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FFmpeg/libavfilter/vf_convolution.c
Andreas Rheinhardt b4f5201967 avfilter: Replace query_formats callback with union of list and callback 
If one looks at the many query_formats callbacks in existence,
one will immediately recognize that there is one type of default
callback for video and a slightly different default callback for
audio: It is "return ff_set_common_formats_from_list(ctx, pix_fmts);"
for video with a filter-specific pix_fmts list. For audio, it is
the same with a filter-specific sample_fmts list together with
ff_set_common_all_samplerates() and ff_set_common_all_channel_counts().

This commit allows to remove the boilerplate query_formats callbacks
by replacing said callback with a union consisting the old callback
and pointers for pixel and sample format arrays. For the not uncommon
case in which these lists only contain a single entry (besides the
sentinel) enum AVPixelFormat and enum AVSampleFormat fields are also
added to the union to store them directly in the AVFilter,
thereby avoiding a relocation.

The state of said union will be contained in a new, dedicated AVFilter
field (the nb_inputs and nb_outputs fields have been shrunk to uint8_t
in order to create a hole for this new field; this is no problem, as
the maximum of all the nb_inputs is four; for nb_outputs it is only
two).

The state's default value coincides with the earlier default of
query_formats being unset, namely that the filter accepts all formats
(and also sample rates and channel counts/layouts for audio)
provided that these properties agree coincide for all inputs and
outputs.

By using different union members for audio and video filters
the type-unsafety of using the same functions for audio and video
lists will furthermore be more confined to formats.c than before.

When the new fields are used, they will also avoid allocations:
Currently something nearly equivalent to ff_default_query_formats()
is called after every successful call to a query_formats callback;
yet in the common case that the newly allocated AVFilterFormats
are not used at all (namely if there are no free links) these newly
allocated AVFilterFormats are freed again without ever being used.
Filters no longer using the callback will not exhibit this any more.

Reviewed-by: Paul B Mahol <onemda@gmail.com>
Reviewed-by: Nicolas George <george@nsup.org>
Signed-off-by: Andreas Rheinhardt <andreas.rheinhardt@outlook.com>
2021-10-05 17:48:25 +02:00

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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/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 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_from_list(ctx, 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_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_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_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_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;
} 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 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 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;
}
} else if (!strcmp(ctx->filter->name, "scharr")) {
for (i = 0; i < 4; i++) {
if ((1 << i) & s->planes)
s->filter[i] = filter_scharr;
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,
},
};
static const AVFilterPad convolution_outputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
},
};
#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,
.init = init,
FILTER_INPUTS(convolution_inputs),
FILTER_OUTPUTS(convolution_outputs),
FILTER_QUERY_FUNC(query_formats),
.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,
.init = init,
FILTER_INPUTS(convolution_inputs),
FILTER_OUTPUTS(convolution_outputs),
FILTER_QUERY_FUNC(query_formats),
.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,
.init = init,
FILTER_INPUTS(convolution_inputs),
FILTER_OUTPUTS(convolution_outputs),
FILTER_QUERY_FUNC(query_formats),
.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,
.init = init,
FILTER_INPUTS(convolution_inputs),
FILTER_OUTPUTS(convolution_outputs),
FILTER_QUERY_FUNC(query_formats),
.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,
.init = init,
FILTER_INPUTS(convolution_inputs),
FILTER_OUTPUTS(convolution_outputs),
FILTER_QUERY_FUNC(query_formats),
.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,
.init = init,
FILTER_INPUTS(convolution_inputs),
FILTER_OUTPUTS(convolution_outputs),
FILTER_QUERY_FUNC(query_formats),
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
.process_command = process_command,
};
#endif /* CONFIG_SCHARR_FILTER */
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