/* * Copyright (c) 2012-2013 Oka Motofumi (chikuzen.mo at gmail dot com) * Copyright (c) 2015 Paul B Mahol * * This file is part of FFmpeg. * * FFmpeg is free software; you can redistribute it and/or * modify it under the terms of the GNU Lesser General Public * License as published by the Free Software Foundation; either * version 2.1 of the License, or (at your option) any later version. * * FFmpeg is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU * Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with FFmpeg; if not, write to the Free Software * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA */ #include "config_components.h" #include "libavutil/avstring.h"#include "libavutil/imgutils.h"#include "libavutil/intreadwrite.h"#include "libavutil/mem_internal.h"#include "libavutil/opt.h"#include "libavutil/pixdesc.h"#include "avfilter.h"#include "convolution.h"#include "formats.h"#include "internal.h"#include "video.h" #define OFFSET(x) offsetof(ConvolutionContext, x)#define FLAGS AV_OPT_FLAG_VIDEO_PARAM|AV_OPT_FLAG_FILTERING_PARAM|AV_OPT_FLAG_RUNTIME_PARAM static const AVOption convolution_options[] = {    { "0m", "set matrix for 1st plane", OFFSET(matrix_str[0]), AV_OPT_TYPE_STRING, {.str="0 0 0 0 1 0 0 0 0"}, 0, 0, FLAGS },    { "1m", "set matrix for 2nd plane", OFFSET(matrix_str[1]), AV_OPT_TYPE_STRING, {.str="0 0 0 0 1 0 0 0 0"}, 0, 0, FLAGS },    { "2m", "set matrix for 3rd plane", OFFSET(matrix_str[2]), AV_OPT_TYPE_STRING, {.str="0 0 0 0 1 0 0 0 0"}, 0, 0, FLAGS },    { "3m", "set matrix for 4th plane", OFFSET(matrix_str[3]), AV_OPT_TYPE_STRING, {.str="0 0 0 0 1 0 0 0 0"}, 0, 0, FLAGS },    { "0rdiv", "set rdiv for 1st plane", OFFSET(rdiv[0]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS},    { "1rdiv", "set rdiv for 2nd plane", OFFSET(rdiv[1]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS},    { "2rdiv", "set rdiv for 3rd plane", OFFSET(rdiv[2]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS},    { "3rdiv", "set rdiv for 4th plane", OFFSET(rdiv[3]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS},    { "0bias", "set bias for 1st plane", OFFSET(bias[0]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS},    { "1bias", "set bias for 2nd plane", OFFSET(bias[1]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS},    { "2bias", "set bias for 3rd plane", OFFSET(bias[2]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS},    { "3bias", "set bias for 4th plane", OFFSET(bias[3]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS},    { "0mode", "set matrix mode for 1st plane", OFFSET(mode[0]), AV_OPT_TYPE_INT, {.i64=MATRIX_SQUARE}, 0, MATRIX_NBMODES-1, FLAGS, "mode" },    { "1mode", "set matrix mode for 2nd plane", OFFSET(mode[1]), AV_OPT_TYPE_INT, {.i64=MATRIX_SQUARE}, 0, MATRIX_NBMODES-1, FLAGS, "mode" },    { "2mode", "set matrix mode for 3rd plane", OFFSET(mode[2]), AV_OPT_TYPE_INT, {.i64=MATRIX_SQUARE}, 0, MATRIX_NBMODES-1, FLAGS, "mode" },    { "3mode", "set matrix mode for 4th plane", OFFSET(mode[3]), AV_OPT_TYPE_INT, {.i64=MATRIX_SQUARE}, 0, MATRIX_NBMODES-1, FLAGS, "mode" },    { "square", "square matrix",     0, AV_OPT_TYPE_CONST, {.i64=MATRIX_SQUARE}, 0, 0, FLAGS, "mode" },    { "row",    "single row matrix", 0, AV_OPT_TYPE_CONST, {.i64=MATRIX_ROW}   , 0, 0, FLAGS, "mode" },    { "column", "single column matrix", 0, AV_OPT_TYPE_CONST, {.i64=MATRIX_COLUMN}, 0, 0, FLAGS, "mode" },    { NULL }}; AVFILTER_DEFINE_CLASS(convolution); static const int same3x3[9] = {0, 0, 0,                               0, 1, 0,                               0, 0, 0}; static const int same5x5[25] = {0, 0, 0, 0, 0,                                0, 0, 0, 0, 0,                                0, 0, 1, 0, 0,                                0, 0, 0, 0, 0,                                0, 0, 0, 0, 0}; static const int same7x7[49] = {0, 0, 0, 0, 0, 0, 0,                                0, 0, 0, 0, 0, 0, 0,                                0, 0, 0, 0, 0, 0, 0,                                0, 0, 0, 1, 0, 0, 0,                                0, 0, 0, 0, 0, 0, 0,                                0, 0, 0, 0, 0, 0, 0,                                0, 0, 0, 0, 0, 0, 0}; static const enum AVPixelFormat pix_fmts[] = {    AV_PIX_FMT_YUVA444P, AV_PIX_FMT_YUV444P, AV_PIX_FMT_YUV440P,    AV_PIX_FMT_YUVJ444P, AV_PIX_FMT_YUVJ440P,    AV_PIX_FMT_YUVA422P, AV_PIX_FMT_YUV422P, AV_PIX_FMT_YUVA420P, AV_PIX_FMT_YUV420P,    AV_PIX_FMT_YUVJ422P, AV_PIX_FMT_YUVJ420P,    AV_PIX_FMT_YUVJ411P, AV_PIX_FMT_YUV411P, AV_PIX_FMT_YUV410P,    AV_PIX_FMT_YUV420P9, AV_PIX_FMT_YUV422P9, AV_PIX_FMT_YUV444P9,    AV_PIX_FMT_YUV420P10, AV_PIX_FMT_YUV422P10, AV_PIX_FMT_YUV444P10,    AV_PIX_FMT_YUV420P12, AV_PIX_FMT_YUV422P12, AV_PIX_FMT_YUV444P12, AV_PIX_FMT_YUV440P12,    AV_PIX_FMT_YUV420P14, AV_PIX_FMT_YUV422P14, AV_PIX_FMT_YUV444P14,    AV_PIX_FMT_YUV420P16, AV_PIX_FMT_YUV422P16, AV_PIX_FMT_YUV444P16,    AV_PIX_FMT_YUVA420P9, AV_PIX_FMT_YUVA422P9, AV_PIX_FMT_YUVA444P9,    AV_PIX_FMT_YUVA420P10, AV_PIX_FMT_YUVA422P10, AV_PIX_FMT_YUVA444P10,    AV_PIX_FMT_YUVA422P12, AV_PIX_FMT_YUVA444P12,    AV_PIX_FMT_YUVA420P16, AV_PIX_FMT_YUVA422P16, AV_PIX_FMT_YUVA444P16,    AV_PIX_FMT_GBRP, AV_PIX_FMT_GBRP9, AV_PIX_FMT_GBRP10,    AV_PIX_FMT_GBRP12, AV_PIX_FMT_GBRP14, AV_PIX_FMT_GBRP16,    AV_PIX_FMT_GBRAP, AV_PIX_FMT_GBRAP10, AV_PIX_FMT_GBRAP12, AV_PIX_FMT_GBRAP16,    AV_PIX_FMT_GRAY8, AV_PIX_FMT_GRAY9, AV_PIX_FMT_GRAY10, AV_PIX_FMT_GRAY12, AV_PIX_FMT_GRAY14, AV_PIX_FMT_GRAY16,    AV_PIX_FMT_NONE}; typedef struct ThreadData {    AVFrame *in, *out;} ThreadData; static void filter16_prewitt(uint8_t *dstp, int width,                             float scale, float delta, const int *const matrix,                             const uint8_t *c[], int peak, int radius,                             int dstride, int stride, int size){    uint16_t *dst = (uint16_t *)dstp;    int x;     for (x = 0; x < width; x++) {        float suma = AV_RN16A(&c[0][2 * x]) * -1 + AV_RN16A(&c[1][2 * x]) * -1 + AV_RN16A(&c[2][2 * x]) * -1 +                     AV_RN16A(&c[6][2 * x]) *  1 + AV_RN16A(&c[7][2 * x]) *  1 + AV_RN16A(&c[8][2 * x]) *  1;        float sumb = AV_RN16A(&c[0][2 * x]) * -1 + AV_RN16A(&c[2][2 * x]) *  1 + AV_RN16A(&c[3][2 * x]) * -1 +                     AV_RN16A(&c[5][2 * x]) *  1 + AV_RN16A(&c[6][2 * x]) * -1 + AV_RN16A(&c[8][2 * x]) *  1;         dst[x] = av_clip(sqrtf(suma*suma + sumb*sumb) * scale + delta, 0, peak);    }} static void filter16_roberts(uint8_t *dstp, int width,                             float scale, float delta, const int *const matrix,                             const uint8_t *c[], int peak, int radius,                             int dstride, int stride, int size){    uint16_t *dst = (uint16_t *)dstp;    int x;     for (x = 0; x < width; x++) {        float suma = AV_RN16A(&c[0][2 * x]) *  1 + AV_RN16A(&c[1][2 * x]) * -1;        float sumb = AV_RN16A(&c[4][2 * x]) *  1 + AV_RN16A(&c[3][2 * x]) * -1;         dst[x] = av_clip(sqrtf(suma*suma + sumb*sumb) * scale + delta, 0, peak);    }} static void filter16_scharr(uint8_t *dstp, int width,                            float scale, float delta, const int *const matrix,                            const uint8_t *c[], int peak, int radius,                            int dstride, int stride, int size){    uint16_t *dst = (uint16_t *)dstp;    int x;     for (x = 0; x < width; x++) {        float suma = AV_RN16A(&c[0][2 * x]) * -47 + AV_RN16A(&c[1][2 * x]) * -162 + AV_RN16A(&c[2][2 * x]) *  -47 +                     AV_RN16A(&c[6][2 * x]) *  47 + AV_RN16A(&c[7][2 * x]) *  162 + AV_RN16A(&c[8][2 * x]) *   47;        float sumb = AV_RN16A(&c[0][2 * x]) * -47 + AV_RN16A(&c[2][2 * x]) *   47 + AV_RN16A(&c[3][2 * x]) * -162 +                     AV_RN16A(&c[5][2 * x]) * 162 + AV_RN16A(&c[6][2 * x]) *  -47 + AV_RN16A(&c[8][2 * x]) *   47;         suma /= 256.f;        sumb /= 256.f;        dst[x] = av_clip(sqrtf(suma*suma + sumb*sumb) * scale + delta, 0, peak);    }} static void filter16_kirsch(uint8_t *dstp, int width,                            float scale, float delta, const int *const matrix,                            const uint8_t *c[], int peak, int radius,                            int dstride, int stride, int size){    uint16_t *dst = (uint16_t *)dstp;    const uint16_t *c0 = (const uint16_t *)c[0], *c1 = (const uint16_t *)c[1], *c2 = (const uint16_t *)c[2];    const uint16_t *c3 = (const uint16_t *)c[3], *c5 = (const uint16_t *)c[5];    const uint16_t *c6 = (const uint16_t *)c[6], *c7 = (const uint16_t *)c[7], *c8 = (const uint16_t *)c[8];    int x;     for (x = 0; x < width; x++) {        int sum0 = c0[x] *  5 + c1[x] *  5 + c2[x] *  5 +                   c3[x] * -3 + c5[x] * -3 +                   c6[x] * -3 + c7[x] * -3 + c8[x] * -3;        int sum1 = c0[x] * -3 + c1[x] *  5 + c2[x] *  5 +                   c3[x] *  5 + c5[x] * -3 +                   c6[x] * -3 + c7[x] * -3 + c8[x] * -3;        int sum2 = c0[x] * -3 + c1[x] * -3 + c2[x] *  5 +                   c3[x] *  5 + c5[x] *  5 +                   c6[x] * -3 + c7[x] * -3 + c8[x] * -3;        int sum3 = c0[x] * -3 + c1[x] * -3 + c2[x] * -3 +                   c3[x] *  5 + c5[x] *  5 +                   c6[x] *  5 + c7[x] * -3 + c8[x] * -3;        int sum4 = c0[x] * -3 + c1[x] * -3 + c2[x] * -3 +                   c3[x] * -3 + c5[x] *  5 +                   c6[x] *  5 + c7[x] *  5 + c8[x] * -3;        int sum5 = c0[x] * -3 + c1[x] * -3 + c2[x] * -3 +                   c3[x] * -3 + c5[x] * -3 +                   c6[x] *  5 + c7[x] *  5 + c8[x] *  5;        int sum6 = c0[x] *  5 + c1[x] * -3 + c2[x] * -3 +                   c3[x] * -3 + c5[x] * -3 +                   c6[x] * -3 + c7[x] *  5 + c8[x] *  5;        int sum7 = c0[x] *  5 + c1[x] *  5 + c2[x] * -3 +                   c3[x] * -3 + c5[x] * -3 +                   c6[x] * -3 + c7[x] * -3 + c8[x] *  5;         sum0 = FFMAX(sum0, sum1);        sum2 = FFMAX(sum2, sum3);        sum4 = FFMAX(sum4, sum5);        sum6 = FFMAX(sum6, sum7);        sum0 = FFMAX(sum0, sum2);        sum4 = FFMAX(sum4, sum6);        sum0 = FFMAX(sum0, sum4);         dst[x] = av_clip(FFABS(sum0) * scale + delta, 0, peak);    }} static void filter_prewitt(uint8_t *dst, int width,                           float scale, float delta, const int *const matrix,                           const uint8_t *c[], int peak, int radius,                           int dstride, int stride, int size){    const uint8_t *c0 = c[0], *c1 = c[1], *c2 = c[2];    const uint8_t *c3 = c[3], *c5 = c[5];    const uint8_t *c6 = c[6], *c7 = c[7], *c8 = c[8];    int x;     for (x = 0; x < width; x++) {        float suma = c0[x] * -1 + c1[x] * -1 + c2[x] * -1 +                     c6[x] *  1 + c7[x] *  1 + c8[x] *  1;        float sumb = c0[x] * -1 + c2[x] *  1 + c3[x] * -1 +                     c5[x] *  1 + c6[x] * -1 + c8[x] *  1;         dst[x] = av_clip_uint8(sqrtf(suma*suma + sumb*sumb) * scale + delta);    }} static void filter_roberts(uint8_t *dst, int width,                           float scale, float delta, const int *const matrix,                           const uint8_t *c[], int peak, int radius,                           int dstride, int stride, int size){    int x;     for (x = 0; x < width; x++) {        float suma = c[0][x] *  1 + c[1][x] * -1;        float sumb = c[4][x] *  1 + c[3][x] * -1;         dst[x] = av_clip_uint8(sqrtf(suma*suma + sumb*sumb) * scale + delta);    }} static void filter_scharr(uint8_t *dst, int width,                          float scale, float delta, const int *const matrix,                          const uint8_t *c[], int peak, int radius,                          int dstride, int stride, int size){    const uint8_t *c0 = c[0], *c1 = c[1], *c2 = c[2];    const uint8_t *c3 = c[3], *c5 = c[5];    const uint8_t *c6 = c[6], *c7 = c[7], *c8 = c[8];    int x;     for (x = 0; x < width; x++) {        float suma = c0[x] * -47 + c1[x] * -162 + c2[x] *  -47 +                     c6[x] *  47 + c7[x] *  162 + c8[x] *   47;        float sumb = c0[x] * -47 + c2[x] *   47 + c3[x] * -162 +                     c5[x] * 162 + c6[x] *  -47 + c8[x] *   47;         suma /= 256.f;        sumb /= 256.f;        dst[x] = av_clip_uint8(sqrtf(suma*suma + sumb*sumb) * scale + delta);    }} static void filter_kirsch(uint8_t *dst, int width,                          float scale, float delta, const int *const matrix,                          const uint8_t *c[], int peak, int radius,                          int dstride, int stride, int size){    const uint8_t *c0 = c[0], *c1 = c[1], *c2 = c[2];    const uint8_t *c3 = c[3], *c5 = c[5];    const uint8_t *c6 = c[6], *c7 = c[7], *c8 = c[8];    int x;     for (x = 0; x < width; x++) {        int sum0 = c0[x] *  5 + c1[x] *  5 + c2[x] *  5 +                   c3[x] * -3 + c5[x] * -3 +                   c6[x] * -3 + c7[x] * -3 + c8[x] * -3;        int sum1 = c0[x] * -3 + c1[x] *  5 + c2[x] *  5 +                   c3[x] *  5 + c5[x] * -3 +                   c6[x] * -3 + c7[x] * -3 + c8[x] * -3;        int sum2 = c0[x] * -3 + c1[x] * -3 + c2[x] *  5 +                   c3[x] *  5 + c5[x] *  5 +                   c6[x] * -3 + c7[x] * -3 + c8[x] * -3;        int sum3 = c0[x] * -3 + c1[x] * -3 + c2[x] * -3 +                   c3[x] *  5 + c5[x] *  5 +                   c6[x] *  5 + c7[x] * -3 + c8[x] * -3;        int sum4 = c0[x] * -3 + c1[x] * -3 + c2[x] * -3 +                   c3[x] * -3 + c5[x] *  5 +                   c6[x] *  5 + c7[x] *  5 + c8[x] * -3;        int sum5 = c0[x] * -3 + c1[x] * -3 + c2[x] * -3 +                   c3[x] * -3 + c5[x] * -3 +                   c6[x] *  5 + c7[x] *  5 + c8[x] *  5;        int sum6 = c0[x] *  5 + c1[x] * -3 + c2[x] * -3 +                   c3[x] * -3 + c5[x] * -3 +                   c6[x] * -3 + c7[x] *  5 + c8[x] *  5;        int sum7 = c0[x] *  5 + c1[x] *  5 + c2[x] * -3 +                   c3[x] * -3 + c5[x] * -3 +                   c6[x] * -3 + c7[x] * -3 + c8[x] *  5;         sum0 = FFMAX(sum0, sum1);        sum2 = FFMAX(sum2, sum3);        sum4 = FFMAX(sum4, sum5);        sum6 = FFMAX(sum6, sum7);        sum0 = FFMAX(sum0, sum2);        sum4 = FFMAX(sum4, sum6);        sum0 = FFMAX(sum0, sum4);         dst[x] = av_clip_uint8(FFABS(sum0) * scale + delta);    }} static void filter16_3x3(uint8_t *dstp, int width,                         float rdiv, float bias, const int *const matrix,                         const uint8_t *c[], int peak, int radius,                         int dstride, int stride, int size){    uint16_t *dst = (uint16_t *)dstp;    int x;     for (x = 0; x < width; x++) {        int sum = AV_RN16A(&c[0][2 * x]) * matrix[0] +                  AV_RN16A(&c[1][2 * x]) * matrix[1] +                  AV_RN16A(&c[2][2 * x]) * matrix[2] +                  AV_RN16A(&c[3][2 * x]) * matrix[3] +                  AV_RN16A(&c[4][2 * x]) * matrix[4] +                  AV_RN16A(&c[5][2 * x]) * matrix[5] +                  AV_RN16A(&c[6][2 * x]) * matrix[6] +                  AV_RN16A(&c[7][2 * x]) * matrix[7] +                  AV_RN16A(&c[8][2 * x]) * matrix[8];        sum = (int)(sum * rdiv + bias + 0.5f);        dst[x] = av_clip(sum, 0, peak);    }} static void filter16_5x5(uint8_t *dstp, int width,                         float rdiv, float bias, const int *const matrix,                         const uint8_t *c[], int peak, int radius,                         int dstride, int stride, int size){    uint16_t *dst = (uint16_t *)dstp;    int x;     for (x = 0; x < width; x++) {        int i, sum = 0;         for (i = 0; i < 25; i++)            sum += AV_RN16A(&c[i][2 * x]) * matrix[i];         sum = (int)(sum * rdiv + bias + 0.5f);        dst[x] = av_clip(sum, 0, peak);    }} static void filter16_7x7(uint8_t *dstp, int width,                         float rdiv, float bias, const int *const matrix,                         const uint8_t *c[], int peak, int radius,                         int dstride, int stride, int size){    uint16_t *dst = (uint16_t *)dstp;    int x;     for (x = 0; x < width; x++) {        int i, sum = 0;         for (i = 0; i < 49; i++)            sum += AV_RN16A(&c[i][2 * x]) * matrix[i];         sum = (int)(sum * rdiv + bias + 0.5f);        dst[x] = av_clip(sum, 0, peak);    }} static void filter16_row(uint8_t *dstp, int width,                         float rdiv, float bias, const int *const matrix,                         const uint8_t *c[], int peak, int radius,                         int dstride, int stride, int size){    uint16_t *dst = (uint16_t *)dstp;    int x;     for (x = 0; x < width; x++) {        int i, sum = 0;         for (i = 0; i < 2 * radius + 1; i++)            sum += AV_RN16A(&c[i][2 * x]) * matrix[i];         sum = (int)(sum * rdiv + bias + 0.5f);        dst[x] = av_clip(sum, 0, peak);    }} static void filter16_column(uint8_t *dstp, int height,                            float rdiv, float bias, const int *const matrix,                            const uint8_t *c[], int peak, int radius,                            int dstride, int stride, int size){    DECLARE_ALIGNED(64, int, sum)[16];    uint16_t *dst = (uint16_t *)dstp;    const int width = FFMIN(16, size);     for (int y = 0; y < height; y++) {         memset(sum, 0, sizeof(sum));        for (int i = 0; i < 2 * radius + 1; i++) {            for (int off16 = 0; off16 < width; off16++)                sum[off16] += AV_RN16A(&c[i][0 + y * stride + off16 * 2]) * matrix[i];        }         for (int off16 = 0; off16 < width; off16++) {            sum[off16] = (int)(sum[off16] * rdiv + bias + 0.5f);            dst[off16] = av_clip(sum[off16], 0, peak);        }        dst += dstride / 2;    }} static void filter_7x7(uint8_t *dst, int width,                       float rdiv, float bias, const int *const matrix,                       const uint8_t *c[], int peak, int radius,                       int dstride, int stride, int size){    int x;     for (x = 0; x < width; x++) {        int i, sum = 0;         for (i = 0; i < 49; i++)            sum += c[i][x] * matrix[i];         sum = (int)(sum * rdiv + bias + 0.5f);        dst[x] = av_clip_uint8(sum);    }} static void filter_5x5(uint8_t *dst, int width,                       float rdiv, float bias, const int *const matrix,                       const uint8_t *c[], int peak, int radius,                       int dstride, int stride, int size){    int x;     for (x = 0; x < width; x++) {        int i, sum = 0;         for (i = 0; i < 25; i++)            sum += c[i][x] * matrix[i];         sum = (int)(sum * rdiv + bias + 0.5f);        dst[x] = av_clip_uint8(sum);    }} static void filter_3x3(uint8_t *dst, int width,                       float rdiv, float bias, const int *const matrix,                       const uint8_t *c[], int peak, int radius,                       int dstride, int stride, int size){    const uint8_t *c0 = c[0], *c1 = c[1], *c2 = c[2];    const uint8_t *c3 = c[3], *c4 = c[4], *c5 = c[5];    const uint8_t *c6 = c[6], *c7 = c[7], *c8 = c[8];    int x;     for (x = 0; x < width; x++) {        int sum = c0[x] * matrix[0] + c1[x] * matrix[1] + c2[x] * matrix[2] +                  c3[x] * matrix[3] + c4[x] * matrix[4] + c5[x] * matrix[5] +                  c6[x] * matrix[6] + c7[x] * matrix[7] + c8[x] * matrix[8];        sum = (int)(sum * rdiv + bias + 0.5f);        dst[x] = av_clip_uint8(sum);    }} static void filter_row(uint8_t *dst, int width,                       float rdiv, float bias, const int *const matrix,                       const uint8_t *c[], int peak, int radius,                       int dstride, int stride, int size){    int x;     for (x = 0; x < width; x++) {        int i, sum = 0;         for (i = 0; i < 2 * radius + 1; i++)            sum += c[i][x] * matrix[i];         sum = (int)(sum * rdiv + bias + 0.5f);        dst[x] = av_clip_uint8(sum);    }} static void filter_column(uint8_t *dst, int height,                          float rdiv, float bias, const int *const matrix,                          const uint8_t *c[], int peak, int radius,                          int dstride, int stride, int size){    DECLARE_ALIGNED(64, int, sum)[16]; 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