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FFmpeg/libavfilter/vf_convolve.c
Martin Storsjö a78f136f3f configure: Use a separate config_components.h header for $ALL_COMPONENTS 
This avoids unnecessary rebuilds of most source files if only the
list of enabled components has changed, but not the other properties
of the build, set in config.h.

Signed-off-by: Martin Storsjö <martin@martin.st>
2022-03-16 14:12:49 +02:00

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/*
* Copyright (c) 2017 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 <float.h>
#include "libavutil/imgutils.h"
#include "libavutil/opt.h"
#include "libavutil/pixdesc.h"
#include "libavutil/tx.h"
#include "avfilter.h"
#include "formats.h"
#include "framesync.h"
#include "internal.h"
#include "video.h"
#define MAX_THREADS 16
typedef struct ConvolveContext {
const AVClass *class;
FFFrameSync fs;
AVTXContext *fft[4][MAX_THREADS];
AVTXContext *ifft[4][MAX_THREADS];
av_tx_fn tx_fn[4];
av_tx_fn itx_fn[4];
int fft_len[4];
int planewidth[4];
int planeheight[4];
int primarywidth[4];
int primaryheight[4];
int secondarywidth[4];
int secondaryheight[4];
AVComplexFloat *fft_hdata_in[4];
AVComplexFloat *fft_vdata_in[4];
AVComplexFloat *fft_hdata_out[4];
AVComplexFloat *fft_vdata_out[4];
AVComplexFloat *fft_hdata_impulse_in[4];
AVComplexFloat *fft_vdata_impulse_in[4];
AVComplexFloat *fft_hdata_impulse_out[4];
AVComplexFloat *fft_vdata_impulse_out[4];
int depth;
int planes;
int impulse;
float noise;
int nb_planes;
int got_impulse[4];
void (*get_input)(struct ConvolveContext *s, AVComplexFloat *fft_hdata,
AVFrame *in, int w, int h, int n, int plane, float scale);
void (*get_output)(struct ConvolveContext *s, AVComplexFloat *input, AVFrame *out,
int w, int h, int n, int plane, float scale);
void (*prepare_impulse)(AVFilterContext *ctx, AVFrame *impulsepic, int plane);
int (*filter)(AVFilterContext *ctx, void *arg, int jobnr, int nb_jobs);
} ConvolveContext;
#define OFFSET(x) offsetof(ConvolveContext, x)
#define FLAGS AV_OPT_FLAG_FILTERING_PARAM|AV_OPT_FLAG_VIDEO_PARAM
static const AVOption convolve_options[] = {
{ "planes", "set planes to convolve", OFFSET(planes), AV_OPT_TYPE_INT, {.i64=7}, 0, 15, FLAGS },
{ "impulse", "when to process impulses", OFFSET(impulse), AV_OPT_TYPE_INT, {.i64=1}, 0, 1, FLAGS, "impulse" },
{ "first", "process only first impulse, ignore rest", 0, AV_OPT_TYPE_CONST, {.i64=0}, 0, 0, FLAGS, "impulse" },
{ "all", "process all impulses", 0, AV_OPT_TYPE_CONST, {.i64=1}, 0, 0, FLAGS, "impulse" },
{ "noise", "set noise", OFFSET(noise), AV_OPT_TYPE_FLOAT, {.dbl=0.0000001}, 0, 1, FLAGS },
{ NULL },
};
static const enum AVPixelFormat pixel_fmts_fftfilt[] = {
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_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
};
static int config_input(AVFilterLink *inlink)
{
ConvolveContext *s = inlink->dst->priv;
const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(inlink->format);
const int w = inlink->w;
const int h = inlink->h;
s->planewidth[1] = s->planewidth[2] = AV_CEIL_RSHIFT(w, desc->log2_chroma_w);
s->planewidth[0] = s->planewidth[3] = w;
s->planeheight[1] = s->planeheight[2] = AV_CEIL_RSHIFT(h, desc->log2_chroma_h);
s->planeheight[0] = s->planeheight[3] = h;
s->nb_planes = desc->nb_components;
s->depth = desc->comp[0].depth;
for (int i = 0; i < s->nb_planes; i++) {
int w = s->planewidth[i];
int h = s->planeheight[i];
int n = FFMAX(w, h);
s->fft_len[i] = 1 << (av_log2(2 * n - 1));
if (!(s->fft_hdata_in[i] = av_calloc(s->fft_len[i], s->fft_len[i] * sizeof(AVComplexFloat))))
return AVERROR(ENOMEM);
if (!(s->fft_hdata_out[i] = av_calloc(s->fft_len[i], s->fft_len[i] * sizeof(AVComplexFloat))))
return AVERROR(ENOMEM);
if (!(s->fft_vdata_in[i] = av_calloc(s->fft_len[i], s->fft_len[i] * sizeof(AVComplexFloat))))
return AVERROR(ENOMEM);
if (!(s->fft_vdata_out[i] = av_calloc(s->fft_len[i], s->fft_len[i] * sizeof(AVComplexFloat))))
return AVERROR(ENOMEM);
if (!(s->fft_hdata_impulse_in[i] = av_calloc(s->fft_len[i], s->fft_len[i] * sizeof(AVComplexFloat))))
return AVERROR(ENOMEM);
if (!(s->fft_vdata_impulse_in[i] = av_calloc(s->fft_len[i], s->fft_len[i] * sizeof(AVComplexFloat))))
return AVERROR(ENOMEM);
if (!(s->fft_hdata_impulse_out[i] = av_calloc(s->fft_len[i], s->fft_len[i] * sizeof(AVComplexFloat))))
return AVERROR(ENOMEM);
if (!(s->fft_vdata_impulse_out[i] = av_calloc(s->fft_len[i], s->fft_len[i] * sizeof(AVComplexFloat))))
return AVERROR(ENOMEM);
}
return 0;
}
static int config_input_impulse(AVFilterLink *inlink)
{
AVFilterContext *ctx = inlink->dst;
if (ctx->inputs[0]->w != ctx->inputs[1]->w ||
ctx->inputs[0]->h != ctx->inputs[1]->h) {
av_log(ctx, AV_LOG_ERROR, "Width and height of input videos must be same.\n");
return AVERROR(EINVAL);
}
return 0;
}
typedef struct ThreadData {
AVComplexFloat *hdata_in, *vdata_in;
AVComplexFloat *hdata_out, *vdata_out;
int plane, n;
} ThreadData;
static int fft_horizontal(AVFilterContext *ctx, void *arg, int jobnr, int nb_jobs)
{
ConvolveContext *s = ctx->priv;
ThreadData *td = arg;
AVComplexFloat *hdata_in = td->hdata_in;
AVComplexFloat *hdata_out = td->hdata_out;
const int plane = td->plane;
const int n = td->n;
int start = (n * jobnr) / nb_jobs;
int end = (n * (jobnr+1)) / nb_jobs;
int y;
for (y = start; y < end; y++) {
s->tx_fn[plane](s->fft[plane][jobnr], hdata_out + y * n, hdata_in + y * n, sizeof(float));
}
return 0;
}
#define SQR(x) ((x) * (x))
static void get_zeropadded_input(ConvolveContext *s,
AVComplexFloat *fft_hdata,
AVFrame *in, int w, int h,
int n, int plane, float scale)
{
float sum = 0.f;
float mean, dev;
int y, x;
if (s->depth == 8) {
for (y = 0; y < h; y++) {
const uint8_t *src = in->data[plane] + in->linesize[plane] * y;
for (x = 0; x < w; x++)
sum += src[x];
}
mean = sum / (w * h);
sum = 0.f;
for (y = 0; y < h; y++) {
const uint8_t *src = in->data[plane] + in->linesize[plane] * y;
for (x = 0; x < w; x++)
sum += SQR(src[x] - mean);
}
dev = sqrtf(sum / (w * h));
scale /= dev;
for (y = 0; y < h; y++) {
const uint8_t *src = in->data[plane] + in->linesize[plane] * y;
for (x = 0; x < w; x++) {
fft_hdata[y * n + x].re = (src[x] - mean) * scale;
fft_hdata[y * n + x].im = 0;
}
for (x = w; x < n; x++) {
fft_hdata[y * n + x].re = 0;
fft_hdata[y * n + x].im = 0;
}
}
for (y = h; y < n; y++) {
for (x = 0; x < n; x++) {
fft_hdata[y * n + x].re = 0;
fft_hdata[y * n + x].im = 0;
}
}
} else {
for (y = 0; y < h; y++) {
const uint16_t *src = (const uint16_t *)(in->data[plane] + in->linesize[plane] * y);
for (x = 0; x < w; x++)
sum += src[x];
}
mean = sum / (w * h);
sum = 0.f;
for (y = 0; y < h; y++) {
const uint16_t *src = (const uint16_t *)(in->data[plane] + in->linesize[plane] * y);
for (x = 0; x < w; x++)
sum += SQR(src[x] - mean);
}
dev = sqrtf(sum / (w * h));
scale /= dev;
for (y = 0; y < h; y++) {
const uint16_t *src = (const uint16_t *)(in->data[plane] + in->linesize[plane] * y);
for (x = 0; x < w; x++) {
fft_hdata[y * n + x].re = (src[x] - mean) * scale;
fft_hdata[y * n + x].im = 0;
}
for (x = w; x < n; x++) {
fft_hdata[y * n + x].re = 0;
fft_hdata[y * n + x].im = 0;
}
}
for (y = h; y < n; y++) {
for (x = 0; x < n; x++) {
fft_hdata[y * n + x].re = 0;
fft_hdata[y * n + x].im = 0;
}
}
}
}
static void get_input(ConvolveContext *s, AVComplexFloat *fft_hdata,
AVFrame *in, int w, int h, int n, int plane, float scale)
{
const int iw = (n - w) / 2, ih = (n - h) / 2;
int y, x;
if (s->depth == 8) {
for (y = 0; y < h; y++) {
const uint8_t *src = in->data[plane] + in->linesize[plane] * y;
for (x = 0; x < w; x++) {
fft_hdata[(y + ih) * n + iw + x].re = src[x] * scale;
fft_hdata[(y + ih) * n + iw + x].im = 0;
}
for (x = 0; x < iw; x++) {
fft_hdata[(y + ih) * n + x].re = fft_hdata[(y + ih) * n + iw].re;
fft_hdata[(y + ih) * n + x].im = 0;
}
for (x = n - iw; x < n; x++) {
fft_hdata[(y + ih) * n + x].re = fft_hdata[(y + ih) * n + n - iw - 1].re;
fft_hdata[(y + ih) * n + x].im = 0;
}
}
for (y = 0; y < ih; y++) {
for (x = 0; x < n; x++) {
fft_hdata[y * n + x].re = fft_hdata[ih * n + x].re;
fft_hdata[y * n + x].im = 0;
}
}
for (y = n - ih; y < n; y++) {
for (x = 0; x < n; x++) {
fft_hdata[y * n + x].re = fft_hdata[(n - ih - 1) * n + x].re;
fft_hdata[y * n + x].im = 0;
}
}
} else {
for (y = 0; y < h; y++) {
const uint16_t *src = (const uint16_t *)(in->data[plane] + in->linesize[plane] * y);
for (x = 0; x < w; x++) {
fft_hdata[(y + ih) * n + iw + x].re = src[x] * scale;
fft_hdata[(y + ih) * n + iw + x].im = 0;
}
for (x = 0; x < iw; x++) {
fft_hdata[(y + ih) * n + x].re = fft_hdata[(y + ih) * n + iw].re;
fft_hdata[(y + ih) * n + x].im = 0;
}
for (x = n - iw; x < n; x++) {
fft_hdata[(y + ih) * n + x].re = fft_hdata[(y + ih) * n + n - iw - 1].re;
fft_hdata[(y + ih) * n + x].im = 0;
}
}
for (y = 0; y < ih; y++) {
for (x = 0; x < n; x++) {
fft_hdata[y * n + x].re = fft_hdata[ih * n + x].re;
fft_hdata[y * n + x].im = 0;
}
}
for (y = n - ih; y < n; y++) {
for (x = 0; x < n; x++) {
fft_hdata[y * n + x].re = fft_hdata[(n - ih - 1) * n + x].re;
fft_hdata[y * n + x].im = 0;
}
}
}
}
static int fft_vertical(AVFilterContext *ctx, void *arg, int jobnr, int nb_jobs)
{
ConvolveContext *s = ctx->priv;
ThreadData *td = arg;
AVComplexFloat *hdata = td->hdata_out;
AVComplexFloat *vdata_in = td->vdata_in;
AVComplexFloat *vdata_out = td->vdata_out;
const int plane = td->plane;
const int n = td->n;
int start = (n * jobnr) / nb_jobs;
int end = (n * (jobnr+1)) / nb_jobs;
int y, x;
for (y = start; y < end; y++) {
for (x = 0; x < n; x++) {
vdata_in[y * n + x].re = hdata[x * n + y].re;
vdata_in[y * n + x].im = hdata[x * n + y].im;
}
s->tx_fn[plane](s->fft[plane][jobnr], vdata_out + y * n, vdata_in + y * n, sizeof(float));
}
return 0;
}
static int ifft_vertical(AVFilterContext *ctx, void *arg, int jobnr, int nb_jobs)
{
ConvolveContext *s = ctx->priv;
ThreadData *td = arg;
AVComplexFloat *hdata = td->hdata_out;
AVComplexFloat *vdata_out = td->vdata_out;
AVComplexFloat *vdata_in = td->vdata_in;
const int plane = td->plane;
const int n = td->n;
int start = (n * jobnr) / nb_jobs;
int end = (n * (jobnr+1)) / nb_jobs;
int y, x;
for (y = start; y < end; y++) {
s->itx_fn[plane](s->ifft[plane][jobnr], vdata_out + y * n, vdata_in + y * n, sizeof(float));
for (x = 0; x < n; x++) {
hdata[x * n + y].re = vdata_out[y * n + x].re;
hdata[x * n + y].im = vdata_out[y * n + x].im;
}
}
return 0;
}
static int ifft_horizontal(AVFilterContext *ctx, void *arg, int jobnr, int nb_jobs)
{
ConvolveContext *s = ctx->priv;
ThreadData *td = arg;
AVComplexFloat *hdata_out = td->hdata_out;
AVComplexFloat *hdata_in = td->hdata_in;
const int plane = td->plane;
const int n = td->n;
int start = (n * jobnr) / nb_jobs;
int end = (n * (jobnr+1)) / nb_jobs;
int y;
for (y = start; y < end; y++) {
s->itx_fn[plane](s->ifft[plane][jobnr], hdata_out + y * n, hdata_in + y * n, sizeof(float));
}
return 0;
}
static void get_xoutput(ConvolveContext *s, AVComplexFloat *input, AVFrame *out,
int w, int h, int n, int plane, float scale)
{
const int imax = (1 << s->depth) - 1;
scale *= imax * 16;
if (s->depth == 8) {
for (int y = 0; y < h; y++) {
uint8_t *dst = out->data[plane] + y * out->linesize[plane];
for (int x = 0; x < w; x++)
dst[x] = av_clip_uint8(input[y * n + x].re * scale);
}
} else {
for (int y = 0; y < h; y++) {
uint16_t *dst = (uint16_t *)(out->data[plane] + y * out->linesize[plane]);
for (int x = 0; x < w; x++)
dst[x] = av_clip(input[y * n + x].re * scale, 0, imax);
}
}
}
static void get_output(ConvolveContext *s, AVComplexFloat *input, AVFrame *out,
int w, int h, int n, int plane, float scale)
{
const int max = (1 << s->depth) - 1;
const int hh = h / 2;
const int hw = w / 2;
int y, x;
if (s->depth == 8) {
for (y = 0; y < hh; y++) {
uint8_t *dst = out->data[plane] + (y + hh) * out->linesize[plane] + hw;
for (x = 0; x < hw; x++)
dst[x] = av_clip_uint8(input[y * n + x].re * scale);
}
for (y = 0; y < hh; y++) {
uint8_t *dst = out->data[plane] + (y + hh) * out->linesize[plane];
for (x = 0; x < hw; x++)
dst[x] = av_clip_uint8(input[y * n + n - hw + x].re * scale);
}
for (y = 0; y < hh; y++) {
uint8_t *dst = out->data[plane] + y * out->linesize[plane] + hw;
for (x = 0; x < hw; x++)
dst[x] = av_clip_uint8(input[(n - hh + y) * n + x].re * scale);
}
for (y = 0; y < hh; y++) {
uint8_t *dst = out->data[plane] + y * out->linesize[plane];
for (x = 0; x < hw; x++)
dst[x] = av_clip_uint8(input[(n - hh + y) * n + n - hw + x].re * scale);
}
} else {
for (y = 0; y < hh; y++) {
uint16_t *dst = (uint16_t *)(out->data[plane] + (y + hh) * out->linesize[plane] + hw * 2);
for (x = 0; x < hw; x++)
dst[x] = av_clip(input[y * n + x].re * scale, 0, max);
}
for (y = 0; y < hh; y++) {
uint16_t *dst = (uint16_t *)(out->data[plane] + (y + hh) * out->linesize[plane]);
for (x = 0; x < hw; x++)
dst[x] = av_clip(input[y * n + n - hw + x].re * scale, 0, max);
}
for (y = 0; y < hh; y++) {
uint16_t *dst = (uint16_t *)(out->data[plane] + y * out->linesize[plane] + hw * 2);
for (x = 0; x < hw; x++)
dst[x] = av_clip(input[(n - hh + y) * n + x].re * scale, 0, max);
}
for (y = 0; y < hh; y++) {
uint16_t *dst = (uint16_t *)(out->data[plane] + y * out->linesize[plane]);
for (x = 0; x < hw; x++)
dst[x] = av_clip(input[(n - hh + y) * n + n - hw + x].re * scale, 0, max);
}
}
}
static int complex_multiply(AVFilterContext *ctx, void *arg, int jobnr, int nb_jobs)
{
ConvolveContext *s = ctx->priv;
ThreadData *td = arg;
AVComplexFloat *input = td->hdata_in;
AVComplexFloat *filter = td->vdata_in;
const float noise = s->noise;
const int n = td->n;
int start = (n * jobnr) / nb_jobs;
int end = (n * (jobnr+1)) / nb_jobs;
int y, x;
for (y = start; y < end; y++) {
int yn = y * n;
for (x = 0; x < n; x++) {
float re, im, ire, iim;
re = input[yn + x].re;
im = input[yn + x].im;
ire = filter[yn + x].re + noise;
iim = filter[yn + x].im;
input[yn + x].re = ire * re - iim * im;
input[yn + x].im = iim * re + ire * im;
}
}
return 0;
}
static int complex_xcorrelate(AVFilterContext *ctx, void *arg, int jobnr, int nb_jobs)
{
ThreadData *td = arg;
AVComplexFloat *input = td->hdata_in;
AVComplexFloat *filter = td->vdata_in;
const int n = td->n;
const float scale = 1.f / (n * n);
int start = (n * jobnr) / nb_jobs;
int end = (n * (jobnr+1)) / nb_jobs;
for (int y = start; y < end; y++) {
int yn = y * n;
for (int x = 0; x < n; x++) {
float re, im, ire, iim;
re = input[yn + x].re;
im = input[yn + x].im;
ire = filter[yn + x].re * scale;
iim = -filter[yn + x].im * scale;
input[yn + x].re = ire * re - iim * im;
input[yn + x].im = iim * re + ire * im;
}
}
return 0;
}
static int complex_divide(AVFilterContext *ctx, void *arg, int jobnr, int nb_jobs)
{
ConvolveContext *s = ctx->priv;
ThreadData *td = arg;
AVComplexFloat *input = td->hdata_in;
AVComplexFloat *filter = td->vdata_in;
const float noise = s->noise;
const int n = td->n;
int start = (n * jobnr) / nb_jobs;
int end = (n * (jobnr+1)) / nb_jobs;
int y, x;
for (y = start; y < end; y++) {
int yn = y * n;
for (x = 0; x < n; x++) {
float re, im, ire, iim, div;
re = input[yn + x].re;
im = input[yn + x].im;
ire = filter[yn + x].re;
iim = filter[yn + x].im;
div = ire * ire + iim * iim + noise;
input[yn + x].re = (ire * re + iim * im) / div;
input[yn + x].im = (ire * im - iim * re) / div;
}
}
return 0;
}
static void prepare_impulse(AVFilterContext *ctx, AVFrame *impulsepic, int plane)
{
ConvolveContext *s = ctx->priv;
const int n = s->fft_len[plane];
const int w = s->secondarywidth[plane];
const int h = s->secondaryheight[plane];
ThreadData td;
float total = 0;
if (s->depth == 8) {
for (int y = 0; y < h; y++) {
const uint8_t *src = (const uint8_t *)(impulsepic->data[plane] + y * impulsepic->linesize[plane]) ;
for (int x = 0; x < w; x++) {
total += src[x];
}
}
} else {
for (int y = 0; y < h; y++) {
const uint16_t *src = (const uint16_t *)(impulsepic->data[plane] + y * impulsepic->linesize[plane]) ;
for (int x = 0; x < w; x++) {
total += src[x];
}
}
}
total = FFMAX(1, total);
s->get_input(s, s->fft_hdata_impulse_in[plane], impulsepic, w, h, n, plane, 1.f / total);
td.n = n;
td.plane = plane;
td.hdata_in = s->fft_hdata_impulse_in[plane];
td.vdata_in = s->fft_vdata_impulse_in[plane];
td.hdata_out = s->fft_hdata_impulse_out[plane];
td.vdata_out = s->fft_vdata_impulse_out[plane];
ff_filter_execute(ctx, fft_horizontal, &td, NULL,
FFMIN3(MAX_THREADS, n, ff_filter_get_nb_threads(ctx)));
ff_filter_execute(ctx, fft_vertical, &td, NULL,
FFMIN3(MAX_THREADS, n, ff_filter_get_nb_threads(ctx)));
s->got_impulse[plane] = 1;
}
static void prepare_secondary(AVFilterContext *ctx, AVFrame *secondary, int plane)
{
ConvolveContext *s = ctx->priv;
const int n = s->fft_len[plane];
ThreadData td;
s->get_input(s, s->fft_hdata_impulse_in[plane], secondary,
s->secondarywidth[plane],
s->secondaryheight[plane],
n, plane, 1.f);
td.n = n;
td.plane = plane;
td.hdata_in = s->fft_hdata_impulse_in[plane];
td.vdata_in = s->fft_vdata_impulse_in[plane];
td.hdata_out = s->fft_hdata_impulse_out[plane];
td.vdata_out = s->fft_vdata_impulse_out[plane];
ff_filter_execute(ctx, fft_horizontal, &td, NULL,
FFMIN3(MAX_THREADS, n, ff_filter_get_nb_threads(ctx)));
ff_filter_execute(ctx, fft_vertical, &td, NULL,
FFMIN3(MAX_THREADS, n, ff_filter_get_nb_threads(ctx)));
s->got_impulse[plane] = 1;
}
static int do_convolve(FFFrameSync *fs)
{
AVFilterContext *ctx = fs->parent;
AVFilterLink *outlink = ctx->outputs[0];
ConvolveContext *s = ctx->priv;
AVFrame *mainpic = NULL, *impulsepic = NULL;
int ret, plane;
ret = ff_framesync_dualinput_get(fs, &mainpic, &impulsepic);
if (ret < 0)
return ret;
if (!impulsepic)
return ff_filter_frame(outlink, mainpic);
for (plane = 0; plane < s->nb_planes; plane++) {
AVComplexFloat *filter = s->fft_vdata_impulse_out[plane];
AVComplexFloat *input = s->fft_vdata_out[plane];
const int n = s->fft_len[plane];
const int w = s->primarywidth[plane];
const int h = s->primaryheight[plane];
const int ow = s->planewidth[plane];
const int oh = s->planeheight[plane];
ThreadData td;
if (!(s->planes & (1 << plane))) {
continue;
}
td.plane = plane, td.n = n;
s->get_input(s, s->fft_hdata_in[plane], mainpic, w, h, n, plane, 1.f);
td.hdata_in = s->fft_hdata_in[plane];
td.vdata_in = s->fft_vdata_in[plane];
td.hdata_out = s->fft_hdata_out[plane];
td.vdata_out = s->fft_vdata_out[plane];
ff_filter_execute(ctx, fft_horizontal, &td, NULL,
FFMIN3(MAX_THREADS, n, ff_filter_get_nb_threads(ctx)));
ff_filter_execute(ctx, fft_vertical, &td, NULL,
FFMIN3(MAX_THREADS, n, ff_filter_get_nb_threads(ctx)));
if ((!s->impulse && !s->got_impulse[plane]) || s->impulse) {
s->prepare_impulse(ctx, impulsepic, plane);
}
td.hdata_in = input;
td.vdata_in = filter;
ff_filter_execute(ctx, s->filter, &td, NULL,
FFMIN3(MAX_THREADS, n, ff_filter_get_nb_threads(ctx)));
td.hdata_in = s->fft_hdata_out[plane];
td.vdata_in = s->fft_vdata_out[plane];
td.hdata_out = s->fft_hdata_in[plane];
td.vdata_out = s->fft_vdata_in[plane];
ff_filter_execute(ctx, ifft_vertical, &td, NULL,
FFMIN3(MAX_THREADS, n, ff_filter_get_nb_threads(ctx)));
td.hdata_out = s->fft_hdata_out[plane];
td.hdata_in = s->fft_hdata_in[plane];
ff_filter_execute(ctx, ifft_horizontal, &td, NULL,
FFMIN3(MAX_THREADS, n, ff_filter_get_nb_threads(ctx)));
s->get_output(s, s->fft_hdata_out[plane], mainpic, ow, oh, n, plane, 1.f / (n * n));
}
return ff_filter_frame(outlink, mainpic);
}
static int config_output(AVFilterLink *outlink)
{
const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(outlink->format);
AVFilterContext *ctx = outlink->src;
ConvolveContext *s = ctx->priv;
AVFilterLink *mainlink = ctx->inputs[0];
AVFilterLink *secondlink = ctx->inputs[1];
int ret, i, j;
s->primarywidth[1] = s->primarywidth[2] = AV_CEIL_RSHIFT(mainlink->w, desc->log2_chroma_w);
s->primarywidth[0] = s->primarywidth[3] = mainlink->w;
s->primaryheight[1] = s->primaryheight[2] = AV_CEIL_RSHIFT(mainlink->h, desc->log2_chroma_h);
s->primaryheight[0] = s->primaryheight[3] = mainlink->h;
s->secondarywidth[1] = s->secondarywidth[2] = AV_CEIL_RSHIFT(secondlink->w, desc->log2_chroma_w);
s->secondarywidth[0] = s->secondarywidth[3] = secondlink->w;
s->secondaryheight[1] = s->secondaryheight[2] = AV_CEIL_RSHIFT(secondlink->h, desc->log2_chroma_h);
s->secondaryheight[0] = s->secondaryheight[3] = secondlink->h;
s->fs.on_event = do_convolve;
ret = ff_framesync_init_dualinput(&s->fs, ctx);
if (ret < 0)
return ret;
outlink->w = mainlink->w;
outlink->h = mainlink->h;
outlink->time_base = mainlink->time_base;
outlink->sample_aspect_ratio = mainlink->sample_aspect_ratio;
outlink->frame_rate = mainlink->frame_rate;
if ((ret = ff_framesync_configure(&s->fs)) < 0)
return ret;
for (i = 0; i < s->nb_planes; i++) {
for (j = 0; j < MAX_THREADS; j++) {
float scale;
ret = av_tx_init(&s->fft[i][j], &s->tx_fn[i], AV_TX_FLOAT_FFT, 0, s->fft_len[i], &scale, 0);
if (ret < 0)
return ret;
ret = av_tx_init(&s->ifft[i][j], &s->itx_fn[i], AV_TX_FLOAT_FFT, 1, s->fft_len[i], &scale, 0);
if (ret < 0)
return ret;
}
}
return 0;
}
static int activate(AVFilterContext *ctx)
{
ConvolveContext *s = ctx->priv;
return ff_framesync_activate(&s->fs);
}
static av_cold int init(AVFilterContext *ctx)
{
ConvolveContext *s = ctx->priv;
if (!strcmp(ctx->filter->name, "convolve")) {
s->filter = complex_multiply;
s->prepare_impulse = prepare_impulse;
s->get_input = get_input;
s->get_output = get_output;
} else if (!strcmp(ctx->filter->name, "xcorrelate")) {
s->filter = complex_xcorrelate;
s->prepare_impulse = prepare_secondary;
s->get_input = get_zeropadded_input;
s->get_output = get_xoutput;
} else if (!strcmp(ctx->filter->name, "deconvolve")) {
s->filter = complex_divide;
s->prepare_impulse = prepare_impulse;
s->get_input = get_input;
s->get_output = get_output;
} else {
return AVERROR_BUG;
}
return 0;
}
static av_cold void uninit(AVFilterContext *ctx)
{
ConvolveContext *s = ctx->priv;
int i, j;
for (i = 0; i < 4; i++) {
av_freep(&s->fft_hdata_in[i]);
av_freep(&s->fft_vdata_in[i]);
av_freep(&s->fft_hdata_out[i]);
av_freep(&s->fft_vdata_out[i]);
av_freep(&s->fft_hdata_impulse_in[i]);
av_freep(&s->fft_vdata_impulse_in[i]);
av_freep(&s->fft_hdata_impulse_out[i]);
av_freep(&s->fft_vdata_impulse_out[i]);
for (j = 0; j < MAX_THREADS; j++) {
av_tx_uninit(&s->fft[i][j]);
av_tx_uninit(&s->ifft[i][j]);
}
}
ff_framesync_uninit(&s->fs);
}
static const AVFilterPad convolve_inputs[] = {
{
.name = "main",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = config_input,
},{
.name = "impulse",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = config_input_impulse,
},
};
static const AVFilterPad convolve_outputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = config_output,
},
};
FRAMESYNC_AUXILIARY_FUNCS(convolve, ConvolveContext, fs)
#if CONFIG_CONVOLVE_FILTER
FRAMESYNC_DEFINE_PURE_CLASS(convolve, "convolve", convolve, convolve_options);
const AVFilter ff_vf_convolve = {
.name = "convolve",
.description = NULL_IF_CONFIG_SMALL("Convolve first video stream with second video stream."),
.preinit = convolve_framesync_preinit,
.init = init,
.uninit = uninit,
.activate = activate,
.priv_size = sizeof(ConvolveContext),
.priv_class = &convolve_class,
FILTER_INPUTS(convolve_inputs),
FILTER_OUTPUTS(convolve_outputs),
FILTER_PIXFMTS_ARRAY(pixel_fmts_fftfilt),
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_INTERNAL | AVFILTER_FLAG_SLICE_THREADS,
};
#endif /* CONFIG_CONVOLVE_FILTER */
#if CONFIG_DECONVOLVE_FILTER
static const AVOption deconvolve_options[] = {
{ "planes", "set planes to deconvolve", OFFSET(planes), AV_OPT_TYPE_INT, {.i64=7}, 0, 15, FLAGS },
{ "impulse", "when to process impulses", OFFSET(impulse), AV_OPT_TYPE_INT, {.i64=1}, 0, 1, FLAGS, "impulse" },
{ "first", "process only first impulse, ignore rest", 0, AV_OPT_TYPE_CONST, {.i64=0}, 0, 0, FLAGS, "impulse" },
{ "all", "process all impulses", 0, AV_OPT_TYPE_CONST, {.i64=1}, 0, 0, FLAGS, "impulse" },
{ "noise", "set noise", OFFSET(noise), AV_OPT_TYPE_FLOAT, {.dbl=0.0000001}, 0, 1, FLAGS },
{ NULL },
};
FRAMESYNC_DEFINE_PURE_CLASS(deconvolve, "deconvolve", convolve, deconvolve_options);
const AVFilter ff_vf_deconvolve = {
.name = "deconvolve",
.description = NULL_IF_CONFIG_SMALL("Deconvolve first video stream with second video stream."),
.preinit = convolve_framesync_preinit,
.init = init,
.uninit = uninit,
.activate = activate,
.priv_size = sizeof(ConvolveContext),
.priv_class = &deconvolve_class,
FILTER_INPUTS(convolve_inputs),
FILTER_OUTPUTS(convolve_outputs),
FILTER_PIXFMTS_ARRAY(pixel_fmts_fftfilt),
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_INTERNAL | AVFILTER_FLAG_SLICE_THREADS,
};
#endif /* CONFIG_DECONVOLVE_FILTER */
#if CONFIG_XCORRELATE_FILTER
static const AVOption xcorrelate_options[] = {
{ "planes", "set planes to cross-correlate", OFFSET(planes), AV_OPT_TYPE_INT, {.i64=7}, 0, 15, FLAGS },
{ "secondary", "when to process secondary frame", OFFSET(impulse), AV_OPT_TYPE_INT, {.i64=1}, 0, 1, FLAGS, "impulse" },
{ "first", "process only first secondary frame, ignore rest", 0, AV_OPT_TYPE_CONST, {.i64=0}, 0, 0, FLAGS, "impulse" },
{ "all", "process all secondary frames", 0, AV_OPT_TYPE_CONST, {.i64=1}, 0, 0, FLAGS, "impulse" },
{ NULL },
};
FRAMESYNC_DEFINE_PURE_CLASS(xcorrelate, "xcorrelate", convolve, xcorrelate_options);
static int config_input_secondary(AVFilterLink *inlink)
{
AVFilterContext *ctx = inlink->dst;
if (ctx->inputs[0]->w <= ctx->inputs[1]->w ||
ctx->inputs[0]->h <= ctx->inputs[1]->h) {
av_log(ctx, AV_LOG_ERROR, "Width and height of second input videos must be less than first input.\n");
return AVERROR(EINVAL);
}
return 0;
}
static const AVFilterPad xcorrelate_inputs[] = {
{
.name = "primary",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = config_input,
},{
.name = "secondary",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = config_input_secondary,
},
};
static const AVFilterPad xcorrelate_outputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = config_output,
},
};
const AVFilter ff_vf_xcorrelate = {
.name = "xcorrelate",
.description = NULL_IF_CONFIG_SMALL("Cross-correlate first video stream with second video stream."),
.preinit = convolve_framesync_preinit,
.init = init,
.uninit = uninit,
.activate = activate,
.priv_size = sizeof(ConvolveContext),
.priv_class = &xcorrelate_class,
FILTER_INPUTS(xcorrelate_inputs),
FILTER_OUTPUTS(xcorrelate_outputs),
FILTER_PIXFMTS_ARRAY(pixel_fmts_fftfilt),
.flags = AVFILTER_FLAG_SUPPORT_TIMELINE_INTERNAL | AVFILTER_FLAG_SLICE_THREADS,
};
#endif /* CONFIG_XCORRELATE_FILTER */
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