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FFmpeg/libavfilter/vf_convolution.c
Stone Chen ef917950f0 avfilter/vf_convolution: add float user_rdiv[4] to allow user options to apply correctly 
Previously to support dynamic reconfigurations of the matrix string (e.g. 0m),
the rdiv values would always be cleared to 0.f, causing the rdiv to be
recalculated based on the new filter. This however had the side effect of
always ignoring user specified rdiv values.

Instead float user_rdiv[0] is added to ConvolutionContext which will store the
user specified rdiv values. Then the original rdiv array will store either the
user_rdiv or the automatically calculated 1/sum.

This fixes trac ticket #10294, #10867.

Signed-off-by: Stone Chen <chen.stonechen@gmail.com>
Signed-off-by: Marton Balint <cus@passwd.hu>
2024-02-25 10:49:37 +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 "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 "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(user_rdiv[0]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS},
{ "1rdiv", "set rdiv for 2nd plane", OFFSET(user_rdiv[1]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS},
{ "2rdiv", "set rdiv for 3rd plane", OFFSET(user_rdiv[2]), AV_OPT_TYPE_FLOAT, {.dbl=0.0}, 0.0, INT_MAX, FLAGS},
{ "3rdiv", "set rdiv for 4th plane", OFFSET(user_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, .unit = "mode" },
{ "1mode", "set matrix mode for 2nd plane", OFFSET(mode[1]), AV_OPT_TYPE_INT, {.i64=MATRIX_SQUARE}, 0, MATRIX_NBMODES-1, FLAGS, .unit = "mode" },
{ "2mode", "set matrix mode for 3rd plane", OFFSET(mode[2]), AV_OPT_TYPE_INT, {.i64=MATRIX_SQUARE}, 0, MATRIX_NBMODES-1, FLAGS, .unit = "mode" },
{ "3mode", "set matrix mode for 4th plane", OFFSET(mode[3]), AV_OPT_TYPE_INT, {.i64=MATRIX_SQUARE}, 0, MATRIX_NBMODES-1, FLAGS, .unit = "mode" },
{ "square", "square matrix", 0, AV_OPT_TYPE_CONST, {.i64=MATRIX_SQUARE}, 0, 0, FLAGS, .unit = "mode" },
{ "row", "single row matrix", 0, AV_OPT_TYPE_CONST, {.i64=MATRIX_ROW} , 0, 0, FLAGS, .unit = "mode" },
{ "column", "single column matrix", 0, AV_OPT_TYPE_CONST, {.i64=MATRIX_COLUMN}, 0, 0, FLAGS, .unit = "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];
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_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 param_init(AVFilterContext *ctx)
{
ConvolutionContext *s = ctx->priv;
AVFilterLink *inlink = ctx->inputs[0];
const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(inlink->format);
int p, i;
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")) {
for (i = 0; i < 4; i++) {
int *matrix = (int *)s->matrix[i];
char *orig, *p, *arg, *saveptr = NULL;
float sum = 1.f;
p = orig = av_strdup(s->matrix_str[i]);
if (p) {
s->matrix_length[i] = 0;
s->rdiv[i] = s->user_rdiv[i];
sum = 0.f;
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]++;
}
av_freep(&orig);
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++) {
s->filter[i] = filter_prewitt;
s->copy[i] = !((1 << i) & s->planes);
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++) {
s->filter[i] = filter_roberts;
s->copy[i] = !((1 << i) & s->planes);
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")) {
ff_sobel_init(s, s->depth, s->nb_planes);
} else if (!strcmp(ctx->filter->name, "kirsch")) {
for (i = 0; i < 4; i++) {
s->filter[i] = filter_kirsch;
s->copy[i] = !((1 << i) & s->planes);
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, "scharr")) {
for (i = 0; i < 4; i++) {
s->filter[i] = filter_scharr;
s->copy[i] = !((1 << i) & s->planes);
s->size[i] = 3;
s->setup[i] = setup_3x3;
s->rdiv[i] = s->scale;
s->bias[i] = s->delta;
}
}
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, "kirsch")) {
if (s->depth > 8)
for (p = 0; p < s->nb_planes; p++)
s->filter[p] = filter16_kirsch;
} else if (!strcmp(ctx->filter->name, "scharr")) {
if (s->depth > 8)
for (p = 0; p < s->nb_planes; p++)
s->filter[p] = filter16_scharr;
}
return 0;
}
static int config_input(AVFilterLink *inlink)
{
AVFilterContext *ctx = inlink->dst;
return param_init(ctx);
}
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;
ff_filter_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 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 param_init(ctx);
}
static const AVFilterPad convolution_inputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = config_input,
.filter_frame = filter_frame,
},
};
#if CONFIG_CONVOLUTION_FILTER
const AVFilter ff_vf_convolution = {
.name = "convolution",
.description = NULL_IF_CONFIG_SMALL("Apply convolution filter."),
.priv_size = sizeof(ConvolutionContext),
.priv_class = &convolution_class,
FILTER_INPUTS(convolution_inputs),
FILTER_OUTPUTS(ff_video_default_filterpad),
FILTER_PIXFMTS_ARRAY(pix_fmts),
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
.process_command = process_command,
};
#endif /* CONFIG_CONVOLUTION_FILTER */
static const AVOption common_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 }
};
AVFILTER_DEFINE_CLASS_EXT(common, "kirsch/prewitt/roberts/scharr/sobel",
common_options);
#if CONFIG_PREWITT_FILTER
const AVFilter ff_vf_prewitt = {
.name = "prewitt",
.description = NULL_IF_CONFIG_SMALL("Apply prewitt operator."),
.priv_size = sizeof(ConvolutionContext),
.priv_class = &common_class,
FILTER_INPUTS(convolution_inputs),
FILTER_OUTPUTS(ff_video_default_filterpad),
FILTER_PIXFMTS_ARRAY(pix_fmts),
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
.process_command = process_command,
};
#endif /* CONFIG_PREWITT_FILTER */
#if CONFIG_SOBEL_FILTER
const AVFilter ff_vf_sobel = {
.name = "sobel",
.description = NULL_IF_CONFIG_SMALL("Apply sobel operator."),
.priv_size = sizeof(ConvolutionContext),
.priv_class = &common_class,
FILTER_INPUTS(convolution_inputs),
FILTER_OUTPUTS(ff_video_default_filterpad),
FILTER_PIXFMTS_ARRAY(pix_fmts),
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
.process_command = process_command,
};
#endif /* CONFIG_SOBEL_FILTER */
#if CONFIG_ROBERTS_FILTER
const AVFilter ff_vf_roberts = {
.name = "roberts",
.description = NULL_IF_CONFIG_SMALL("Apply roberts cross operator."),
.priv_size = sizeof(ConvolutionContext),
.priv_class = &common_class,
FILTER_INPUTS(convolution_inputs),
FILTER_OUTPUTS(ff_video_default_filterpad),
FILTER_PIXFMTS_ARRAY(pix_fmts),
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
.process_command = process_command,
};
#endif /* CONFIG_ROBERTS_FILTER */
#if CONFIG_KIRSCH_FILTER
const AVFilter ff_vf_kirsch = {
.name = "kirsch",
.description = NULL_IF_CONFIG_SMALL("Apply kirsch operator."),
.priv_size = sizeof(ConvolutionContext),
.priv_class = &common_class,
FILTER_INPUTS(convolution_inputs),
FILTER_OUTPUTS(ff_video_default_filterpad),
FILTER_PIXFMTS_ARRAY(pix_fmts),
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
.process_command = process_command,
};
#endif /* CONFIG_KIRSCH_FILTER */
#if CONFIG_SCHARR_FILTER
const AVFilter ff_vf_scharr = {
.name = "scharr",
.description = NULL_IF_CONFIG_SMALL("Apply scharr operator."),
.priv_size = sizeof(ConvolutionContext),
.priv_class = &common_class,
FILTER_INPUTS(convolution_inputs),
FILTER_OUTPUTS(ff_video_default_filterpad),
FILTER_PIXFMTS_ARRAY(pix_fmts),
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
.process_command = process_command,
};
#endif /* CONFIG_SCHARR_FILTER */
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