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ffmpeg/libavfilter/vf_dnn_processing.c

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/*
* Copyright (c) 2019 Guo Yejun
*
* 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
*/
/**
* @file
* implementing a generic image processing filter using deep learning networks.
*/
#include "libavutil/opt.h"
#include "libavutil/pixdesc.h"
#include "libavutil/avassert.h"
#include "libavutil/imgutils.h"
#include "filters.h"
#include "dnn_filter_common.h"
#include "internal.h"
#include "video.h"
#include "libswscale/swscale.h"
#include "libavutil/time.h"
typedef struct DnnProcessingContext {
const AVClass *class;
DnnContext dnnctx;
struct SwsContext *sws_uv_scale;
int sws_uv_height;
} DnnProcessingContext;
#define OFFSET(x) offsetof(DnnProcessingContext, dnnctx.x)
#define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM
static const AVOption dnn_processing_options[] = {
{ "dnn_backend", "DNN backend", OFFSET(backend_type), AV_OPT_TYPE_INT, { .i64 = DNN_TF }, INT_MIN, INT_MAX, FLAGS, .unit = "backend" },
#if (CONFIG_LIBTENSORFLOW == 1)
{ "tensorflow", "tensorflow backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = DNN_TF }, 0, 0, FLAGS, .unit = "backend" },
#endif
#if (CONFIG_LIBOPENVINO == 1)
{ "openvino", "openvino backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = DNN_OV }, 0, 0, FLAGS, .unit = "backend" },
#endif
#if (CONFIG_LIBTORCH == 1)
{ "torch", "torch backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = DNN_TH }, 0, 0, FLAGS, "backend" },
#endif
DNN_COMMON_OPTIONS
{ NULL }
};
AVFILTER_DEFINE_CLASS(dnn_processing);
static av_cold int init(AVFilterContext *context)
{
DnnProcessingContext *ctx = context->priv;
return ff_dnn_init(&ctx->dnnctx, DFT_PROCESS_FRAME, context);
}
static const enum AVPixelFormat pix_fmts[] = {
AV_PIX_FMT_RGB24, AV_PIX_FMT_BGR24,
AV_PIX_FMT_GRAY8, AV_PIX_FMT_GRAYF32,
AV_PIX_FMT_YUV420P, AV_PIX_FMT_YUV422P,
AV_PIX_FMT_YUV444P, AV_PIX_FMT_YUV410P, AV_PIX_FMT_YUV411P,
AV_PIX_FMT_NV12,
AV_PIX_FMT_NONE
};
#define LOG_FORMAT_CHANNEL_MISMATCH() \
av_log(ctx, AV_LOG_ERROR, \
"the frame's format %s does not match " \
"the model input channel %d\n", \
av_get_pix_fmt_name(fmt), \
model_input->dims[dnn_get_channel_idx_by_layout(model_input->layout)]);
static int check_modelinput_inlink(const DNNData *model_input, const AVFilterLink *inlink)
{
AVFilterContext *ctx = inlink->dst;
enum AVPixelFormat fmt = inlink->format;
int width_idx, height_idx;
width_idx = dnn_get_width_idx_by_layout(model_input->layout);
height_idx = dnn_get_height_idx_by_layout(model_input->layout);
// the design is to add explicit scale filter before this filter
if (model_input->dims[height_idx] != -1 &&
model_input->dims[height_idx] != inlink->h) {
av_log(ctx, AV_LOG_ERROR, "the model requires frame height %d but got %d\n",
model_input->dims[height_idx],
inlink->h);
return AVERROR(EIO);
}
if (model_input->dims[width_idx] != -1 &&
model_input->dims[width_idx] != inlink->w) {
av_log(ctx, AV_LOG_ERROR, "the model requires frame width %d but got %d\n",
model_input->dims[width_idx],
inlink->w);
return AVERROR(EIO);
}
if (model_input->dt != DNN_FLOAT) {
avpriv_report_missing_feature(ctx, "data type rather than DNN_FLOAT");
return AVERROR(EIO);
}
switch (fmt) {
case AV_PIX_FMT_RGB24:
case AV_PIX_FMT_BGR24:
if (model_input->dims[dnn_get_channel_idx_by_layout(model_input->layout)] != 3) {
LOG_FORMAT_CHANNEL_MISMATCH();
return AVERROR(EIO);
}
return 0;
case AV_PIX_FMT_GRAY8:
case AV_PIX_FMT_GRAYF32:
case AV_PIX_FMT_YUV420P:
case AV_PIX_FMT_YUV422P:
case AV_PIX_FMT_YUV444P:
case AV_PIX_FMT_YUV410P:
case AV_PIX_FMT_YUV411P:
case AV_PIX_FMT_NV12:
if (model_input->dims[dnn_get_channel_idx_by_layout(model_input->layout)] != 1) {
LOG_FORMAT_CHANNEL_MISMATCH();
return AVERROR(EIO);
}
return 0;
default:
avpriv_report_missing_feature(ctx, "%s", av_get_pix_fmt_name(fmt));
return AVERROR(EIO);
}
return 0;
}
static int config_input(AVFilterLink *inlink)
{
AVFilterContext *context = inlink->dst;
DnnProcessingContext *ctx = context->priv;
int result;
DNNData model_input;
int check;
result = ff_dnn_get_input(&ctx->dnnctx, &model_input);
if (result != 0) {
av_log(ctx, AV_LOG_ERROR, "could not get input from the model\n");
return result;
}
check = check_modelinput_inlink(&model_input, inlink);
if (check != 0) {
return check;
}
return 0;
}
static av_always_inline int isPlanarYUV(enum AVPixelFormat pix_fmt)
{
const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(pix_fmt);
av_assert0(desc);
return !(desc->flags & AV_PIX_FMT_FLAG_RGB) && desc->nb_components == 3;
}
static int prepare_uv_scale(AVFilterLink *outlink)
{
AVFilterContext *context = outlink->src;
DnnProcessingContext *ctx = context->priv;
AVFilterLink *inlink = context->inputs[0];
enum AVPixelFormat fmt = inlink->format;
if (isPlanarYUV(fmt)) {
if (inlink->w != outlink->w || inlink->h != outlink->h) {
if (fmt == AV_PIX_FMT_NV12) {
ctx->sws_uv_scale = sws_getContext(inlink->w >> 1, inlink->h >> 1, AV_PIX_FMT_YA8,
outlink->w >> 1, outlink->h >> 1, AV_PIX_FMT_YA8,
SWS_BICUBIC, NULL, NULL, NULL);
ctx->sws_uv_height = inlink->h >> 1;
} else {
const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(fmt);
int sws_src_h = AV_CEIL_RSHIFT(inlink->h, desc->log2_chroma_h);
int sws_src_w = AV_CEIL_RSHIFT(inlink->w, desc->log2_chroma_w);
int sws_dst_h = AV_CEIL_RSHIFT(outlink->h, desc->log2_chroma_h);
int sws_dst_w = AV_CEIL_RSHIFT(outlink->w, desc->log2_chroma_w);
ctx->sws_uv_scale = sws_getContext(sws_src_w, sws_src_h, AV_PIX_FMT_GRAY8,
sws_dst_w, sws_dst_h, AV_PIX_FMT_GRAY8,
SWS_BICUBIC, NULL, NULL, NULL);
ctx->sws_uv_height = sws_src_h;
}
}
}
return 0;
}
static int config_output(AVFilterLink *outlink)
{
AVFilterContext *context = outlink->src;
DnnProcessingContext *ctx = context->priv;
int result;
AVFilterLink *inlink = context->inputs[0];
// have a try run in case that the dnn model resize the frame
result = ff_dnn_get_output(&ctx->dnnctx, inlink->w, inlink->h, &outlink->w, &outlink->h);
if (result != 0) {
av_log(ctx, AV_LOG_ERROR, "could not get output from the model\n");
return result;
}
prepare_uv_scale(outlink);
return 0;
}
static int copy_uv_planes(DnnProcessingContext *ctx, AVFrame *out, const AVFrame *in)
{
const AVPixFmtDescriptor *desc;
int uv_height;
if (!ctx->sws_uv_scale) {
av_assert0(in->height == out->height && in->width == out->width);
desc = av_pix_fmt_desc_get(in->format);
uv_height = AV_CEIL_RSHIFT(in->height, desc->log2_chroma_h);
for (int i = 1; i < 3; ++i) {
int bytewidth = av_image_get_linesize(in->format, in->width, i);
if (bytewidth < 0) {
return AVERROR(EINVAL);
}
av_image_copy_plane(out->data[i], out->linesize[i],
in->data[i], in->linesize[i],
bytewidth, uv_height);
}
} else if (in->format == AV_PIX_FMT_NV12) {
sws_scale(ctx->sws_uv_scale, (const uint8_t **)(in->data + 1), in->linesize + 1,
0, ctx->sws_uv_height, out->data + 1, out->linesize + 1);
} else {
sws_scale(ctx->sws_uv_scale, (const uint8_t **)(in->data + 1), in->linesize + 1,
0, ctx->sws_uv_height, out->data + 1, out->linesize + 1);
sws_scale(ctx->sws_uv_scale, (const uint8_t **)(in->data + 2), in->linesize + 2,
0, ctx->sws_uv_height, out->data + 2, out->linesize + 2);
}
return 0;
}
static int flush_frame(AVFilterLink *outlink, int64_t pts, int64_t *out_pts)
{
DnnProcessingContext *ctx = outlink->src->priv;
int ret;
DNNAsyncStatusType async_state;
ret = ff_dnn_flush(&ctx->dnnctx);
if (ret != 0) {
return -1;
}
do {
AVFrame *in_frame = NULL;
AVFrame *out_frame = NULL;
async_state = ff_dnn_get_result(&ctx->dnnctx, &in_frame, &out_frame);
if (out_frame) {
if (isPlanarYUV(in_frame->format))
copy_uv_planes(ctx, out_frame, in_frame);
av_frame_free(&in_frame);
ret = ff_filter_frame(outlink, out_frame);
if (ret < 0)
return ret;
if (out_pts)
*out_pts = out_frame->pts + pts;
}
av_usleep(5000);
} while (async_state >= DAST_NOT_READY);
return 0;
}
static int activate(AVFilterContext *filter_ctx)
{
AVFilterLink *inlink = filter_ctx->inputs[0];
AVFilterLink *outlink = filter_ctx->outputs[0];
DnnProcessingContext *ctx = filter_ctx->priv;
AVFrame *in = NULL, *out = NULL;
int64_t pts;
int ret, status;
int got_frame = 0;
int async_state;
FF_FILTER_FORWARD_STATUS_BACK(outlink, inlink);
do {
// drain all input frames
ret = ff_inlink_consume_frame(inlink, &in);
if (ret < 0)
return ret;
if (ret > 0) {
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);
if (ff_dnn_execute_model(&ctx->dnnctx, in, out) != 0) {
return AVERROR(EIO);
}
}
} while (ret > 0);
// drain all processed frames
do {
AVFrame *in_frame = NULL;
AVFrame *out_frame = NULL;
async_state = ff_dnn_get_result(&ctx->dnnctx, &in_frame, &out_frame);
if (out_frame) {
if (isPlanarYUV(in_frame->format))
copy_uv_planes(ctx, out_frame, in_frame);
av_frame_free(&in_frame);
ret = ff_filter_frame(outlink, out_frame);
if (ret < 0)
return ret;
got_frame = 1;
}
} while (async_state == DAST_SUCCESS);
// if frame got, schedule to next filter
if (got_frame)
return 0;
if (ff_inlink_acknowledge_status(inlink, &status, &pts)) {
if (status == AVERROR_EOF) {
int64_t out_pts = pts;
ret = flush_frame(outlink, pts, &out_pts);
ff_outlink_set_status(outlink, status, out_pts);
return ret;
}
}
FF_FILTER_FORWARD_WANTED(outlink, inlink);
return 0;
}
static av_cold void uninit(AVFilterContext *ctx)
{
DnnProcessingContext *context = ctx->priv;
sws_freeContext(context->sws_uv_scale);
ff_dnn_uninit(&context->dnnctx);
}
static const AVFilterPad dnn_processing_inputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = config_input,
},
};
static const AVFilterPad dnn_processing_outputs[] = {
{
.name = "default",
.type = AVMEDIA_TYPE_VIDEO,
.config_props = config_output,
},
};
const AVFilter ff_vf_dnn_processing = {
.name = "dnn_processing",
.description = NULL_IF_CONFIG_SMALL("Apply DNN processing filter to the input."),
.priv_size = sizeof(DnnProcessingContext),
.init = init,
.uninit = uninit,
FILTER_INPUTS(dnn_processing_inputs),
FILTER_OUTPUTS(dnn_processing_outputs),
FILTER_PIXFMTS_ARRAY(pix_fmts),
.priv_class = &dnn_processing_class,
.activate = activate,
};
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