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FFmpeg/libavfilter/vf_convolution.c
Paul B Mahol c6ce18be08 avfilter/vf_convolution: add 16-column operation for filter_column() 
Based on patch by Xu Jun <xujunzz@sjtu.edu.cn>
2021-02-13 14:45:48 +01:00

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/*
* 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 "libavutil/avstring.h"
#include "libavutil/imgutils.h"
#include "libavutil/intreadwrite.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 int query_formats(AVFilterContext *ctx)
{
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
};
return ff_set_common_formats(ctx, ff_make_format_list(pix_fmts));
}
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_sobel(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]) * -2 + AV_RN16A(&c[2][2 * x]) * -1 +
AV_RN16A(&c[6][2 * x]) * 1 + AV_RN16A(&c[7][2 * x]) * 2 + 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]) * -2 +
AV_RN16A(&c[5][2 * x]) * 2 + 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_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_sobel(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] * -2 + c2[x] * -1 +
c6[x] * 1 + c7[x] * 2 + c8[x] * 1;
float sumb = c0[x] * -1 + c2[x] * 1 + c3[x] * -2 +
c5[x] * 2 + c6[x] * -1 + c8[x] * 1;
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];
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 < 16; off16++)
sum[off16] += c[i][0 + y * stride + off16] * matrix[i];
}
for (int off16 = 0; off16 < 16; off16++) {
sum[off16] = (int)(sum[off16] * rdiv + bias + 0.5f);
dst[off16] = av_clip_uint8(sum[off16]);
}
dst += dstride;
}
}
static void setup_3x3(int radius, const uint8_t *c[], const uint8_t *src, int stride,
int x, int w, int y, int h, int bpc)
{
int i;
for (i = 0; i < 9; i++) {
int xoff = FFABS(x + ((i % 3) - 1));
int yoff = FFABS(y + (i / 3) - 1);
xoff = xoff >= w ? 2 * w - 1 - xoff : xoff;
yoff = yoff >= h ? 2 * h - 1 - yoff : yoff;
c[i] = src + xoff * bpc + yoff * stride;
}
}
static void setup_5x5(int radius, const uint8_t *c[], const uint8_t *src, int stride,
int x, int w, int y, int h, int bpc)
{
int i;
for (i = 0; i < 25; i++) {
int xoff = FFABS(x + ((i % 5) - 2));
int yoff = FFABS(y + (i / 5) - 2);
xoff = xoff >= w ? 2 * w - 1 - xoff : xoff;
yoff = yoff >= h ? 2 * h - 1 - yoff : yoff;
c[i] = src + xoff * bpc + yoff * stride;
}
}
static void setup_7x7(int radius, const uint8_t *c[], const uint8_t *src, int stride,
int x, int w, int y, int h, int bpc)
{
int i;
for (i = 0; i < 49; i++) {
int xoff = FFABS(x + ((i % 7) - 3));
int yoff = FFABS(y + (i / 7) - 3);
xoff = xoff >= w ? 2 * w - 1 - xoff : xoff;
yoff = yoff >= h ? 2 * h - 1 - yoff : yoff;
c[i] = src + xoff * bpc + yoff * stride;
}
}
static void setup_row(int radius, const uint8_t *c[], const uint8_t *src, int stride,
int x, int w, int y, int h, int bpc)
{
int i;
for (i = 0; i < radius * 2 + 1; i++) {
int xoff = FFABS(x + i - radius);
xoff = xoff >= w ? 2 * w - 1 - xoff : xoff;
c[i] = src + xoff * bpc + y * stride;
}
}
static void setup_column(int radius, const uint8_t *c[], const uint8_t *src, int stride,
int x, int w, int y, int h, int bpc)
{
int i;
for (i = 0; i < radius * 2 + 1; i++) {
int xoff = FFABS(x + i - radius);
xoff = xoff >= h ? 2 * h - 1 - xoff : xoff;
c[i] = src + y * bpc + xoff * stride;
}
}
static int filter_slice(AVFilterContext *ctx, void *arg, int jobnr, int nb_jobs)
{
ConvolutionContext *s = ctx->priv;
ThreadData *td = arg;
AVFrame *in = td->in;
AVFrame *out = td->out;
int plane;
for (plane = 0; plane < s->nb_planes; plane++) {
const int mode = s->mode[plane];
const int bpc = s->bpc;
const int radius = s->size[plane] / 2;
const int height = s->planeheight[plane];
const int width = s->planewidth[plane];
const int stride = in->linesize[plane];
const int dstride = out->linesize[plane];
const int sizeh = mode == MATRIX_COLUMN ? width : height;
const int sizew = mode == MATRIX_COLUMN ? height : width;
const int slice_start = (sizeh * jobnr) / nb_jobs;
const int slice_end = (sizeh * (jobnr+1)) / nb_jobs;
const float rdiv = s->rdiv[plane];
const float bias = s->bias[plane];
const uint8_t *src = in->data[plane];
const int dst_pos = slice_start * (mode == MATRIX_COLUMN ? bpc : dstride);
uint8_t *dst = out->data[plane] + dst_pos;
const int *matrix = s->matrix[plane];
const int step = mode == MATRIX_COLUMN ? 16 : 1;
const uint8_t *c[49];
int y, x;
if (s->copy[plane]) {
if (mode == MATRIX_COLUMN)
av_image_copy_plane(dst, dstride, src + slice_start * bpc, stride,
(slice_end - slice_start) * bpc, height);
else
av_image_copy_plane(dst, dstride, src + slice_start * stride, stride,
width * bpc, slice_end - slice_start);
continue;
}
for (y = slice_start; y < slice_end; y += step) {
const int xoff = mode == MATRIX_COLUMN ? (y - slice_start) * bpc : radius * bpc;
const int yoff = mode == MATRIX_COLUMN ? radius * dstride : 0;
for (x = 0; x < radius; x++) {
const int xoff = mode == MATRIX_COLUMN ? (y - slice_start) * bpc : x * bpc;
const int yoff = mode == MATRIX_COLUMN ? x * dstride : 0;
s->setup[plane](radius, c, src, stride, x, width, y, height, bpc);
s->filter[plane](dst + yoff + xoff, 1, rdiv,
bias, matrix, c, s->max, radius,
dstride, stride, slice_end - step);
}
s->setup[plane](radius, c, src, stride, radius, width, y, height, bpc);
s->filter[plane](dst + yoff + xoff, sizew - 2 * radius,
rdiv, bias, matrix, c, s->max, radius,
dstride, stride, slice_end - step);
for (x = sizew - radius; x < sizew; x++) {
const int xoff = mode == MATRIX_COLUMN ? (y - slice_start) * bpc : x * bpc;
const int yoff = mode == MATRIX_COLUMN ? x * dstride : 0;
s->setup[plane](radius, c, src, stride, x, width, y, height, bpc);
s->filter[plane](dst + yoff + xoff, 1, rdiv,
bias, matrix, c, s->max, radius,
dstride, stride, slice_end - step);
}
if (mode != MATRIX_COLUMN)
dst += dstride;
}
}
return 0;
}
static int config_input(AVFilterLink *inlink)
{
AVFilterContext *ctx = inlink->dst;
ConvolutionContext *s = ctx->priv;
const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(inlink->format);
int p;
s->depth = desc->comp[0].depth;
s->max = (1 << s->depth) - 1;
s->planewidth[1] = s->planewidth[2] = AV_CEIL_RSHIFT(inlink->w, desc->log2_chroma_w);
s->planewidth[0] = s->planewidth[3] = inlink->w;
s->planeheight[1] = s->planeheight[2] = AV_CEIL_RSHIFT(inlink->h, desc->log2_chroma_h);
s->planeheight[0] = s->planeheight[3] = inlink->h;
s->nb_planes = av_pix_fmt_count_planes(inlink->format);
s->nb_threads = ff_filter_get_nb_threads(ctx);
s->bpc = (s->depth + 7) / 8;
if (!strcmp(ctx->filter->name, "convolution")) {
if (s->depth > 8) {
for (p = 0; p < s->nb_planes; p++) {
if (s->mode[p] == MATRIX_ROW)
s->filter[p] = filter16_row;
else if (s->mode[p] == MATRIX_COLUMN)
s->filter[p] = filter16_column;
else if (s->size[p] == 3)
s->filter[p] = filter16_3x3;
else if (s->size[p] == 5)
s->filter[p] = filter16_5x5;
else if (s->size[p] == 7)
s->filter[p] = filter16_7x7;
}
}
#if CONFIG_CONVOLUTION_FILTER && ARCH_X86_64
ff_convolution_init_x86(s);
#endif
} else if (!strcmp(ctx->filter->name, "prewitt")) {
if (s->depth > 8)
for (p = 0; p < s->nb_planes; p++)
s->filter[p] = filter16_prewitt;
} else if (!strcmp(ctx->filter->name, "roberts")) {
if (s->depth > 8)
for (p = 0; p < s->nb_planes; p++)
s->filter[p] = filter16_roberts;
} else if (!strcmp(ctx->filter->name, "sobel")) {
if (s->depth > 8)
for (p = 0; p < s->nb_planes; p++)
s->filter[p] = filter16_sobel;
} else if (!strcmp(ctx->filter->name, "kirsch")) {
if (s->depth > 8)
for (p = 0; p < s->nb_planes; p++)
s->filter[p] = filter16_kirsch;
}
return 0;
}
static int filter_frame(AVFilterLink *inlink, AVFrame *in)
{
AVFilterContext *ctx = inlink->dst;
ConvolutionContext *s = ctx->priv;
AVFilterLink *outlink = ctx->outputs[0];
AVFrame *out;
ThreadData td;
out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
if (!out) {
av_frame_free(&in);
return AVERROR(ENOMEM);
}
av_frame_copy_props(out, in);
td.in = in;
td.out = out;
ctx->internal->execute(ctx, filter_slice, &td, NULL, FFMIN3(s->planeheight[1], s->planewidth[1], s->nb_threads));
av_frame_free(&in);
return ff_filter_frame(outlink, out);
}
static av_cold int init(AVFilterContext *ctx)
{
ConvolutionContext *s = ctx->priv;
int i;
if (!strcmp(ctx->filter->name, "convolution")) {
for (i = 0; i < 4; i++) {
int *matrix = (int *)s->matrix[i];
char *p, *arg, *saveptr = NULL;
float sum = 0;
p = s->matrix_str[i];
if (p) {
s->matrix_length[i] = 0;
while (s->matrix_length[i] < 49) {
if (!(arg = av_strtok(p, " |", &saveptr)))
break;
p = NULL;
sscanf(arg, "%d", &matrix[s->matrix_length[i]]);
sum += matrix[s->matrix_length[i]];
s->matrix_length[i]++;
}
if (!(s->matrix_length[i] & 1)) {
av_log(ctx, AV_LOG_ERROR, "number of matrix elements must be odd\n");
return AVERROR(EINVAL);
}
}
if (s->mode[i] == MATRIX_ROW) {
s->filter[i] = filter_row;
s->setup[i] = setup_row;
s->size[i] = s->matrix_length[i];
} else if (s->mode[i] == MATRIX_COLUMN) {
s->filter[i] = filter_column;
s->setup[i] = setup_column;
s->size[i] = s->matrix_length[i];
} else if (s->matrix_length[i] == 9) {
s->size[i] = 3;
if (!memcmp(matrix, same3x3, sizeof(same3x3))) {
s->copy[i] = 1;
} else {
s->filter[i] = filter_3x3;
s->copy[i] = 0;
}
s->setup[i] = setup_3x3;
} else if (s->matrix_length[i] == 25) {
s->size[i] = 5;
if (!memcmp(matrix, same5x5, sizeof(same5x5))) {
s->copy[i] = 1;
} else {
s->filter[i] = filter_5x5;
s->copy[i] = 0;
}
s->setup[i] = setup_5x5;
} else if (s->matrix_length[i] == 49) {
s->size[i] = 7;
if (!memcmp(matrix, same7x7, sizeof(same7x7))) {
s->copy[i] = 1;
} else {
s->filter[i] = filter_7x7;
s->copy[i] = 0;
}
s->setup[i] = setup_7x7;
} else {
return AVERROR(EINVAL);
}
if (sum == 0)
sum = 1;
if (s->rdiv[i] == 0)
s->rdiv[i] = 1. / sum;
if (s->copy[i] && (s->rdiv[i] != 1. || s->bias[i] != 0.))
s->copy[i] = 0;
}
} else if (!strcmp(ctx->filter->name, "prewitt")) {
for (i = 0; i < 4; i++) {
if ((1 << i) & s->planes)
s->filter[i] = filter_prewitt;
else
s->copy[i] = 1;
s->size[i] = 3;
s->setup[i] = setup_3x3;
s->rdiv[i] = s->scale;
s->bias[i] = s->delta;
}
} else if (!strcmp(ctx->filter->name, "roberts")) {
for (i = 0; i < 4; i++) {
if ((1 << i) & s->planes)
s->filter[i] = filter_roberts;
else
s->copy[i] = 1;
s->size[i] = 3;
s->setup[i] = setup_3x3;
s->rdiv[i] = s->scale;
s->bias[i] = s->delta;
}
} else if (!strcmp(ctx->filter->name, "sobel")) {
for (i = 0; i < 4; i++) {
if ((1 << i) & s->planes)
s->filter[i] = filter_sobel;
else
s->copy[i] = 1;
s->size[i] = 3;
s->setup[i] = setup_3x3;
s->rdiv[i] = s->scale;
s->bias[i] = s->delta;
}
} else if (!strcmp(ctx->filter->name, "kirsch")) {
for (i = 0; i < 4; i++) {
if ((1 << i) & s->planes)
s->filter[i] = filter_kirsch;
else
s->copy[i] = 1;
s->size[i] = 3;
s->setup[i] = setup_3x3;
s->rdiv[i] = s->scale;
s->bias[i] = s->delta;
}
}
return 0;
}
static int process_command(AVFilterContext *ctx, const char *cmd, const char *args,
char *res, int res_len, int flags)
{
int ret;
ret = ff_filter_process_command(ctx, cmd, args, res, res_len, flags);
if (ret < 0)
return ret;
return init(ctx);
}
static const AVFilterPad convolution_inputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = config_input,
.filter_frame = filter_frame,
},
{ NULL }
};
static const AVFilterPad convolution_outputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
},
{ NULL }
};
#if CONFIG_CONVOLUTION_FILTER
AVFilter ff_vf_convolution = {
.name = "convolution",
.description = NULL_IF_CONFIG_SMALL("Apply convolution filter."),
.priv_size = sizeof(ConvolutionContext),
.priv_class = &convolution_class,
.init = init,
.query_formats = query_formats,
.inputs = convolution_inputs,
.outputs = convolution_outputs,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
.process_command = process_command,
};
#endif /* CONFIG_CONVOLUTION_FILTER */
#if CONFIG_PREWITT_FILTER || CONFIG_ROBERTS_FILTER || CONFIG_SOBEL_FILTER
static const AVOption prewitt_roberts_sobel_options[] = {
{ "planes", "set planes to filter", OFFSET(planes), AV_OPT_TYPE_INT, {.i64=15}, 0, 15, FLAGS},
{ "scale", "set scale", OFFSET(scale), AV_OPT_TYPE_FLOAT, {.dbl=1.0}, 0.0, 65535, FLAGS},
{ "delta", "set delta", OFFSET(delta), AV_OPT_TYPE_FLOAT, {.dbl=0}, -65535, 65535, FLAGS},
{ NULL }
};
#if CONFIG_PREWITT_FILTER
#define prewitt_options prewitt_roberts_sobel_options
AVFILTER_DEFINE_CLASS(prewitt);
AVFilter ff_vf_prewitt = {
.name = "prewitt",
.description = NULL_IF_CONFIG_SMALL("Apply prewitt operator."),
.priv_size = sizeof(ConvolutionContext),
.priv_class = &prewitt_class,
.init = init,
.query_formats = query_formats,
.inputs = convolution_inputs,
.outputs = convolution_outputs,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
.process_command = process_command,
};
#endif /* CONFIG_PREWITT_FILTER */
#if CONFIG_SOBEL_FILTER
#define sobel_options prewitt_roberts_sobel_options
AVFILTER_DEFINE_CLASS(sobel);
AVFilter ff_vf_sobel = {
.name = "sobel",
.description = NULL_IF_CONFIG_SMALL("Apply sobel operator."),
.priv_size = sizeof(ConvolutionContext),
.priv_class = &sobel_class,
.init = init,
.query_formats = query_formats,
.inputs = convolution_inputs,
.outputs = convolution_outputs,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
.process_command = process_command,
};
#endif /* CONFIG_SOBEL_FILTER */
#if CONFIG_ROBERTS_FILTER
#define roberts_options prewitt_roberts_sobel_options
AVFILTER_DEFINE_CLASS(roberts);
AVFilter ff_vf_roberts = {
.name = "roberts",
.description = NULL_IF_CONFIG_SMALL("Apply roberts cross operator."),
.priv_size = sizeof(ConvolutionContext),
.priv_class = &roberts_class,
.init = init,
.query_formats = query_formats,
.inputs = convolution_inputs,
.outputs = convolution_outputs,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
.process_command = process_command,
};
#endif /* CONFIG_ROBERTS_FILTER */
#if CONFIG_KIRSCH_FILTER
#define kirsch_options prewitt_roberts_sobel_options
AVFILTER_DEFINE_CLASS(kirsch);
AVFilter ff_vf_kirsch = {
.name = "kirsch",
.description = NULL_IF_CONFIG_SMALL("Apply kirsch operator."),
.priv_size = sizeof(ConvolutionContext),
.priv_class = &kirsch_class,
.init = init,
.query_formats = query_formats,
.inputs = convolution_inputs,
.outputs = convolution_outputs,
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
.process_command = process_command,
};
#endif /* CONFIG_KIRSCH_FILTER */
#endif /* CONFIG_PREWITT_FILTER || CONFIG_ROBERTS_FILTER || CONFIG_SOBEL_FILTER */
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