float, int, int)void cv::fastNlMeansDenoisingMulti(cv::InputArrayOfArrays, cv::OutputArray, int, int, const std::vector &, int, int, int)fastNlMeansDenoisingMultivoid cv::fastNlMeansDenoisingColoredMulti(cv::InputArrayOfArrays, cv::OutputArray, int, int, float, float, int, int)Type of input images should be CV_8UC3!fastNlMeansDenoisingColoredMulti-D OP_CALC_FASTNLMEANS -D TEMPLATE_SIZE=%d -D SEARCH_SIZE=%d -D pixel_t=%s -D int_t=%s -D wlut_t=%s -D weight_t=%s -D convert_weight_t=%s -D sum_t=%s -D convert_sum_t=%s -D BLOCK_COLS=%d -D BLOCK_ROWS=%d -D CTA_SIZE=%d -D TEMPLATE_SIZE2=%d -D SEARCH_SIZE2=%d -D convert_int_t=%s -D cn=%d -D psz=%d -D convert_pixel_t=%s%slong%s%dconvert_long%s -D ABSalmostTemplateWindowSizeSqBinShift >= 0ocl_fastNlMeansDenoising/Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/photo/src/fast_nlmeans_denoising_opencl.hpptemplateWindowSize <= 46340ocl_calcAlmostDist2Weighthn > 0 && hn <= 4calcAlmostDist2Weight-D OP_CALC_WEIGHTS -D FT=%s -D w_t=%s -D wlut_t=%s -D convert_wlut_t=%s%s%s -D DOUBLE_SUPPORTallocator::allocate(size_t n) 'n' exceeds maximum supported sizeInput images vector should not be empty!fastNlMeansDenoisingMultiCheckPreconditionsAll windows sizes should be odd!imgToDenoiseIndex and temporalWindowSize should be chosen corresponding srcImgs size!Input images should have the same size and type!Unsupported number of channels! Only 1, 2, 3, and 4 are supportedfastNlMeansDenoising_src.channels() == pixelInfo::channelsFastNlMeansDenoisingInvoker/Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/photo/src/fast_nlmeans_denoising_invoker.hpptemplate_window_size_ <= 46340Unsupported image format! Only CV_8U, CV_8UC2, CV_8UC3 and CV_8UC4 are supportedfastNlMeansDenoisingMulti_srcImgs.size() > 0FastNlMeansMultiDenoisingInvoker/Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/photo/src/fast_nlmeans_multi_denoising_invoker.hppsrcImgs[0].channels() == 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channelsvirtual void cv::MergeDebevecImpl::process(cv::InputArrayOfArrays, cv::OutputArray, cv::InputArray)MergeMertensnamecontrast_weightsaturation_weightexposure_weightNo element name has been givenoperator<</Users/build/buildAgent/work/b5d3ba53e49a4b81/build-victor-deps/build-opencv/opencv/modules/core/include/opencv2/core/persistence.hppn.isString() && String(n) == namereadvirtual void cv::MergeMertensImpl::process(cv::InputArrayOfArrays, cv::OutputArrayOfArrays, cv::InputArray, cv::InputArray)virtual void cv::MergeMertensImpl::process(cv::InputArrayOfArrays, cv::OutputArray)channels == 1 || channels == 3MergeRobertsonvirtual void cv::MergeRobertsonImpl::process(cv::InputArrayOfArrays, cv::OutputArray, cv::InputArray, cv::InputArray)response.rows == LDR_SIZE && response.cols == 1 && response.channels() == channelsvirtual void cv::MergeRobertsonImpl::process(cv::InputArrayOfArrays, cv::OutputArray, 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0 && minyd >= 0 && maxxd <= dest.rows && maxyd <= dest.colsseamlessClonevoid cv::colorChange(cv::InputArray, cv::InputArray, cv::OutputArray, float, float, float)void cv::illuminationChange(cv::InputArray, cv::InputArray, cv::OutputArray, float, float)void cv::textureFlattening(cv::InputArray, cv::InputArray, cv::OutputArray, float, float, int)) ÑXA,^0 0Aa`20AbDpÑXAdWäAˆeYëA¼eðY;AÔezPLRx›4$ø•ÿÿÿÿÿÿ) ôÿÿÿÿÿÿA†C PƒŒŽ4\ðµÿÿÿÿÿÿ0ÃöÿÿÿÿÿÿA†C NƒŒŽ4”èÇÿÿÿÿÿÿ0øÿÿÿÿÿÿA†C NƒŒŽ4ÌàÙÿÿÿÿÿÿpKùÿÿÿÿÿÿA†C PƒŒŽ,(ìÿÿÿÿÿÿäúÿÿÿÿÿÿA†C Bƒ44èíÿÿÿÿÿÿë“úÿÿÿÿÿÿA†C GƒŒŽ,l îÿÿÿÿÿÿ;súÿÿÿÿÿÿA†C Bƒ'^-^-^-^-^-ÿ]-÷]-é]-à]-×](-n]-J](-Ñ\-ª\(-1\- \(-‘[-j[(-ñZ-ÊZ(-LZ-%Z/- Z/-çY-ßY/-±Y(-PY-ðX-èX-àX-ÑX(-xX-WX(-ÞW-ºW(--z>(->-í=(-”=-s=(-÷<-Ð<-Ä<&-¬8--Z8-˜7-E7-6-Z6'-ñ5-_5-25-5*-q4)-i4+-,4-4*-k3)-c3-K3*-¢2)-š2 -Ž2\2-T2-L2-42-*2(-Á1-—1-1(-.1-1-ø0(-™0-o0-Y0-M0(-ø/-Ô/-Ç/(-n/-J/-7/-+/(-».-‘.-„.(-.-Ø--É--Á--¹--±--©--¡----j-(---Ú,(-q,-J,(-ä+-½+(-d+-C+(-Ï*-¨*-œ*%-|&--*&-h%-%-h$-2$'-É#-7#- #-ò"*-I")-A"+-"-ì!*-C!)-;!-#!*-z )-r -f 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#1/36 1548786669 501 20 100644 9924 ` opencl_kernels_photo.cpp.oÏúíþ° 8x$Ðx$__text__TEXTÐ€__cstring__TEXTI$Ð__data__DATAP$( &H&$ h&x&$Pphotonlmeans#ifdef cl_amd_printf #pragma OPENCL_EXTENSION cl_amd_printf:enable #endif #ifdef DOUBLE_SUPPORT #ifdef cl_amd_fp64 #pragma OPENCL EXTENSION cl_amd_fp64:enable #elif defined cl_khr_fp64 #pragma OPENCL EXTENSION cl_khr_fp64:enable #endif #endif #ifdef OP_CALC_WEIGHTS __kernel void calcAlmostDist2Weight(__global wlut_t * almostDist2Weight, int almostMaxDist, FT almostDist2ActualDistMultiplier, int fixedPointMult, w_t den, FT WEIGHT_THRESHOLD) { int almostDist = get_global_id(0); if (almostDist < almostMaxDist) { FT dist = almostDist * almostDist2ActualDistMultiplier; #ifdef ABS w_t w = exp((w_t)(-dist*dist) * den); #else w_t w = exp((w_t)(-dist) * den); #endif wlut_t weight = convert_wlut_t(fixedPointMult * (isnan(w) ? (w_t)1.0 : w)); almostDist2Weight[almostDist] = weight < (wlut_t)(WEIGHT_THRESHOLD * fixedPointMult) ? (wlut_t)0 : weight; } } #elif defined OP_CALC_FASTNLMEANS #define noconvert #define SEARCH_SIZE_SQ (SEARCH_SIZE * SEARCH_SIZE) inline int calcDist(pixel_t a, pixel_t b) { #ifdef ABS int_t retval = convert_int_t(abs_diff(a, b)); #else int_t diff = convert_int_t(a) - convert_int_t(b); int_t retval = diff * diff; #endif #if cn == 1 return retval; #elif cn == 2 return retval.x + retval.y; #elif cn == 3 return retval.x + retval.y + retval.z; #elif cn == 4 return retval.x + retval.y + retval.z + retval.w; #else #error "cn should be either 1, 2, 3 or 4" #endif } #ifdef ABS inline int calcDistUpDown(pixel_t down_value, pixel_t down_value_t, pixel_t up_value, pixel_t up_value_t) { return calcDist(down_value, down_value_t) - calcDist(up_value, up_value_t); } #else inline int calcDistUpDown(pixel_t down_value, pixel_t down_value_t, pixel_t up_value, pixel_t up_value_t) { int_t A = convert_int_t(down_value) - convert_int_t(down_value_t); int_t B = convert_int_t(up_value) - convert_int_t(up_value_t); int_t retval = (A - B) * (A + B); #if cn == 1 return retval; #elif cn == 2 return retval.x + retval.y; #elif cn == 3 return retval.x + retval.y + retval.z; #elif cn == 4 return retval.x + retval.y + retval.z + retval.w; #else #error "cn should be either 1, 2, 3 or 4" #endif } #endif #define COND if (x == 0 && y == 0) inline void calcFirstElementInRow(__global const uchar * src, int src_step, int src_offset, __local int * dists, int y, int x, int id, __global int * col_dists, __global int * up_col_dists) { y -= TEMPLATE_SIZE2; int sx = x - SEARCH_SIZE2, sy = y - SEARCH_SIZE2; int col_dists_current_private[TEMPLATE_SIZE]; for (int i = id; i < SEARCH_SIZE_SQ; i += CTA_SIZE) { int dist = 0, value; __global const pixel_t * src_template = (__global const pixel_t *)(src + mad24(sy + i / SEARCH_SIZE, src_step, mad24(psz, sx + i % SEARCH_SIZE, src_offset))); __global const pixel_t * src_current = (__global const pixel_t *)(src + mad24(y, src_step, mad24(psz, x, src_offset))); __global int * col_dists_current = col_dists + i * TEMPLATE_SIZE; #pragma unroll for (int j = 0; j < TEMPLATE_SIZE; ++j) col_dists_current_private[j] = 0; for (int ty = 0; ty < TEMPLATE_SIZE; ++ty) { #pragma unroll for (int tx = -TEMPLATE_SIZE2; tx <= TEMPLATE_SIZE2; ++tx) { value = calcDist(src_template[tx], src_current[tx]); col_dists_current_private[tx + TEMPLATE_SIZE2] += value; dist += value; } src_current = (__global const pixel_t *)((__global const uchar *)src_current + src_step); src_template = (__global const pixel_t *)((__global const uchar *)src_template + src_step); } #pragma unroll for (int j = 0; j < TEMPLATE_SIZE; ++j) col_dists_current[j] = col_dists_current_private[j]; dists[i] = dist; up_col_dists[0 + i] = col_dists[TEMPLATE_SIZE - 1]; } } inline void calcElementInFirstRow(__global const uchar * src, int src_step, int src_offset, __local int * dists, int y, int x0, int x, int id, int first, __global int * col_dists, __global int * up_col_dists) { x += TEMPLATE_SIZE2; y -= TEMPLATE_SIZE2; int sx = x - SEARCH_SIZE2, sy = y - SEARCH_SIZE2; for (int i = id; i < SEARCH_SIZE_SQ; i += CTA_SIZE) { __global const pixel_t * src_current = (__global const pixel_t *)(src + mad24(y, src_step, mad24(psz, x, src_offset))); __global const pixel_t * src_template = (__global const pixel_t *)(src + mad24(sy + i / SEARCH_SIZE, src_step, mad24(psz, sx + i % SEARCH_SIZE, src_offset))); __global int * col_dists_current = col_dists + TEMPLATE_SIZE * i; int col_dist = 0; #pragma unroll for (int ty = 0; ty < TEMPLATE_SIZE; ++ty) { col_dist += calcDist(src_current[0], src_template[0]); src_current = (__global const pixel_t *)((__global const uchar *)src_current + src_step); src_template = (__global const pixel_t *)((__global const uchar *)src_template + src_step); } dists[i] += col_dist - col_dists_current[first]; col_dists_current[first] = col_dist; up_col_dists[mad24(x0, SEARCH_SIZE_SQ, i)] = col_dist; } } inline void calcElement(__global const uchar * src, int src_step, int src_offset, __local int * dists, int y, int x0, int x, int id, int first, __global int * col_dists, __global int * up_col_dists) { int sx = x + TEMPLATE_SIZE2; int sy_up = y - TEMPLATE_SIZE2 - 1; int sy_down = y + TEMPLATE_SIZE2; pixel_t up_value = *(__global const pixel_t *)(src + mad24(sy_up, src_step, mad24(psz, sx, src_offset))); pixel_t down_value = *(__global const pixel_t *)(src + mad24(sy_down, src_step, mad24(psz, sx, src_offset))); sx -= SEARCH_SIZE2; sy_up -= SEARCH_SIZE2; sy_down -= SEARCH_SIZE2; for (int i = id; i < SEARCH_SIZE_SQ; i += CTA_SIZE) { int wx = i % SEARCH_SIZE, wy = i / SEARCH_SIZE; pixel_t up_value_t = *(__global const pixel_t *)(src + mad24(sy_up + wy, src_step, mad24(psz, sx + wx, src_offset))); pixel_t down_value_t = *(__global const pixel_t *)(src + mad24(sy_down + wy, src_step, mad24(psz, sx + wx, src_offset))); __global int * col_dists_current = col_dists + mad24(i, TEMPLATE_SIZE, first); __global int * up_col_dists_current = up_col_dists + mad24(x0, SEARCH_SIZE_SQ, i); int col_dist = up_col_dists_current[0] + calcDistUpDown(down_value, down_value_t, up_value, up_value_t); dists[i] += col_dist - col_dists_current[0]; col_dists_current[0] = col_dist; up_col_dists_current[0] = col_dist; } } inline void convolveWindow(__global const uchar * src, int src_step, int src_offset, __local int * dists, __global const wlut_t * almostDist2Weight, __global uchar * dst, int dst_step, int dst_offset, int y, int x, int id, __local weight_t * weights_local, __local sum_t * weighted_sum_local, int almostTemplateWindowSizeSqBinShift) { int sx = x - SEARCH_SIZE2, sy = y - SEARCH_SIZE2; weight_t weights = (weight_t)0; sum_t weighted_sum = (sum_t)0; for (int i = id; i < SEARCH_SIZE_SQ; i += CTA_SIZE) { int src_index = mad24(sy + i / SEARCH_SIZE, src_step, mad24(i % SEARCH_SIZE + sx, psz, src_offset)); sum_t src_value = convert_sum_t(*(__global const pixel_t *)(src + src_index)); int almostAvgDist = dists[i] >> almostTemplateWindowSizeSqBinShift; weight_t weight = convert_weight_t(almostDist2Weight[almostAvgDist]); weights += weight; weighted_sum += (sum_t)weight * src_value; } weights_local[id] = weights; weighted_sum_local[id] = weighted_sum; barrier(CLK_LOCAL_MEM_FENCE); for (int lsize = CTA_SIZE >> 1; lsize > 2; lsize >>= 1) { if (id < lsize) { int id2 = lsize + id; weights_local[id] += weights_local[id2]; weighted_sum_local[id] += weighted_sum_local[id2]; } barrier(CLK_LOCAL_MEM_FENCE); } if (id == 0) { int dst_index = mad24(y, dst_step, mad24(psz, x, dst_offset)); sum_t weighted_sum_local_0 = weighted_sum_local[0] + weighted_sum_local[1] + weighted_sum_local[2] + weighted_sum_local[3]; weight_t weights_local_0 = weights_local[0] + weights_local[1] + weights_local[2] + weights_local[3]; *(__global pixel_t *)(dst + dst_index) = convert_pixel_t(weighted_sum_local_0 / (sum_t)weights_local_0); } } __kernel void fastNlMeansDenoising(__global const uchar * src, int src_step, int src_offset, __global uchar * dst, int dst_step, int dst_offset, int dst_rows, int dst_cols, __global const wlut_t * almostDist2Weight, __global uchar * buffer, int almostTemplateWindowSizeSqBinShift) { int block_x = get_group_id(0), nblocks_x = get_num_groups(0); int block_y = get_group_id(1); int id = get_local_id(0), first; __local int dists[SEARCH_SIZE_SQ]; __local weight_t weights[CTA_SIZE]; __local sum_t weighted_sum[CTA_SIZE]; int x0 = block_x * BLOCK_COLS, x1 = min(x0 + BLOCK_COLS, dst_cols); int y0 = block_y * BLOCK_ROWS, y1 = min(y0 + BLOCK_ROWS, dst_rows); int block_data_start = SEARCH_SIZE_SQ * (mad24(block_y, dst_cols, x0) + mad24(block_y, nblocks_x, block_x) * TEMPLATE_SIZE); __global int * col_dists = (__global int *)(buffer + block_data_start * sizeof(int)); __global int * up_col_dists = col_dists + SEARCH_SIZE_SQ * TEMPLATE_SIZE; for (int y = y0; y < y1; ++y) for (int x = x0; x < x1; ++x) { if (x == x0) { calcFirstElementInRow(src, src_step, src_offset, dists, y, x, id, col_dists, up_col_dists); first = 0; } else { if (y == y0) calcElementInFirstRow(src, src_step, src_offset, dists, y, x - x0, x, id, first, col_dists, up_col_dists); else calcElement(src, src_step, src_offset, dists, y, x - x0, x, id, first, col_dists, up_col_dists); first = (first + 1) % TEMPLATE_SIZE; } convolveWindow(src, src_step, src_offset, dists, almostDist2Weight, dst, dst_step, dst_offset, y, x, id, weights, weighted_sum, almostTemplateWindowSizeSqBinShift); } } #endif 094aea838a917cea483f77e19dd39de3($P$__ZN2cv3ocl5photo14nlmeans_oclsrcE